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  • 1
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    Quantum Machine Learning (2018)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Quantum computing promises an unprecedented ability to solve intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. The Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center is the space agency's primary facility for conducting research and development in quantum information sciences. QuAIL conducts fundamental research in quantum physics but also explores how best to exploit and apply this disruptive technology to enable NASA missions in aeronautics, Earth and space sciences, and space exploration. At the same time, machine learning has become a major focus in computer science and captured the imagination of the public as a panacea to myriad big data problems. In this talk, we will discuss how classical machine learning can take advantage of quantum computing to significantly improve its effectiveness. Although we illustrate this concept on a quantum annealer, other quantum platforms could be used as well. If explored fully and implemented efficiently, quantum machine learning could greatly accelerate a wide range of tasks leading to new technologies and discoveries that will significantly change the way we solve real-world problems.
    Keywords: Mathematical and Computer Sciences (General)
    Type: ARC-E-DAA-TN51254 , Society for Industrial and Applied Mathematics (SIAM) Conference on Parallel Processing for Scientific Computing; Mar 07, 2018 - Mar 10, 2018; Tokyo; Japan
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  • 2
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    Quantum Computing at NASA: Current Status (2017)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Mathematical and Computer Sciences (General)
    Type: ARC-E-DAA-TN45174 , International Conference on Space Mission Challenges for Information Technology (SMC-IT) 2017; Sep 27, 2017 - Sep 29, 2017; Madrid; Spain
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  • 3
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    Unstructured Adaptive (UA) NAS Parallel Benchmark (2004)
    In:  CASI
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    Publication Date: 2019-07-10
    Description: We present a complete specification of a new benchmark for measuring the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. It complements the existing NAS Parallel Benchmark suite. The benchmark involves the solution of a stylized heat transfer problem in a cubic domain, discretized on an adaptively refined, unstructured mesh.
    Keywords: Mathematical and Computer Sciences (General)
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  • 4
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    Performance Enhancement Strategies for Multi-Block Overset Grid CFD Applications (2003)
    In:  CASI
    Details
    Publication Date: 2019-07-10
    Description: The overset grid methodology has significantly reduced time-to-solution of highfidelity computational fluid dynamics (CFD) simulations about complex aerospace configurations. The solution process resolves the geometrical complexity of the problem domain by using separately generated but overlapping structured discretization grids that periodically exchange information through interpolation. However, high performance computations of such large-scale realistic applications must be handled efficiently on state-of-the-art parallel supercomputers. This paper analyzes the effects of various performance enhancement strategies on the parallel efficiency of an overset grid Navier-Stokes CFD application running on an SGI Origin2000 machinc. Specifically, the role of asynchronous communication, grid splitting, and grid grouping strategies are presented and discussed. Details of a sophisticated graph partitioning technique for grid grouping are also provided. Results indicate that performance depends critically on the level of latency hiding and the quality of load balancing across the processors.
    Keywords: Mathematical and Computer Sciences (General)
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  • 5
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    Role of High-End Computing in Meeting NASA's Science and Engineering Challenges (2006)
    In:  CASI
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    Publication Date: 2019-08-13
    Description: Two years ago, NASA was on the verge of dramatically increasing its HEC capability and capacity. With the 10,240-processor supercomputer, Columbia, now in production for 18 months, HEC has an even greater impact within the Agency and extending to partner institutions. Advanced science and engineering simulations in space exploration, shuttle operations, Earth sciences, and fundamental aeronautics research are occurring on Columbia, demonstrating its ability to accelerate NASA s exploration vision. This talk describes how the integrated production environment fostered at the NASA Advanced Supercomputing (NAS) facility at Ames Research Center is accelerating scientific discovery, achieving parametric analyses of multiple scenarios, and enhancing safety for NASA missions. We focus on Columbia s impact on two key engineering and science disciplines: Aerospace, and Climate. We also discuss future mission challenges and plans for NASA s next-generation HEC environment.
    Keywords: Mathematical and Computer Sciences (General)
    Type: The Fourth International Conference on Computational Fluid Dynamics; Jul 10, 2006 - Jul 14, 2006; Ghent, Belguim; Belgium
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  • 6
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    Job Superscheduler Architecture and Performance in Computational Grid Environments (2003)
    In:  CASI
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    Publication Date: 2019-07-13
    Description: Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.
    Keywords: Mathematical and Computer Sciences (General)
    Type: SC2003; Nov 15, 2003 - Nov 21, 2003; Phoenix, AZ; United States
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  • 7
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    Dynamic Load Balancing for Adaptive Meshes using Symmetric Broadcast Networks (1998)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Many scientific applications involve grids that lack a uniform underlying structure. These applications are often dynamic in the sense that the grid structure significantly changes between successive phases of execution. In parallel computing environments, mesh adaptation of grids through selective refinement/coarsening has proven to be an effective approach. However, achieving load balance while minimizing inter-processor communication and redistribution costs is a difficult problem. Traditional dynamic load balancers are mostly inadequate because they lack a global view across processors. In this paper, we compare a novel load balancer that utilizes symmetric broadcast networks (SBN) to a successful global load balancing environment (PLUM) created to handle adaptive unstructured applications. Our experimental results on the IBM SP2 demonstrate that performance of the proposed SBN load balancer is comparable to results achieved under PLUM.
    Keywords: Communications and Radar
    Type: 12th ACM International Conference on Supercomputing; Jul 13, 1998 - Jul 17, 1998; Melbourne; Australia
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  • 8
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    Job Scheduling in a Heterogeneous Grid Environment (2004)
    In:  CASI
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    Publication Date: 2019-07-13
    Description: Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.
    Keywords: Mathematical and Computer Sciences (General)
    Type: 2004 HPDC Conference; Jan 01, 2004; Unknown
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  • 9
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    HPC Matters: How Advanced Computing Enables NASA Missions (2019)
    In:  CASI
    Details
    Publication Date: 2019-10-17
    Description: No abstract available
    Keywords: Mathematical and Computer Sciences (General)
    Type: ARC-E-DAA-TN73350 , HPC User Forum; Oct 07, 2019 - Oct 08, 2019; Lugano; Switzerland|HPC User Forum; Oct 10, 2019 - Oct 11, 2019; Edinburgh, Scotland; United Kingdom
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