ALBERT

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Description: A cyber-physical system (CPS) is an integration of computation with physical processes whose behavior is defined by both computational and physical parts of the system. In this paper, we present a view of the challenges and opportunities for design automation of CPS. We identify a combination of characteristics that define the challenges unique to the design automation of CPS. We then present selected promising advances in depth, focusing on four foundational directions: combining model-based and data-driven design methods; design for human-in-the-loop systems; component-based design with contracts, and design for security and privacy. These directions are illustrated with examples from two application domains: smart energy systems and next-generation automotive systems.

Description: Accurate yield estimation under parametric variation is one of the most integral parts for robust and nonwasted circuit design. In particular, due to the significant impact of disparity on the high-replication circuit, precise yield estimation is essential in SRAM design. In this paper, we propose an enhanced perturbation vector generation method to improve the accuracy of the yield estimation of the conventional direct SRAM yield computation method, which are access disturb margin (ADM) and write margin (WRM) first, by splitting the concave yield metric space, the estimation error caused by linear approximation can be significantly reduced with minor increase in simulation runtime. In addition, to compensate the inaccuracy of the conventional perturbation vector, a calibration method to reflect the multi-dc condition in SRAM assist operations is also proposed. Numerical results show that 37% improved estimation accuracy and 29% reduced estimation error can be achieved compared to the conventional ADM/WRM in the wide voltage range.

Description: With CMOS scaling beyond 14 nm, reliability is a major concern for IC manufacturers. Reliability-aware design has a non-negligible overhead and cannot account for user experience in mobile devices. An alternative is dynamic reliability management (DRM), which counteracts degradation by adapting the operating conditions at runtime. In this paper, for the first time we formulate DRM as an optimization problem that accounts for reliability, temperature and performance. We develop an optimal policy for multicores using convex optimization, and show that it is not feasible to implement on real systems. For this reason, we propose workload-aware reliability management (WARM), a fast DRM technique adapting to diverse workload requirements to trade reliability and user experience. WARM is implemented and tested on a real Android device. WARM approximates the solution of the convex solver within 5% on average, while executing more than $400 {\times }$ faster. WARM integrates a thermal controller that allocates tasks to meet thermal constraints. This is required since degradation strongly depends on temperature. We show that WARM meets temperature constraints within 5% in 87.5% more cases than the state-of-the-art. We show that WARM task allocation achieves up to one year lifetime improvement for a multicore platform. It can achieve up to 100% of performance improvement on cluster architectures, such as big.LITTLE, while still guaranteeing the reliability target. Finally, we show that it achieves performance in the 4% of the maximum for a broad range of a applications, while meeting the reliability constraints.

Description: On-chip bus implementations must be bug-free and secure to provide the functionality and performance required by modern system-on-a-chip (SoC) designs. Regardless of the specific topology and protocol, bus behavior is never fully specified, meaning there exist cycles/conditions where some bus signals are irrelevant, and ignored by the verification effort. We highlight the susceptibility of current bus implementations to Hardware Trojans hiding in this partially specified behavior, and present a model for creating a covert Trojan communication channel between SoC components for any bus topology and protocol. By only altering existing bus signals during the period where their behaviors are unspecified , the Trojan channel is very difficult to detect. We give Trojan channel circuitry specifics for AMBA AXI4 and advanced peripheral bus (APB), then create a simple system comprised of several master and slave units connected by an AXI4-Lite interconnect to quantify the overhead of the Trojan channel and illustrate the ability of our Trojans to evade a suite of protocol compliance checking assertions from ARM. We also create an SoC design running a multiuser Linux OS to demonstrate how a Trojan communication channel can allow an unprivileged user access to root-user data. We then outline several detection strategies for this class of Hardware Trojan.

Description: Scan test data compression is widely used in industry to reduce test data volume (TDV) and test application time (TAT). This paper shows how multiple scan chain expansion ratios can help to obtain high test data compression in system-on-chips. Scan chains are partitioned with a higher expansion ratio than normal in scan compression mode and then are gradually concatenated based on a cost function to detect any faults that could not be detected at the higher expansion ratios. It improves the overall test compression ratio since it potentially allows faults to be detected at the highest expansion ratio. This paper introduces a new cost function to choose scan chain concatenation candidates for concatenation for multiple expansion ratios. To avoid TDV and TAT increase by scan concatenation, the proposed method takes a logic structure and scan chain length into consideration. Experiment results show the proposed method reduces TAT and TDV by 53%–64% compared with a traditional scan compression method.

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Description: Double-gate devices, like independent-gate (IG) FinFET, have introduced new possibilities and challenges in synthesis of transistor networks. Existing factorization methods and graph-based optimizations are not actually the most effective way to generate optimized IG FinFET based networks because only reducing the number of literals in a given Boolean expression does not guarantee the minimum transistor count. This paper presents two novel methods aiming the minimization of the number of devices in logic networks. The first contribution is a method for defactoring Boolean expressions able to apply the conventional factorization algorithms together with IG FinFET particularities, so improving it. The second contribution is a novel graph-based method that improves even more transistor arrangements by exploiting enhanced nonseries-parallel associations. Experimental results shown a significant reduction in the size of transistor networks delivered by the proposed methods.

Description: For complex datapaths, resource sharing can help reduce area consumption. Traditionally, resource sharing is applied when the same resource can be scheduled for different uses in different cycles, often resulting in a longer schedule. Multipumping is a method whereby a resource is clocked at a frequency that is a multiple of the surrounding circuit, thereby offering multiple executions per global clock cycle. This allows a single resource to be shared among multiple uses in the same cycle. This concept maps well to modern field-programmable gate arrays (FPGAs), where hard macro blocks are typically capable of running at higher frequencies than most designs implemented in the logic fabric. While this technique has been demonstrated for static resources, modern digital signal processing (DSP) blocks are flexible, supporting varied operations at runtime. In this paper, we demonstrate multipumping for resource sharing of the flexible DSP48E1 macros in Xilinx FPGAs. We exploit their dynamic programmability to enable resource sharing for the full set of supported DSP block operations, and compare this to multipumping only multipliers and DSP blocks with fixed configurations. The proposed approach saves on average 48% DSP blocks at a cost of 74% more LUTs, effectively saving 30% equivalent LUT area and is feasible for the majority of designs, in which clock frequency is typically below half the maximum supported by the DSP blocks.

Description: Counterfeit integrated circuits (IC) can be very harmful to the security and reliability of critical applications. Physical unclonable functions (PUFs) have been proposed as a mechanism for uniquely identifying ICs and thus reducing the prevalence of counterfeits. However, maintaining large databases of PUF challenge response pairs (CRPs) and dealing with PUF errors make it difficult to use PUFs reliably. This paper presents an innovative approach to authenticate CRPs on PUF-based ICs. The proposed method can tolerate considerable bit errors from responses of PUFs without the use of error correcting codes. Different types of optimization methods are applied to improve the overall performance. The simulation shows that it is successful in authenticating 99.96% authorized chips and filtering out 99.92% cloned chips by tolerating 12 errors in 128 bits. The results are verified with ring oscillator PUF and arbiter PUF implementations on Kintex-7 FPGA. The approach saves hardware and software resources significantly, compared to those of other authentication solutions.

Description: Due to the emergence of extremely high density memory along with the growing number of embedded memories, memory yield is an important issue. Memory self-repair using redundancies to increase the yield of memories is widely used. Because high density memories are vulnerable to soft errors, memory error correction code (ECC) plays an important role in memory design. In this paper, methods to exploit spare columns including replaced defective columns are proposed to improve memory ECC. To utilize replaced defective columns, the defect information needs to be stored. Two approaches to store defect information are proposed—one is to use a spare column and the other is to use a content-addressable-memory. Experimental results show that the proposed method can significantly enhance the ECC performance.

Description: A distance metric of patterns is crucial to hotspot cluster analysis and classification. In this paper, we propose an improved tangent space (ITS)-based distance metric for hotspot cluster analysis and classification. The proposed distance metric is an important extension of the well-developed tangent space method in computer vision. It can handle patterns containing multiple polygons, while the traditional tangent space method can only deal with patterns with a single polygon. It inherits most of the advantages of the traditional tangent space method, e.g., it is easy to compute and is tolerant with small variations or shifts of the shapes. The ITS-based distance metric is a more reliable and accurate metric for hotspot cluster analysis and classification. We also propose a hierarchical density-based clustering method for hotspot clustering. It is more suitable for arbitrary shaped clusters.

Description: The effects of soft errors in processor cores have been widely studied. However, little has been published about soft errors in uncore components, such as the memory subsystem and I/O controllers, of a system-on-a-chip (SoC). In this paper, we study how soft errors in uncore components affect system-level behaviors. We have created a new mixed-mode simulation platform that combines simulators at two different levels of abstraction, and achieves $20~000{\times }$ speedup over register-transfer-level-only simulation. Using this platform, we present the first study of the system-level impact of soft errors inside various uncore components of a large-scale, multicore SoC using the industrial-grade, open-source OpenSPARC T2 SoC design. Our results show that soft errors in uncore components can significantly impact system-level reliability. We also demonstrate that uncore soft errors can create major challenges for traditional system-level checkpoint recovery techniques. To overcome such recovery challenges, we present a new replay recovery technique for uncore components belonging to the memory subsystem. For the L2 cache controller and the dynamic random-access memory controller components of OpenSPARC T2, our new technique reduces the probability that an application run fails to produce correct results due to soft errors by more than $50 {\times }$ with 1.82% and 2.58% chip-level area and power impact, respectively.

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Description: Phase change memory (PCM), given its nonvolatility, potential high density, and low standby power, is a promising candidate to be used as main memory in next generation computer systems. However, to hide its shortcomings of limited endurance and slow write performance, state-of-the-art solutions tend to construct a dynamic RAM (DRAM)-PCM hybrid memory and place write-intensive pages in DRAM. While existing optimizations to this hybrid architecture focus on tuning DRAM configurations to reduce the number of write operations to PCM, this paper explores the interactions between DRAM and PCM to improve both the performance and the endurance of a DRAM-PCM hybrid main memory. Specifically, it exploits the flexibility of mapping virtual pages to physical pages, and develops a proactive strategy to allocate pages taking both program segments and DRAM conflict misses into consideration, thus distributing those heavily written pages across different DRAM sets. Meanwhile, a lifetime-aware DRAM replacement algorithm and a conflict-aware page remapping strategy are proposed to further reduce DRAM misses and PCM writes. Experiments confirm that the proposed techniques are able to improve average memory hit time and reduce maximum PCM write counts thus enhancing both performance and lifetime of a DRAM-PCM hybrid main memory.

Description: Guide-patterns (GPs) are critical to the construction of contacts and vias in directed self-assembly (DSA) lithography. Simulations can be used to verify GPs, but runtime is excessive. Instead, we categorize the shapes of GPs using a small number of geometric parameters. Then a verification function is built to predict whether a GP will produce the required contacts, as follows: a vector in parameter space is constructed to represent each GP in a test set; the acceptability of each GP is then assessed by DSA simulation, and each vector is tagged “good” or “bad” accordingly; next, the parameter space is deformed to convert a radial distribution into one in which the good and bad vectors can be separated by a hyper-plane, which finally becomes the verification function. We also show how to reduce the dimensionality of the parameter space by principal component analysis, and how to generalize the geometric description of GPs to allow different types of GP to be verified in a uniform fashion. The proposed GP verification is demonstrated in 10 nm technology.

Description: In deep-submicron very large scale integration manufacturing, dummy fills are widely applied to reduce topographic variations and improve layout pattern uniformity. However, the introduction of dummy fills may impact the wire electrical properties, such as coupling capacitance. Traditional tile-based method for fill insertion usually results in very large number of fills, which increases the cost of layout storage. In advanced technology nodes, solving the tile-based dummy fill design is more and more expensive. In this paper, we propose a high performance dummy fill insertion framework based on geometric properties to optimize multiple objectives simultaneously, including coupling capacitance, density variations and gradient. The experimental results for ICCAD 2014 contest benchmarks demonstrate the effectiveness of our methods.

Description: Analog CMOS integrated circuits (ICs) designs depend typically on designer knowledge and experience, as such problems are multivariate and multiobjective, presenting many combinations of input variables to be investigated in order to meet the required specifications. Nowadays, the a posteriori approach is widely used to perform the optimization processes of analog CMOS ICs using evolutionary algorithms. However, these techniques are not totally able to explore potential solutions in specific regions of the Pareto front. Designers then have difficulty in choosing the best solution capable of achieving all desired specifications simultaneously among all the ones found. In this context, the a priori approach using fitness functions has become an important alternative method to overcome these issues of the a posteriori methodology. This paper aims to compare different fitness function profiles used in the a priori optimization processes to boost the effectiveness of the search processes in relation to robustness, accuracy, and yield in analog CMOS ICs designs. We show that the Gaussian profile, proposed here, applied to the lower limit, center value, and upper limit fitness functions is able to improve all the a priori optimization evolutionary techniques investigated, including the genetic, imperialist competitive, and shuffled frog leaping algorithms.

Description: Vertically integrated circuits (3-D ICs) may revitalize Moore’s law scaling which has slowed down in recent years. 3-D stacking is an emerging technology that stacks multiple dies vertically to achieve higher transistor density independent of device scaling. They provide high-density vertical interconnects, which can reduce interconnect power and delay. Moreover, 3-D ICs can integrate disparate circuit technologies into a single chip, thereby unlocking new system-on-chip architectures that do not exist in 2-D technology. While 3-D integration could bring new architectural opportunities and significant performance enhancement, new thermal, power delivery, signal integrity and reliability challenges emerge as power consumption grows, and device density increases. Moreover, the significant expansion of CPU design space in 3-D requires new architectural models and methodologies for design space exploration (DSE). New design tools and methods are required to address these 3-D-specific challenges. This keynote paper focuses on the state of the art, ongoing advances and future challenges of 3-D IC design tools and methods. The primary focus of this paper is TSV-based 3-D ICs, although we also discuss recent advances in monolithic 3-D ICs. The objective of this paper is to provide a unified perspective on the fundamental opportunities and challenges posed by 3-D ICs especially from the context of design tools and methods. We also discuss the methodology of co-design to address more complicated and interdependent design problems in 3-D IC, and conclude with a discussion of the remaining challenges and open problems that must be overcome to make 3-D IC technology commercially viable.

Description: Nonvolatile static random access memory (nvSRAM) has been widely investigated as a promising on-chip memory architecture in energy harvesting sensor nodes, due to zero standby power, resilience to power failures, and fast read/write operations. However, conventional approaches back up all data from static random access memory into nonvolatile memory when power failures happen. It leads to significant energy overhead and peak inrush current, which has a negative impact on the system performance and circuit reliability. This paper proposes a holistic data backup optimization to mitigate these problems in nvSRAM, consisting of a partial backup algorithm and a run-time adaptive write policy. A statistic dead-block predictor is employed to achieve dead block identification with trivial hardware overhead. An adaptive policy is used to switch between write-back and write-through strategy to reduce the rollback induced by backup failures. Experimental results show that the proposed scheme improves the performance by 4.6% on average while the backup power consumption and the inrush current are reduced by 38.1% and 54% on average compared to the full backup scheme. What is more, the backup capacitor size for energy buffer can be reduced by 40% on average under the same performance constraint.

Description: Layout-level gate or routing camouflaging techniques have attracted interest as countermeasures against reverse engineering of combinational logic. In order to minimize area overhead, typically only a subset of gate or routing components are camouflaged, and each camouflaged component layout can implement one of a few different functions or connections. The security of camouflaging relies on the difficulty of learning the overall combinational logic function without knowing the functions implemented by the individual camouflaged components of the circuit. In this paper, we expand our previous work on using incremental SAT solving to reconstruct the logical function of a circuit with camouflaged components. Our algorithm uses the standard attacker model in which an adversary knows only the noncamouflaged component functions, and has the ability to query the circuit to learn the correct output vector for any input vector. Our results demonstrate a $10.5\times$ speedup in average runtime over the best known existing deobfuscation algorithm prior to this technique. The results presented go beyond our previous work by showing that this technique, previously applied only to a particular style of gate camouflaging, is general and can be used to deobfuscate three different proposed styles of camouflaging. We give results to quantify the effectiveness of camouflaging techniques on a variety of ISCAS-85 benchmark circuits.

Description: The continuous globalization of the semiconductor industry has significantly raised the vulnerability of chips under hardware Trojan (HT) attacks. It is extremely challenging to detect HTs in fabricated chips due to the existence of process variations (PVs), since PVs may cause larger impacts than HTs. In this paper, we propose a novel framework for HT detection in digital integrated circuits. The goal of this paper is to detect HTs inserted during fabrication. The HT detection problem is formulated as an under-determined linear system by a sparse gate profiling technique, and the existence of HTs is mapped to the sparse solution of the linear system. A Bayesian inference-based calibration technique is proposed to recover PVs for each chip for the sparse gate profiling technique. A batch of under-determined linear systems are solved together by the well-studied simultaneous orthogonal matching pursuit algorithm to get their common sparse solution. Experimental results show that even under big measurement errors, the proposed framework gets quite high HT detection rates with low measurement cost.

Description: Smart systems represent a broad class of intelligent, miniaturized devices incorporating functionality like sensing, actuation, and control. In order to support these functions, they must include sophisticated and heterogeneous components, such as sensors and actuators, multiple power sources and storage devices, digital signal processing, and wireless connectivity. The high degree of heterogeneity typical of smart systems has a heavy impact on their design: the challenges are not in fact restricted to their functionality, but are also related to a number of extra-functional properties, including power consumption, temperature, and aging. Current simulation- or model-based design approaches do not target a smart system as a whole, but rather single domains (digital, analog, power devices, etc.) or properties. This paper tries to overcome this limitation by proposing a framework for the concurrent simulation of both functionality and such extra-functional properties. The latter are modeled as different information flows, managed by dedicated “virtual buses” and formalized through the adoption of IP-XACT. SystemC, through the support of physical and continuous time modeling provided by its analog and mixed signal extension, is used to implement both functional and extra-functional models. Experimental results show the efficiency, accuracy and modularity of the proposed approach on an example case study, in which substantial speedups with respect to standard model-based design tools go along with a very high degree of accuracy (< 10 −5 %). Furthermore, the case study highlights that the proposed framework allows to easily capture at run time the mutual impact of properties, e.g., in case of power and temperature.

Description: Monolithic 3-D (M3D) integrated circuits (ICs) are an emerging technology that offer much higher integration densities than previous 3-D IC approaches. In this paper, we present a complete netlist-to-layout design flow to design an M3D block, as well as to integrate 2-D and 3-D blocks into an M3D SoC. This design flow is based on commercial tools built for 2-D ICs, and enhanced with our 3-D specific methodologies. We use the OpenSPARC T2 SoC as a case study, implement it in a 28-nm fully depleted silicon on insulator foundry process, and demonstrate that we can achieve up to 12% and 8% power savings for a single block and SoC, respectively, when compared with their 2-D counterparts implemented using commercial tools.

Description: The performance of nanometer-scale circuits is adversely affected by aging induced by bias temperature instability (BTI) and hot carrier injection (HCI). Both BTI and HCI impact transistor electrical parameters at a level that depends on the operating environment and usage of the circuit. This paper presents a novel method, using on-chip sensors based on ring oscillators (ROSCs), to detect the delay shifts in circuits as a result of aging. Our method uses presilicon analysis of the circuit to compute calibration factors that can translate BTI- and HCI-induced delay shifts in the ROSC to those in the circuit of interest. Our simulations show that the delay estimates are within 1% of the true values from presilicon analysis. Further, for post-silicon analysis, a refinement strategy is proposed where sensor measurements can be amalgamated with infrequent online delay measurements on the monitored circuit to partially capture its true workloads. This leads to about 8% lower delay guardbanding overheads compared to the conventional methods as demonstrated using benchmark circuits.

Description: After the 3-D stacking, 3-D-ICs based on through-silicon-vias (TSVs) must be inspected for any TSV defects such as resistive open or bridge defects. In some research studies, several effective testing techniques have been developed such as parallel or serial test architectures, which measure the voltage across a single TSV with a comparator. However, in the current test architectures, hardware overhead and test time are proportional to the number of TSVs. In this paper, we propose a new unified test architecture for screening of TSV defects in 3-D-ICs. Depending on the number of assembled TSVs, the proposed grouping-based test architecture can effectively reduce the cumulative test time and hardware overhead without compromising the test quality.

Description: Cryptographic architectures provide different security properties to sensitive usage models. However, unless reliability of architectures is guaranteed, such security properties can be undermined through natural or malicious faults. In this paper, two underlying block ciphers which can be used in authenticated encryption algorithms are considered, i.e., light encryption device and high security and lightweight block ciphers. The former is of the Advanced Encryption Standard type and has been considered area-efficient, while the latter constitutes a Feistel network structure and is suitable for low-complexity and low-power embedded security applications. In this paper, we propose efficient error detection architectures including variants of recomputing with encoded operands and signature-based schemes to detect both transient and permanent faults. Authenticated encryption is applied in cryptography to provide confidentiality, integrity, and authenticity simultaneously to the message sent in a communication channel. In this paper, we show that the proposed schemes are applicable to the case study of simple lightweight CFB for providing authenticated encryption with associated data. The error simulations are performed using Xilinx Integrated Synthesis Environment tool and the results are benchmarked for the Xilinx FPGA family Virtex-7 to assess the reliability capability and efficiency of the proposed architectures.

Description: Network on chip (NoC) is a scalable interconnection architecture for ever increasing communication demand between processing cores. However, in nanoscale technology size, NoC lifetime is limited due to aging processes of negative bias temperature instability, hot carrier injection, and electromigration. Usually, because of unbalanced utilization of NoC resources, some parts of the network experience more thermal stress and duty cycle in comparison with other parts, which may accelerate chip failure. To slow down the aging rate of NoC, this paper proposes an oblivious routing algorithm called location-based aging-resilient Xy-Yx (LAXY) to distribute packet flow over entire network. LAXY is based on the fact that dimension-ordered routing algorithms imposes the highest traffic load on the central nodes in mesh topologies. To balance the traffic over the network, certain routers at the east and the west of NoC, with dimension-order XY routing, statically are configured as YX. Various configurations have been explored for LAXY and the simulations show a specific configuration, called Fishtail , increases mean time to failure of the routers and interconnects by about 42% and 56%, respectively. Moreover, by balancing the load over the network, LAXY improves overall packet latency by about 7% in average, with negligible area overhead.

Description: This paper develops a merging procedure for functional test sequences that achieves test compaction for a pool of functional test sequences by reducing the number of sequences in the pool. The procedure has the following new features: 1) in contrast to existing selection procedures, the merging procedure described in this paper increases the fault coverage of test sequences in the pool, thus enhancing the ability to reduce the number of sequences and 2) in contrast to existing procedures that concatenate or merge test sequences, the procedure described in this paper does not increase the lengths of the sequences it merges. The procedure is based on the concept of restoration of test vectors. In the context of test sequence merging, restoration consists of copying test vectors from a test sequence $ {T_{j}}$ into a test sequence $ {T_{i}}$ in order to allow $ {T_{i}}$ to detect faults that $ {T_{j}}$ detects. The merging procedure focuses on the removal of one test sequence $ {T_{j}}$ at a time by restoring test vectors from $ {T_{j}}$ into other sequences, allowing them to detect the faults that $ {T_{j}}$ detects. Experimental results for benchmark circuits demonstrate that the procedure reduces the number of sequences in a pool significantly.

Description: Parallelizing the memory accesses in a nested loop is a critical challenge to facilitate loop pipelining. An effective approach for high-level synthesis on field-programmable gate array is to map these accesses to multiple on-chip memory banks using a memory partitioning technique. In this paper, we propose an efficient memory partitioning algorithm with low overhead and low time complexity for parallel data access via data reuse. We find that for most applications in image and video processing, a large amount of data can be reused among different iterations of a loop nest. Motivated by this observation, we propose to cache reusable data using on-chip registers, organized as register chains. The nonreusable data are then separated into several memory banks by a memory partitioning algorithm. We revise the existing padding method to cover cases occurring frequently in our method wherein certain components of partition vector are zeros. Experimental results have demonstrated that compared with the state-of-the-art algorithms, the proposed method is efficient in terms of execution time, resource overhead, and power consumption across a wide range of access patterns extracted from applications in image and video processing. As for the testing patterns, the execution time is typically less than one millisecond. And the number of required memory banks is reduced by 59.7% on average, which leads to an average reduction of 78.2% in look-up tables, 65.5% in flip-flops, 37.1% in DSP48Es, and therefore 74.8% reduction in dynamic power consumption. Moreover, the storage overhead incurred by the proposed method is zero for most widely used access patterns in image filtering.

Description: Motivated by the bus escape routing problem in printed circuit boards (PCBs), we study the following optimization problem: given a set of rectangles attached to the boundary of a rectangular region, find a subset of nonoverlapping rectangles with maximum total weight. We present an efficient algorithm that solves this problem optimally in ${O(n^{4})}$ time, where ${n}$ is the number of rectangles in the input instance. This improves over the best previous ${O(n^{6})}$ -time algorithm available for the problem. We also present two efficient approximation algorithms for the problem that find near-optimal solutions with guaranteed approximation factors. The first algorithm finds a 2-approximate solution in ${O(n^{2})}$ time, and the second one computes a ${4/3}$ -approximation in ${O(n^{3})}$ time. The experimental results demonstrate the efficiency of both our exact and approximation algorithms.

Description: The use of formal models to describe early versions of the structure and the behavior of a system has become common practice in industry. UML and OCL are the de-facto specification languages for these tasks. They allow for capturing system properties and module behavior in an abstract but still formal fashion. At the same time, this enables designers to detect errors or inconsistencies in the initial phases of the design flow—even if the implementation has not already started. Corresponding tools for verification of formal models got established in the recent past. However, verification results are usually not reused in later design steps anymore. In fact, similar verification tasks are applied again, e.g., after the implementation has been completed. This is a waste of computational and human effort. In this paper, we address this problem by proposing a method which checks a given implementation of a system against its corresponding formal method. This allows for transferring verification results already obtained from the formal model to the implementation and, eventually, motivates a new design flow which addresses verification across abstraction levels. This paper describes the applied techniques as well as their orchestration. Afterwards, the applicability of the proposed methodology is demonstrated by means of examples as well as a case study from an industrial context.

Description: Microscale mechanical networks are prevalent in lab-on-a-chip systems, which are rapidly expanding into biological, chemical, and physical research. In these systems, nano-liter volumes of fluids are manipulated and a precise control of flow in individual segments within a complex network is often desirable. One paradigm for such control suggests adjusting the hydraulic resistance of each segment, relying on the fact that like in electrical circuits, fluid flow is depended upon the relation between the potential drop (pressure difference) and the resistance of the transmitting conductor. Current solutions for the control of hydraulic resistance rely on intricate fabrication processes, are often characterized by a high-biased error and can generally produce a limited range of resistance. Here, a computer-aided design of a six-bit digitally controlled adjustable hydraulic resistor, which features five linear ranges of resistance and a small footprint is presented. This design can be rapidly embedded within a microfluidic network for real time control of fluid flow.

Description: Power supply fluctuation can be potential threat to the correct operations of processors, in the form of voltage emergency that happens when supply voltage drops below a certain threshold. Noise sensors (with either analog or digital outputs) can be placed in the nonfunction area of processors to detect voltage emergencies by monitoring the runtime voltage fluctuations. Our work addresses two important problems related to building a sensor-based voltage emergency detection system: 1) offline sensor placement, i.e., where to place the noise sensors so that the number and locations of sensors are optimized in order to strike a balance between design cost and chip reliability and 2) online voltage emergency detection, i.e., how to use these placed sensors to detect voltage emergencies in the hotspot locations. In this paper, we propose integrated solutions to these two problems, respectively, for analog and digital (more specifically, binary) sensor outputs, by exploiting the voltage correlation between the sensor candidate locations and the hotspot locations. For the analog case, we use the Group Lasso and an ordinary least squares approach; for the binary case, we integrate the Group Lasso and the SVM approach. Experimental results show that, our approach can achieve 2.3X–2.7X better voltage emergency detection results on average for analog outputs when compared to the state-of-the-art work; and for the binary case, on average our methodology can achieve up to 21% improvement in prediction accuracy compared to an approach called max-probability-no-prediction.

Description: Advances in digital microfluidic (DMF) technologies offer a promising platform for a variety of biochemical applications, ranging from massively parallel DNA analysis and computational drug discovery to toxicity monitoring and medical diagnosis. In this paper, we address the migration problem that arises when the technology undergoes a change in the context of DMFs. Given a biochemical reaction synthesized for actuation on a given DMF architecture, we discuss how the same biochemical reaction can be ported seamlessly to an enhanced architecture, with possible modifications to the architectural parameters (e.g., clock frequency, mixer size, and mixing time) or geometric changes (e.g., change in reservoir locations or mixer positions, inclusion of new sensors or other physical resources). Complete resynthesis of the protocol for the new architecture may often become either inefficient or even infeasible due to scalability, proprietary, security, or cost issues. We propose an adaptation method for handling such technology-changes by modifying the existing actuation sequence through an incremental procedure. The foundation of our method lies in symbolic encoding and satisfiability-solvers, enriched with pertinent graph-theoretic and geometric techniques. This enables us to generate functionally correct solutions for the new target architecture without necessitating a complete resynthesis step, thereby enabling the utilization of these chips by users in biology who are not familiar with the on-chip synthesis tool-flow. We highlight the benefits of the proposed approach through extensive simulations on assay benchmarks.

Description: In 3-D integrated circuits (3-D ICs), through silicon via (TSV) is a critical technique to provide vertical connections. However, the yield and reliability challenge of TSV in industry is one of key obstacles to adopt the 3-D ICs technology. Various fault-tolerance structures by using additional spare TSVs (s-TSVs) to repair faulty functional TSVs (f-TSVs) have been proposed in literature for yield and reliability enhancement. However, these structures are formed in standard cell placement stage where all the f-TSVs are already placed. In reality, since the s-TSVs can be only inserted into the whitespace, the quality of the generated repair solution is strongly dependent on the whitespace distribution. In this paper, we propose an efficient TSV planning and repair framework in floorplanning stage, which takes nonuniform TSV distribution and clustered TSV defect-distribution into account. The proposed framework mainly consists of four stages: 1) a whitespace redistribution algorithm that uses a probability-based strategy to make the whitespace distribution more reasonable for the f-TSV planning. Subsequently, a convex-cost flow-based model for f-TSV allocation considering the fault clustering; 2) a top-down globally partitioning combined with a bottom-up locally merging to partition f-TSVs into groups with minimum hardware cost; 3) the min-cost max-flow algorithm for s-TSV allocation with minimum wirelength overhead; and 4) an integer linear programming-based model to form a fault-tolerance structure with minimum multiplexer delay overhead. The experimental results demonstrate that the proposed repair framework can improve the yield with minimum hardware cost and multiplexer delay overhead.

Description: It has been a wonderful four years of steering this flagship publication. I had the privilege of coming across some of the best ideas in our field and seeing the rapid adoption of new ideas in our community. TCAD has embraced new areas in system design encompassing design and design automation of cyber physical systems, embedded systems, and Internet of Things. Our special issues and keynotes over the past few years have aimed at focusing on emerging fields such as neuromorphic computing and hardware security. TCAD continues to highlight core innovations in its traditionally strong topic areas such as physical design, synthesis, and simulation. These topics have also been strongly influenced by emergence of new devices, circuits, and computational models.

Description: Synthesis and design methodology suitable for computer-aided design tools are now emerging as major challenge for analog system designers. This paper proposes a systematic synthesis procedure which provides reusability and programmability, for linear and nonlinear analog circuits using configurable building block (CBB) and analog cell (AC). Operational transconductance amplifier-based ACs are synthesized in terms of CBBs. Reusability and programmability of the synthesis methodology have been demonstrated by realizing different types of linear and nonlinear circuits and mapping those circuits in field programmable analog array. Finally, the proposed methodology has been integrated as an electronic design automation tool AnaSyn1.0. Performance of all the proposed circuits has been verified by SPICE simulation.

Description: Modern system-on-chip designs implement sophisticated power management features to achieve better energy efficiency. This includes power-down modes for analog circuit blocks. Typically, they are implemented by additional power-down circuitry which shuts down all bias currents. During the design of power-down circuitry, it must be ensured that the circuit still meets all specifications in normal operation. Furthermore, floating nodes and asymmetric stress need to be avoided in order to reduce device degradation over time. Therefore, the manual design of power-down circuitry can become a challenging and time consuming task requiring alternating implementation and verification phases. In this paper, a power-down synthesis methodology is presented which constructs fault-free power-down circuitry by systematically applying typical shutoff patterns. Furthermore, the synthesized power-down circuitry is visualized in the circuit schematic to support the designer in capturing the structure of the inserted power-down circuitry. Finally, the sizing of power-down transistors is determined automatically. Experimental results for three amplifier circuits, a voltage controlled ring oscillator and a low voltage differential signaling driver demonstrate the efficiency and efficacy of the presented methods.

Description: Differential fault analysis of stream ciphers, such as Grain (Grain v1 and Grain-128) has been an active area of research. Several countermeasures to thwart such analysis have been also proposed in the related cryptographic literature. In this paper, we demonstrate a novel combination of power and fault analysis strategies to devise attacks against such protected implementations of Grain stream cipher. We considered clock glitch induced faults occurring in practice to construct our fault model. In addition, we developed a generic power analysis attack technique against the Grain family of stream ciphers assuming that the cipher implementation can be resynchronized multiple times with a fixed secret key and any randomly generated initialization vector. Subsequently, we combine our proposed power analysis strategy with the notion of the practically occurring faults to mount attacks on various fault attack countermeasures. In order to validate our proposed power analysis attack, we report the results of power trace classifications of a Grain v1 implementation on SASEBO-GII board. The captured power traces were analyzed using least squares support vector machine learning algorithm-based multiclass classifiers to segregate the power traces into the respective Hamming distance (HD) classes. To extract power samples with high information about HD classes, signal-to-noise ratio (SNR) metric was chosen for feature selection. The experimental results of power trace classifications of test set showed success rate as high as 92.5% when the seven largest SNR sample instants over a clock cycle were chosen as features along with a suitable kernel hyperparameter combination.

Description: Coarse-grained reconfigurable architectures (CGRAs) can provide extremely energy-efficient acceleration for applications that are rich in arithmetic operations such as digital signal processing and multimedia applications. Since those applications are often naturally represented by stream graphs, it is very compelling to develop optimization strategies for stream graphs on CGRAs. One unique property of stream graphs is that they contain many kernels or loops, which creates both advantages and challenges when it comes to mapping them to CGRAs. This paper addresses two main problems with it, namely, many-buffer problem and control overhead problem, and presents our results of optimizing the execution of stream graphs for CGRAs including our low-cost architecture extensions. Our evaluation results demonstrate that our software and hardware optimizations can help generate highly efficient mapping of stream applications to CGRAs, with $3.4boldsymbol {times }$ speedup on average at the application level over CPU-only execution, which is significant.

Description: The hybrid architecture analysis and design language (AADL) has been proposed to model the interactions between embedded control systems and continuous physical environment. However, the worst-case performance analysis of hybrid AADL designs often leads to overly pessimistic estimations, and is not suitable for accurate reasoning about overall system performance, in particular when the system closely interacts with an uncertain external environment. To address this challenge, this paper proposes a statistical model checking-based framework that can perform quantitative evaluation of uncertainty-aware hybrid AADL designs against various performance queries. Our approach extends hybrid AADL to support the modeling of environment uncertainties. Furthermore, we propose a set of transformation rules that can automatically translate AADL designs together with designers’ requirements into networks of priced timed automata and performance queries, respectively. Comprehensive experimental results on the movement authority scenario of Chinese train control system level 3 demonstrate the effectiveness of our approach.

Description: It is a significant problem to efficiently identify the frequently occurring patterns in a given dataset, so as to unveil the trends hidden behind the dataset. This paper is motivated by the serious demands of a high-performance in-memory frequent-pattern mining strategy, with joint optimization over the mining performance and system durability. While the widely used frequent-pattern tree (FP-tree) serves as an efficient approach for frequent-pattern mining, its construction procedure often makes it unfriendly for nonvolatile memories (NVMs). In particular, the incremental construction of FP-tree could generate many unnecessary writes to the NVM and greatly degrade the energy efficiency, because NVM writes typically take more time and energy than reads. To overcome the drawbacks of FP-tree on NVMs, this paper proposes evergreen FP-tree (EvFP-tree), which includes a lazy counter and a minimum-bit-altered (MBA) encoding scheme to make FP-tree friendly for NVMs. The basic idea of the lazy counter is to greatly eliminate the redundant writes generated in FP-tree construction. On the other hand, the MBA encoding scheme is to complement existing wear-leveling techniques to evenly write each memory cell to extend the NVM lifetime. As verified by experiments, EvFP-tree greatly enhances the mining performance and system lifetime by 40.28% and 87.20% on average, respectively. And EvFP-tree reduces the energy consumption by 50.30% on average.

Description: Machine-learning algorithms have shown outstanding image recognition/classification performance for computer vision applications. However, the compute and energy requirement for implementing such classifier models for large-scale problems is quite high. In this paper, we propose feature driven selective classification (FALCON) inspired by the biological visual attention mechanism in the brain to optimize the energy-efficiency of machine-learning classifiers. We use the consensus in the characteristic features (color/texture) across images in a dataset to decompose the original classification problem and construct a tree of classifiers (nodes) with a generic-to-specific transition in the classification hierarchy. The initial nodes of the tree separate the instances based on feature information and selectively enable the latter nodes to perform object specific classification. The proposed methodology allows selective activation of only those branches and nodes of the classification tree that are relevant to the input while keeping the remaining nodes idle. Additionally, we propose a programmable and scalable neuromorphic engine (NeuE) that utilizes arrays of specialized neural computational elements to execute the FALCON-based classifier models for diverse datasets. The structure of FALCON facilitates the reuse of nodes while scaling up from small classification problems to larger ones thus allowing us to construct classifier implementations that are significantly more efficient. We evaluate our approach for a 12-object classification task on the Caltech101 dataset and ten-object task on CIFAR-10 dataset by constructing FALCON models on the NeuE platform in 45-nm technology. Our results demonstrate up to $3.66boldsymbol times $ improvement in energy-efficiency for no loss in output quality, and even higher improvements of up to $5.91boldsymbol time- $ with 3.9% accuracy loss compared to an optimized baseline network. In addition, FALCON shows an improvement in training time of up to $1.96boldsymbol times $ as compared to the traditional classification approach.

Description: Multiple patterning lithography has been recognized as one of the most promising solutions, in addition to extreme ultraviolet lithography, directed self-assembly, nanoimprint lithography, and electron beam lithography, for advancing the resolution limit of conventional optical lithography. Multiple patterning layout decomposition (MPLD) becomes more challenging as advanced technology introduces complex coloring rules. Existing works model MPLD as a graph coloring problem; nevertheless, when complex coloring rules are considered, layout decomposition can no longer be modeled accurately by graph coloring. Therefore, in this paper, for capturing the essence of layout decomposition with complex coloring rules, we model the MPLD problem as an exact cover problem. We then propose a fast and exact MPLD framework based on augmented dancing links. Our method is flexible and general: it can consider the basic and complex coloring rules simultaneously, can maintain density balancing, and can handle quadruple patterning and beyond. Experimental results show that our approach outperforms state-of-the-art works on reported conflicts and stitches and is promising for handling complex coloring rules and density balancing as well.

Description: Effective transient power grid simulators are needed during design processes because a designed power grid needs to be numerously analyzed. This paper builds an efficient and reliable incremental power grid transient simulator, which we name it InTraSim, by integrating macro modeling techniques, sparse recovery mechanisms, an innovated pseudo-node value estimation method, and an initiated adaptive error control scheme. InTraSim is able to deal with not only element-value alterations of designs but also topology modifications of designs.

Description: Directed-self-assembly (DSA) technology is a promising candidate for cut printing in sub-10nm 1-D gridded designs, where cuts might need to be redistributed such that they could be patterned by DSA guiding templates. In this paper, we first propose a linear-time optimal dynamic-programming-based algorithm for a special case of the template guided cut redistribution problem, where there is at most one dummy wire segment on a track. We then extend our algorithm to general cases by applying a bipartite matching algorithm to decompose a general problem to a set of subproblems conforming to the special case (thus each of them can be solved optimally). Our resulting algorithm can achieve a provably good performance bound, with the cost of a template distribution only linearly to the problem size. Experimental results show that our algorithm can resolve all spacing rule violations, with smaller running times, compared with the previous works on a set of common benchmarks. In addition, we also extend our algorithm to consider general design rules, simple templates, and dummy cuts.

Description: In this paper, we focus on the low-power scheduling problem with multiple threshold and/or supply voltage technologies in high-level synthesis. We propose a unified scheduling approach which is applicable to various optimization problems, including: 1) dynamic power and resource usage co-optimization; 2) leakage power optimization; and 3) dynamic power and leakage power co-optimization. To deal with different objectives with high flexibility, three problems are divided into two common subproblems including delay assignment and resource density variance minimization, then a vertex potential-based mobility allocation model is proposed to solve two subproblems simultaneously. Experimental results show that, for dynamic power and resource co-optimization, our scheduling approach produces optimum solutions for all six benchmarks with 15 groups of data; for leakage power optimization it also greatly excels the latest existing work, by 20% leakage power reduction and 52 times speedup. Besides, for dynamic and leakage power co-optimization, the Pareto solutions are studied.

Description: Resistive switching devices are nonlinear electrical components that have drawn great attention in the design of new technologies including memory devices and neuromorphic circuits. In this paper, an SPICE implementation of a novel compact model is presented and put under test by means of different circuit configurations. The model is based on two identical opposite-biased diodes in series with a resistor where the switching behavior is governed by the creation and rupture of multiple conductive channels. Results show that the model is stable under different input sources and amplitudes and, with special interest, in multielement circuits. The model is validated with experimental data available in the literature. Both the corresponding SPICE code and schematic are provided in order to facilitate the model use and assessment.

Description: Yield estimation is an indispensable piece of information at the onset of high-volume production of a device, as it can inform timely process and design refinements in order to achieve high yield, rapid ramp-up, and fast time-to-market. To date, yield estimation is generally performed through simulation-based methods. However, such methods are not only very time-consuming for certain circuit classes, but also limited by the accuracy of the statistical models provided in the process design kits (PDKs). In contrast, herein we introduce yield estimation solutions which rely exclusively on silicon measurements and we apply them toward predicting yield during: 1) production migration from one fabrication facility to another and 2) transition from one design generation to the next. These solutions are applicable to any circuit, regardless of PDK accuracy and transistor-level simulation complexity, and range from rather straightforward to more sophisticated ones, capable of leveraging additional sources of silicon data. Effectiveness of the proposed yield forecasting methods is evaluated using actual high-volume production data from two 65-nm RF transceiver devices.

Description: Scan-based tests that maintain close-to-functional operation conditions are important for avoiding overtesting of delay faults while achieving the fault coverage required for avoiding test escapes. For a measurable proximity to functional operation conditions, partially functional broadside tests have a known Hamming distance between their scan-in states and reachable states. Another parameter that is important for the discussion of overtesting is the switching activity. This paper suggests a combined metric, where a reduced switching activity is taken as a safety margin that allows a higher Hamming distance between the scan-in state and a reachable state. The metric is defined such that a value of 100% or lower is preferred. To demonstrate that the metric is flexible enough to allow tests to be generated, the paper describes a test generation procedure that uses the metric.

Description: Magnetic tunnel junction (MTJ)-based devices have been studied extensively as a promising candidate to implement hybrid energy-efficient computing circuits due to their nonvolatility, high integration density, and CMOS compatibility. In this paper, MTJs are leveraged to develop a novel full adder (FA) based on 3- and 5-input majority gates. Spin Hall effect (SHE) is utilized for changing the MTJ states resulting in low-energy switching behavior. SHE-MTJ devices are modeled in Verilog-A using precise physical equations. SPICE circuit simulator is used to validate the functionality of 1-bit SHE-based FA. The simulation results show 76% and 32% improvement over previous voltage-mode MTJ-based FA in terms of energy consumption and device count, respectively. The concatanatability of our proposed 1-bit SHE-FA is investigated through developing a 4-bit SHE-FA. Finally, delay and power consumption of an ${ {n}}$ -bit SHE-based adder has been formulated to provide a basis for developing an energy efficient SHE-based ${n}$ -bit arithmetic logic unit.

Description: A false key-controlled aggressive voltage scaling (AVS) technique is proposed as a countermeasure against leakage power analysis (LPA) attacks. A random number of false keys are utilized to control the supply voltage scaling to mask the possible leakage of the information related to the correct key to a malicious attacker. Contrary to the random AVS technique, false key-controlled AVS technique can guarantee that the added false keys always exhibit higher correlation coefficients than that of the correct key even if sufficient number of plaintexts (>10 million) are enabled. As demonstrated with the simulation results, the measurement-to-disclose (MTD) value of a cryptographic circuit can be enhanced over ten million against LPA attacks by utilizing the proposed technique, while the MTD values of a conventional cryptographic circuit without countermeasure and one with random AVS are, respectively, less than 500 and 100,000.

Description: Sparse matrix-vector multiplication (SpMV) is one of the most important kernels for many applications. In this paper, we study the implementation of SpMV for scale-free matrices on many-core architectures including graphic processing units and Xeon Phi coprocessors. We first propose a hardware oblivious implementation for heterogeneous many-core processors using OpenCL. Our OpenCL implementation uses a novel SpMV format called hybrid COO+CSR (HCC), which employs 2-D jagged partitioning to balance the workload among a large number of cores and improve the data locality. Moreover, the OpenCL implementation is designed to be parametric, which allows systematic performance tuning. We conduct experiments to evaluate the efficiency of our hardware oblivious implementation. Experiments show that it achieves comparable performance to the Intel MKL and state-of-the-art OpenCL-based ViennaCL library implementation. Although the OpenCL implementation provides functional portability for heterogeneous systems, it fails to take advantage of the low-level architectural features. To further improve the performance, we propose a hardware conscious implementation using the native parallel programming language. We use the Xeon Phi platform as a case study. In our hardware conscious implementation, we ensure that the HCC format efficiently utilizes the vector process units on Xeon Phi by employing low-level intrinsics, and improve the overall performance through locality-aware block mapping, and intrablock tiling. Experiments using a wide range of representative scale-free matrices demonstrate that compared with the OpenCL-based hardware oblivious implementation, the hardware conscious implementation achieves $2.2boldsymbol {times }$ speedup on average. Compared with MKL, the hardware conscious implementation achieves $3.1boldsymbol {times }$ speedup on Xeon Phi.

Description: Due to the conventional look-up-table (LUT) using the static random access memory (SRAM) cell, field programmable gate arrays (FPGAs) almost reach the limitation in term of the density, speed, and configuration overhead. This paper proposes an improved memristor-based LUT (MLUT) circuit which is compatible with the mainstream LUT circuit in FPGA. Any arbitrary combined logic functions can be implemented in the MLUT through specific configurations. Then the MLUT shows superior advantages over the conventional LUT such as smaller area overhead and fewer data transmission. As a case study, a one-bit full adder is simulated to verify that the design is of practice in PSPICE. Moreover, the adder can be cascaded into multibit full adder demonstrating competitiveness against the conventional configurable logic block in FPGA technology. MLUT can be a candidate to replace the conventional SRAM-based LUT and further improves the performance of FPGAs.

Description: In this paper, we propose Lagrangian relaxation (LR)-based algorithms to optimize both circuit performance and total wirelength at the global placement stage. We introduce a general timing-driven global placement problem formulation that is applicable to three different circuit design styles: 1) synchronous circuits; 2) synchronous circuits with sequential optimization techniques; and 3) asynchronous circuits. LR is applied to handle the timing constraints of the formulated problem. Based on how the cell spreading constraints are handled, two different approaches are proposed: one approach handles the spreading constraints inside the LR framework and transforms the timing-driven placement (TDP) problem into a series of weighted wirelength minimization problems, which can be solved by directly leveraging existing wirelength-driven placers. The other approach handles the spreading constraints outside the LR framework. Thus, only timing constraints need to be taken care of in the LR framework and better solutions can be expected. In both approaches, we simplified the LR subproblem using Karush–Kuhn–Tucker conditions. Our algorithms are implemented based on a state-of-the-art wirelength-driven quadratic placer. The experiments demonstrate that the proposed algorithms are able to achieve significant improvements on circuit performance compared with a commercial wirelength-driven placement flow and a commercial asynchronous TDP flow.

Description: This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.

Description: Internet-of-Things (IoT) is the technical backbone of smart cities which are envisioned to cope up with rapid urbanization of human population with limited resources. IoT provides three key features of smart cities such as intelligence, interconnection, and instrumentation. IoT is essentially a system-of-systems which can be considered as a configurable dynamic global network of networks. The main components of IoT include the following: 1) The Things; 2) Internet; 3) LAN; and 4) The Cloud. IoT is built by various diverse components including electronics, sensors, actuators, controllers, networks, firmware, and software. However, the existing electronics, controllers, and processors do not meet IoT requirements, such as multiple sensors, communication protocols, and security requirements. The existing computer-aided design (CAD) or electronic design automation tools are not enough to meet diverse challenges such as time-to-market, complexity, and cost of IoT. The required electronic circuits and systems need to be developed by handling and solving specific requirements. Real-time and ultralow power plays a major role since mobile devices in the IoT have to provide a long availability with a relative small energy budget. At the same time, reliability, availability, real-time constraints, and performance requirements pose significant challenges, and therefore, lead to a high interest in research. In this special issue, different approaches to design novel devices, circuits, and systems for solving the challenges with IoT are targeted. Various novel design automation components including modeling, design flows, simulation methods, and optimizations for designing of modern IoT are targeted, from system level down to device level. The current special issue was envisioned with the above technical considerations. After a rigorous review process, a set of articles were selected for this special issue. These papers are briefly discussed i- the rest of the editorial.

Description: The Internet of Things (IoT) refers to a pervasive presence of interconnected and uniquely identifiable physical devices. These devices’ goal is to gather data and drive actions in order to improve productivity, and ultimately reduce or eliminate reliance on human intervention for data acquisition, interpretation, and use. The proliferation of these connected low-power devices will result in a data explosion that will significantly increase data transmission costs with respect to energy consumption and latency. Edge computing reduces these costs by performing computations at the edge nodes, prior to data transmission, to interpret and/or utilize the data. While much research has focused on the IoT’s connected nature and communication challenges, the challenges of IoT embedded computing with respect to device microprocessors has received much less attention. This paper explores IoT applications’ execution characteristics from a microarchitectural perspective and the microarchitectural characteristics that will enable efficient and effective edge computing. To tractably represent a wide variety of next-generation IoT applications, we present a broad IoT application classification methodology based on application functions, to enable quicker workload characterizations for IoT microprocessors. We then survey and discuss potential microarchitectural optimizations and computing paradigms that will enable the design of right-provisioned microprocessors that are efficient, configurable, extensible, and scalable. This paper provides a foundation for the analysis and design of a diverse set of microprocessor architectures for next-generation IoT devices.

Description: In mixed-criticality (MC) systems, multiple activities with various certification requirements (thus with different criticality levels) can co-exist on shared hardware platforms, where multicore processors have emerged as the de facto computing engines. In this paper, by using the partitioned earliest-deadline-first with virtual deadlines (EDF-VDs) scheduler for a set of periodic MC tasks running on multicore systems, we derive a criticality-aware utilization bound for efficient feasibility tests and then identify its characteristics . Our analysis shows that the bound increases with increasing number of cores and decreasing system criticality level. We show that, since the utilizations of MC tasks at different criticality levels can vary considerably, the utilization contribution of a task on different cores may have large variations and thus can significantly affect the system schedulability under the EDF-VD scheduler. Based on these observations, we propose a novel and efficient criticality-aware task partitioning algorithm (CA-TPA) to compensate for the inherent pessimism of the utilization bound. In order to improve the system schedulability, the task priorities are determined according to their utilization contributions to the system in CA-TPA. Moreover, by analyzing the utilization variations of tasks at different levels, we develop several heuristics to minimize the utilization increment and balance the workload on cores. The simulation results show that the CA-TPA scheme is very effective in achieving higher schedulability ratio and yielding balanced workloads. The actual implementation in Linux operating system further demonstrates the applicability of CA-TPA with lower run-time overhead, compared to the existing partitioning schemes.

Description: Convolutional neural network (CNN) has become a successful algorithm in the region of artificial intelligence and a strong candidate for many computer vision algorithms. But the computation complexity of CNN is much higher than traditional algorithms. With the help of GPU acceleration, CNN-based applications are widely deployed in servers. However, for embedded platforms, CNN-based solutions are still too complex to be applied. Various dedicated hardware designs on field-programmable gate arrays (FPGAs) have been carried out to accelerate CNNs, while few of them explore the whole design flow for both fast deployment and high power efficiency. In this paper, we investigate state-of-the-art CNN models and CNN-based applications. Requirements on memory, computation and the flexibility of the system are summarized for mapping CNN on embedded FPGAs. Based on these requirements, we propose Angel-Eye, a programmable and flexible CNN accelerator architecture, together with data quantization strategy and compilation tool. Data quantization strategy helps reduce the bit-width down to 8-bit with negligible accuracy loss. The compilation tool maps a certain CNN model efficiently onto hardware. Evaluated on Zynq XC7Z045 platform, Angel-Eye is $6 {times }$ faster and $5{times }$ better in power efficiency than peer FPGA implementation on the same platform. Applications of VGG network, pedestrian detection and face alignment are used to evaluate our design on Zynq XC7Z020. NIVIDA TK1 and TX1 platforms are used for comparison. Angel-Eye achieves similar performance and delivers up to $16 {times }$ better energy efficiency.

Description: Multisocket computer systems are popular in workstations and servers. However, they suffer from the relatively low bandwidth of intersocket communication especially for massive parallel workloads that generate many intersocket requests for synchronizations and remote memory accesses. Intersocket traffic puts pressure on the underlying network connecting all processors with a limited bandwidth confined by pin resources. Given this constraint, we propose to dynamically increase the intersocket bandwidth by sacrificing off-chip memory bandwidth when systems have heavy intersocket communication but few off-chip memory accesses. Our design increases the physical bandwidth for intersocket communication via switching the function of pins from off-chip memory accesses to intersocket communication and can achieve an average performance speedup of 1.28 in geocentric mean for selected parallel multithreaded benchmarks.

Description: Asynchronous circuits are becoming increasingly important in system design for Internet of Things, where they orchestrate the interface between big synchronous computation components and the analog environment, which is inherently asynchronous and has high uncertainty with respect to power supply, temperature, and long-term aging effects. However, wide adoption of asynchronous circuits by industrial users is hindered by a steep learning curve for asynchronous control models, such as signal transition graphs (STGs), that are developed by the academic community for specification, verification, and synthesis of asynchronous circuits. In this paper, we introduce a novel high-level description language for asynchronous circuits, which is based on behavioral concepts —high-level descriptions of asynchronous circuit requirements, that can be shared, reused, and extended by users, and can be automatically translated to STGs for further processing by conventional asynchronous and synchronous electronic design automation tools, such as Petrify and Mpsat. Our aim is to simplify the process of capturing system requirements in the form of a formal specification, and to promote behavioral concepts as a means for design reuse. The proposed design flow is fully automated in open-source toolsuite Workcraft, and is applied to the development of an asynchronous power regulator.

Description: With the emergence of Internet of Things (IoT), there is an urgent need to design energy-efficient and secure IoT devices. For example, IoT devices such as radio frequency identification tags and wireless sensor nodes employ AES cryptographic module that are susceptible to differential power analysis (DPA) attacks. With the scaling of technology, leakage power in the cryptographic device increases, which increases their vulnerability to DPA attack. This paper presents a novel FinFET-based secure adiabatic logic (FinSAL), that is energy-efficient and DPA-immune. The proposed adiabatic FinSAL is used to design logic gates such as buffers, XOR, and NAND. Further, the logic gates based on adiabatic FinSAL are used to implement a positive polarity Reed Muller architecture-based S-box circuit. SPICE simulations at 12.5 MHz show that adiabatic FinSAL (20-nm FinFET technology) S-box circuit saves up to 81% of energy per cycle as compared to the conventional S-box circuit implemented using FinFET (20-nm FinFET technology). Further, the security of adiabatic FinSAL S-box circuit has been evaluated by performing the DPA attack through SPICE simulations. We proved that the FinSAL S-box circuit is resistant to a DPA attack through a developed DPA attack flow applicable to SPICE simulations. Further, the impact of FinSAL on hardware security at different technology nodes of FinFETs (7, 10, 14, and 16 nm) are evaluated. From the simulation results, FinSAL gates at 14-nm FinFET offer superior security with optimum power consumption, therefore is the best candidate to design low-power secure IoT devices.

Description: Security is one of the top considerations in hardware designs for Internet-of-Things (IoT), where embedded cryptosystems are extensively used. Traditionally, random dynamic voltage scaling technology has been shown to be very effective in improving the resistance of cryptosystems against side-channel attacks. However, in this paper we demonstrate that the resistance can be undermined by providing lower off-chip power supply voltage. In order to address this issue, we then further propose to monitor the off-chip power supply voltage, and trigger an alarm to protect valued information once the power supply voltage is lower than the expected voltage (threshold voltage). However, considering both maintenance cost of IoT devices and the environment noise on power supply voltage, we first formulated this problem as a nonzero sum game model, and the attacker and the circuit supplier (defender) are the players of this game. The analysis of the Nash equilibria in this game show interesting guideline to the defender about the choice of threshold voltage, which is based on parameters of cryptosystem including the value of information, denial-of-service cost in IoT, etc.

Description: Along with the advent and popularity of cloud computing, Internet of Things, and bring your own device, the trust requirement for terminal devices has increased significantly. An untrusted terminal, a terminal that runs in an untrustworthy execution environment, may cause serious security issues for enterprise networks. With the release of Software Guard Extension, Intel has provided a promising way to construct trusted terminals and services. Utilizing this technology, we propose a security-enhanced attestation for remote terminals, which can achieve shielded execution for measurements and attestation programs. Furthermore, we present a policy-based measurement mechanism where sensitive data, including secret keys and policy details are concealed using the enclave-specific keys. We implement our attestation prototype on real platform with Intel Skylake processor. Evaluation results show that our attestation system can provide much stronger security guarantees, yet incurs small performance overhead.

Description: Advances in semiconductor technology enable integrating tens of cores on a single chip. Providing quality-of-service (QoS) for communication flows in complex embedded applications is critical. In this paper, we present a new approach for designing guaranteed service (GS) networks-on-chip by introducing a new arbitration algorithm and differentiating high and low priority traffic flows in best-effort (BE) networks. An analytical model is provided to compute accurate performance bound parameters in the network with the new arbitration. When the flows have the same priorities in a switch, the new algorithm acts exactly the same as the basic round robin arbitration. It works as a superset of the basic algorithm, when the flows have different priorities. The proposed method helps designers to easily equip traditional BE networks with effective hard QoS, changing it to a GS network. This is done without the need to get involved in the designing complexity of traditional GS networks and still benefit from the superior properties of BE networks. We show substantial improvement in performance bounds for high priority flows (more than 40% in delay and 80% in bandwidth, on average) compared to the known approaches.

Description: As very large scale integration technology scales to deep submicrometer and beyond, interconnect delay greatly limits the circuit performance. The traditional 2-D global routing and subsequent net by net assignment of available empty tracks on various layers lacks a global view for timing optimization. To overcome the limitation, this paper presents a timing driven incremental layer assignment tool, to reassign layers among routing segments of critical nets and noncritical nets. Lagrangian relaxation techniques are proposed to iteratively provide consistent layer/via assignments. Modeling via min-cost flow for layer shuffling avoids using integer programming and yet guarantees integer solutions via uni-modular property of the inherent model. In addition, multiprocessing of ${K times K}$ partitions of the whole chip provides runtime speed up. Furthermore, a slew targeted optimization is presented to reduce the number of violations incrementally through iteration-based Lagrangian relaxation, followed by a post greedy algorithm to fix local violations. Certain parameters introduced in the models provide tradeoff between timing optimization and via count. Experimental results in both ISPD 2008 and industry benchmark suites demonstrate the effectiveness of the proposed incremental algorithms.

Description: Detailed routing is an important stage in very large scale integrated physical design. Due to the extreme scaling of transistor feature size and the complicated design rules, ensuring routing completion without design rule checking (DRC) violations becomes more and more difficult. Studies have shown that the low routing quality partly results from nonoptimal net-ordering nature of traditional sequential methods. The concurrent routing strategy is always based on an NP-hard model, thus is at a disadvantage in runtime. In this paper, we present a novel concurrent detailed routing algorithm that routes all nets simultaneously. Based on the multicommodity flow model, detailed routing problem with complex design rule constraints is formulated as an integer linear programming. Some model simplification heuristics and efficient model solving algorithms are proposed to improve the runtime. Experimental results show that, the proposed algorithms can reduce the DRC violations by 80%, meanwhile can reduce wirelength and via count by 5% and 8% compared with an industry tool. In addition, the proposed algorithm is general that it can be adopted as an incremental detailed router to refine a routing solution, so the number of DRC violations that industry tool cannot fix are further reduced by 27%.

Description: At its core, a technical publication represents a community or a community of communities that share an interest in solving commonly understood technical problems, often with an understanding of the nature of methods that must be invented. As communities go, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) represents a very diverse community spread across a large number of technical areas spanning very large scale integration (VLSI), CAD, circuits, embedded systems, formal methods, etc., and internationally spanning nearly all regions of the IEEE.

Description: In this paper, a fully synthesizable all-digital transmitter (ADTX) is first proposed. This transmitter (TX) uses Cartesian architecture and supports wide-band quadratic-amplitude modulation with wide carrier frequency range. Furthermore, the design methodology for ADTX and corresponding bandpass filter is discussed. This TX is synthesized with digital register transfer level-graphic database system flow, and can be easily implemented in any standard CMOS technology. An exemplary TX is synthesized by TSMC 28-nm standard cell library with extremely small area (0.0009 mm 2 ) and supports carrier frequency as high as 6 GHz with excellent error vector magnitude (<−30 dB). To the best of the authors’ knowledge, this is the first work on a fully synthesizable design of RF transistors, allowing easy technology migration and portability.

Description: Solid state drives (SSDs) have been widely deployed in personal computers, data centers, and cloud storages. In order to improve performance, SSDs are usually constructed with a number of channels with each channel connecting to a number of nand flash chips, each flash chip consisting of multiple dies and each die containing multiple planes. Based on this parallel architecture, I/O requests are potentially able to access parallel units simultaneously. Despite the rich parallelism offered by the parallel architecture, recent studies show that the utilization of flash parallel units is seriously low. This paper shows that the low parallel unit utilization is highly caused by the access conflict among I/O requests. In this paper, we propose parallel issue queueing (PIQ), a novel I/O scheduler at the host systems. PIQ groups I/O requests without conflicts into the same batch and I/O requests with conflicts into different batches. Hence, the multiple I/O requests in one batch can be fulfilled simultaneously by exploiting the rich parallelism of SSDs. Extensive experimental results show that PIQ delivers significant performance improvement especially for the applications which have heavy access conflicts.

Description: One of the main challenges in quantum computing is to ensure error-free operation of the basic quantum gates. There are various implementation technologies of quantum gates for which the distance between interacting qubits must be kept within a limit for reliable operation. This leads to the so-called requirement of neighborhood arrangements of the interacting qubits, often referred to as nearest neighbor (NN) constraint. This is typically achieved by inserting SWAP gates in the quantum circuits, where a SWAP gate between two qubits exchanges their states. Minimizing the number of SWAP gates to provide NN compliance is an important problem to solve. A number of approaches have been proposed in this regard, based on local and global ordering techniques. In this paper, a generalized approach for combined local and global ordering of qubits have been proposed that is based on an improved heuristic for cost estimation and is also scalable. The approach can be extended to ${N}$ -dimensional arrangement of qubits, for any arbitrary values of ${N}$ . Practical constraints, however, restrict the maximum value of ${N}$ to 3. Extensive experiments on benchmark functions have been carried out to evaluate the performance in terms of SWAP gate requirements. 3-D organization of qubits shows average reductions of 6.7% and 37.4%, respectively, in the number of SWAP gates over 2-D and 1-D organizations. Also compared to the best 2-D and 1-D results reported in the literature, on the average 8.7% and 8.4% reductions, respectively, are observed.

Description: Labs-on-Chips (LoCs) implement laboratory procedures on a single chip and are successfully used for chemical and biomedical applications. A promising and emerging realization of such chips are Networked LoCs (NLoCs) in which small volumes of fluids, so-called droplets, flow in closed channels of submillimeter diameters. NLoCs allow for an incubation and storage of assays over a long period of time and, hence, avoid evaporation and unwanted reactions. To increase the flexibility, effectiveness, and reusability, network functionalities allow to passively route droplets in channels and, hence, to dynamically select operations depending on the executed experiment. However, only manually designed architectures are considered for NLoCs thus far. They frequently suffer from large execution times and/or a high contamination of channels. To overcome these drawbacks, we propose the consideration of application-specific architectures for NLoCs. To this end, an automatic design method is proposed which, for a given set of experiments as well as constraints and objectives from the designer, is able to generate an optimized NLoC architecture realizing these experiments. Evaluations and case studies demonstrate the potential of the proposed solution for design exploration. Moreover, we are able to show that application-specific architectures are capable of realizing experiments in just a fraction of the time needed by architectures used thus far as well as with a substantially reduced contamination.

Description: Analyzing the timing properties of asynchronous systems is essential for characterizing their performance and power. Previous work on timing showed that such systems under and-causality and fixed delay exhibit periodicity properties. We give a different graph-based rigorous proof of the exact timing behavior of more general classes of such systems, and conclude their exact periodicity property, where each of the signal transition will occur with the same period after finite occurrences. We established our results under weaker assumption about system connectivity/topology, and this paper provides the theoretical foundation, for the exact periodicity property to be applied and exploited in circuits containing a combination of synchronous and asynchronous components. We provide simulation-based results for several typical asynchronous circuit topologies to quantify this time period in practical circuits. We also provide an extension of our analysis and methods to the case of bounded delay systems. A key result that is a consequence of our analysis is that asynchronous circuits can be integrated with synchronous logic via a metastability-free interface, thereby eliminating the high-overhead synchronizers when an asynchronous circuit is fully surrounded by synchronous logic.

Description: Convolutional neural networks (CNNs) have revolutionized the world of computer vision over the last few years, pushing image classification beyond human accuracy. The computational effort of today’s CNNs requires power-hungry parallel processors or GP-GPUs. Recent developments in CNN accelerators for system-on-chip integration have reduced energy consumption significantly. Unfortunately, even these highly optimized devices are above the power envelope imposed by mobile and deeply embedded applications and face hard limitations caused by CNN weight I/O and storage. This prevents the adoption of CNNs in future ultralow power Internet of Things end-nodes for near-sensor analytics. Recent algorithmic and theoretical advancements enable competitive classification accuracy even when limiting CNNs to binary (+1/−1) weights during training. These new findings bring major optimization opportunities in the arithmetic core by removing the need for expensive multiplications, as well as reducing I/O bandwidth and storage. In this paper, we present an accelerator optimized for binary-weight CNNs that achieves 1.5 TOp/s at 1.2 V on a core area of only 1.33 million gate equivalent (MGE) or 1.9 mm 2 and with a power dissipation of 895 $mu$ W in UMC 65-nm technology at 0.6 V. Our accelerator significantly outperforms the state-of-the-art in terms of energy and area efficiency achieving 61.2 TOp/s/W@0.6 V and 1.1 TOp/s/MGE@1.2 V, respectively.

Description: Today, life is becoming increasingly connected. From TVs to smartphones, including vehicles, buildings, and household appliances, everything is interconnected in what we call the “Internet of Things” (IoT). IoT is now part of our life and we have to deal with it. More than ten billion devices are already connected and five times more are expected to be deployed in the next five years. While deployment and integration of IoT is expanding, one of the main challenge is to provide practical solutions to security, privacy, and trust issues in IoT. Protection and security mechanisms need to include features such as interoperability and scalability but also traceability, authentication, and access control while remaining lightweight. Among the most promising approaches to such security mechanisms, physical unclonable functions (PUFs) provide a unique identifier for similar but different integrated circuits using some of their physical characteristics. These types of functions can thus be used to authenticate integrated circuits, provide traceability and access control. This paper presents a comprehensive case study of the transient effect ring oscillator (RO) PUF from its implementation on FPGAs to its complete characterization. The implementation of the PUF is detailed for two different families of FPGAs: 1) Xilinx Spartan 6 and 2) Altera Cyclone V. All the metrics used for the characterization are explained in detail and the results of the characterization include robustness to environmental parameters including variations in temperature and voltage. Finally, we compare our results with those obtained for another PUF: the RO PUF. All the design files are available online to ensure repeatability and enable comparison of our contribution with other studies.

Description: Clock network should be optimized to reduce clock power dissipation. The power efficient clock network can be constructed by multibit flip-flop generation and gated clock tree aware flip-flop clumping to pull flip-flops close to the same integrated clock gating cell. It is capable of providing an attractive solution to reduce clock power. This paper considers multicorner and multimode timing constraints for the two combined approach. This proposed method is applied to five industrial digital intellectual property blocks of state-of-the-art mobile system-on-a-chip fabricated in 14-nm CMOS process. Experimental results show that MBFF generation algorithm achieves 22% clock power reduction. Applying a gated clock tree aware flip-flop clumping on top of the MBFF generation further reduces the power to around 32%.

Description: Sophisticated subthreshold passive radio frequency identification tag’s baseband processor (BBP) core design for ultralow-power Internet of Things end devices is presented in this paper. Custom logic cells and tailored logic architectures are applied to eliminate timing violations when the operating voltage is much lower than nominal level. For the consideration of limited availability of radio frequency power, power-aware scheme is applied to the key modules, including PIE decoding and command receiving. Furthermore, Galois linear feedback shift register and double-edge-triggered techniques help to improve clock efficiency and reduce the impact of frequency variation in data link portions. Importantly, a novel custom ratioed logic style is adopted in key modules to fundamentally speed up signals’ propagation at ultralow-voltage. The proposed BBP was fabricated in 90-nm CMOS as well as the regular design with the same function. It was also implemented in the tag chip’s fabrication. In measurement the proposed design indicates good robustness and is much more competent for subthreshold operation. It can operate below 0.3 V with power consumption below 130 nW.

Description: Over the last years, many smart buildings applications, such as indoor localization or safety systems, have been subject of intense research. Smart environments usually rely on several hardware nodes equipped with sensors, actuators, and communication functionalities. The high level of heterogeneity and the lack of standardization across technologies make design of such environments a very challenging task, as each installation has to be designed manually and performed ad-hoc for the specific building. On the other hand, many different systems show common characteristics, like the strict dependency with the building floor plan, also sharing similar requirements such as a nodes allocation that provides sensing coverage and nodes connectivity. This paper provides a computer-aided design application for the design of smart building systems based on the installation of hardware nodes across the indoor space. The tool provides a site-specific algorithm for cost-effective deployment of wireless localization systems, with the aim to maximize the localization accuracy. Experimental results from real-world environment show that the proposed site-specific model can improve the positioning accuracy of general models from the state-of-the-art. The tool, available open-source, is modular and extensible through plug-ins allowing to model building systems with different requirements.