ALBERT

Description: The importance of memory performance and capacity is a growing concern for high performance computing laboratories around the world. It has long been recognized that improvements in processor speed exceed the rate of improvement in dynamic random access memory speed and, as a result, memory access times can be the limiting factor in high performance scientific codes. The use of multi-core processors exacerbates this problem with the rapid growth in the number of cores not being matched by similar improvements in memory capacity, increasing the likelihood of memory contention. In this paper, we present WMTools , a lightweight memory tracing tool and analysis framework for parallel codes, which is able to identify peak memory usage and also analyse per-function memory use over time. An evaluation of WMTools , in terms of its effectiveness and also its overheads, is performed using nine established scientific applications/benchmark codes representing a variety of programming languages and scientific domains. We also show how WMTools can be used to automatically generate a parameterized memory model for one of these applications, a two-dimensional non-linear magnetohydrodynamics application, Lare2D . Through the memory model we are able to identify an unexpected growth term which becomes dominant at scale. With a refined model we are able to predict memory consumption with under 7% error.

Description: This work describes a novel approach for the reduction of energy consumption in data centres (DCs) that will yield benefits both in terms of running costs and its environmental impact. The method is based on the introduction of collaborative interactions and flexibility clauses in contracts between all the DC ecosystem entities. The included entities are all the actors along the energy production–consumption chain, from the energy provider to the Information Technology customer. The collaborative approach also integrates the interaction between federated DCs. In this paper, we find a detailed description of the architecture that enables interaction between the DC ecosystem parties, which is designed to be progressively deployed, allowing traditional and ‘greened’ services to coexist, and without modification of the existing DC automation and framework systems.

Description: For open-ended computational growth, we argue that: (i) instead of hardwiring and hiding component spatial relationships, computer architecture should soften and expose them; and (2) instead of relegating reliability to hardware, robustness must climb the computational stack toward the end users. We suggest that eventually all truly large-scale computers will be robust spatial computers —even if intended neither for spatial tasks nor harsh environments. This paper is an extended introduction for the spatial computing community to the Movable Feast Machine (MFM), a computing model in the spirit of an object-oriented asynchronous cellular automata. We motivate the approach and then present the model, touching on robustness mechanisms such as redundancy, compartmentalization and homeostasis. We provide simulation data from prototype movable elements such as self-healing wire for data transport and movable ‘membrane’ rings for spatial segregation, and illustrate how some larger computations like sorting or evaluating a lambda expression can be reconceived for robustness and movability within a spatial computing architecture.

Description: Harnessing the power of Web communities, the effort on creating metadata can be greatly reduced. Collaborative communities can create, update and maintain content models for multimedia resources more effectively than single users working alone. This paper presents MC 2 , a framework for MPEG-7 content-modelling communities. MC 2 is based on the challenges to collaborative multimedia content modelling reported in the research literature and the results of an experiment undertaken to investigate user behaviour in collaborative content modelling. An MC 2 service has also been implemented as a proof of concept for this framework, which is evaluated with a population of users and against the challenges.

Description: We present our work on the dimensioning of a packet-switching wavelength division multiplexing ring in order to reduce its infrastructure (capital expenditure) cost. We study a new all-optical architecture: the packed optical add-drop multiplexer (POADM). We aim to minimize the overall cost of the network by reducing the number of indispensable devices in the nodes and the number of required wavelengths. We formalize the packing problems underlying the ring dimensioning. The elements to be packed are made up of transmissions that share the same destination. We assume that elements can be cut before being packed into boxes. We furnish a complete theoretical analysis of the complexity and approximability of these problems. We define also several measures of quality for a cut and provide an optimal cutting strategy, according to these measures. Our subsequent contribution is a heuristic solution that solves the bi-criteria packing problem (the number of boxes and the number of cuts are minimized simultaneously). The exhaustive numerical results of this heuristic algorithm come next. We rely on our optimal cutting strategy to appraise the efficiency of other strategies. We also adapt the only existing POADM dimensioning algorithm, more restrictive than ours, and we confront it with our solution. The analysis of results allows us to provide network design guidelines to perform the dimensioning in the most efficient way.

Description: A sensor network, unlike a traditional communication network, is deeply embedded in physical environments and its operation is mainly driven by the event activities in the environment. In long-term operations, the event activities usually show certain patterns that can be learned and exploited to optimize the network design. However, this has been underexplored in the literature. One work related to this is using Activity Transition Probability Graph (ATPG) for radio duty cycling [Tang et al. (2011) ActSee: Activity-Aware Radio Duty-Cycling for Sensor Networks in Smart Environments. Proc. IEEE INSS 2011 , Penghu, Taiwan, June 12–15. IEEE Press]. In this paper, we present a novel Energy and Activity-aware Routing (EAR) protocol for sensor networks. As a case study, we have evaluated EAR with the data trace of real Smart Environments. In EAR an ATPG is learned and built from the event activity patterns. EAR is an online routing protocol, that chooses the next-hop relay node by utilizing: activity pattern information in the ATPG graph and a novel index of energy balance in the network. EAR extends the network lifetime by maintaining an energy balance across the nodes in the network, while meeting the application performance with desired throughput and low data delivery latency. We theoretically prove that: (i) the network throughput with EAR achieves a competitive ratio (i.e. the ratio of the performance of any offline algorithm that has knowledge of all past and future packet arrivals to the performance of our online algorithm) that is asymptotically optimal, and (ii) EAR achieves a lower bound in the network lifetime. Extensive experimental results from: (i) a 82 node Motelab sensor network testbed [Werner-Allen et al. (2005) MoteLab: A Wireless Sensor Network Testbed. Proc. ACM IPSN 2005 , Los Angeles, CA, USA, April 25–27, pp. 483–488. IEEE Press, NJ, USA] and (ii) a varying size network (20–100) in sensor network simulator TOSSIM, validate that EAR outperforms the existing methods both in terms of network performance (network lifetime, network energy consumption) and application performance (low latency, desired throughput) for an energy-constrained sensor network.

Description: Multiplicative Newton–Raphson and Goldschmidt algorithms are widely used in current processors to implement division, reciprocal, square root and square root reciprocal operations. Based on an initial approximation of a given accuracy, several iterations are performed until the required result accuracy is achieved. The number of iterations depends on the initial approximation and on the required accuracy. Each iteration consists of several multiplications. In this paper, we present an accurate error analysis that takes into account all the contributions to the final error and allows us to obtain error bounds for each iteration. These error bounds can be used to obtain optimal unit designs by reducing the size of the multiplier and, therefore, to reduce the area requirements. To show the usefulness of the error analysis, we compare the optimal multiplier size obtained from our error analysis with the multipliers in the floating-point division and square root units of some popular processors and we conclude that the multiplier size and its area can be reduced by, roughly, 10%.

Description: Virtual machine (VM) migration has recently emerged as a potential tool to improve the performance, cost and fault tolerance of data centers. However, migrating VMs requires more hardware resources to reserve target slots during the migration. A large number of simultaneous migrations can exhaust the physical resources of a data center. Consequently, the system may deny new service requests. In this paper, we introduce an efficient strategy to limit the number of target slots used for the migration process with the aim of maintaining high data center availability. In particular, the number of target slots is determined by the tradeoff between the waiting time of the queued migration processes and the probability that the system rejects new user requests due to the lack of available resources. We also propose a method to reduce the waiting time of the migration process by adding a sufficient number of slots during the migration process. Accordingly, a data center can use fewer resources while still guaranteeing the quality of the service. The efficiency of our proposed method is demonstrated by the experimental results.