Publications

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Due to advances in CMOS fabrication technology, high performance computing capabilities have continually grown. More capable hardware has allowed a range of complex scientific applications to be developed. However, these applications present a bottleneck to future performance. Entrenched 'legacy' codes - 'Dusty Decks' - demand that new hardware must remain compatible with existing software. Additionally, conventional architectures faces increasing challenges. Many of these challenges revolve around the growing disparity between processor and memory speed - the 'Memory Wall' - and difficulties scaling to large numbers of parallel processors. To a large extent, these limitations are inherent to the traditional computer architecture. As data is consumed more quickly, moving that data to the point of computation becomes more difficult. Barring any upward revision in the speed of light, this will continue to be a fundamental limitation on the speed of computation. This work focuses on these solving these problems in the context of Light Weight Processing (LWP). LWP is an innovative technique which combines Processing-In-Memory, short vector computation, multithreading, and extended memory semantics. It applies these techniques to try and answer the questions 'What will a next-generation supercomputer look like?' and 'How will we program it?' To that end, this work presents four contributions: (1) An implementation of MPI which uses features of LWP to substantially improve message processing throughput; (2) A technique leveraging extended memory semantics to improve message passing by overlapping computation and communication; (3) An OpenMP library modified to allow efficient partitioning of threads between a conventional CPU and LWPs - greatly improving cost/performance; and (4) An algorithm to extract very small 'threadlets' which can overcome the inherent disadvantages of a simple processor pipeline.

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Modern society's physical health depends vitally upon a number of real, interdependent, critical infrastructure networks that deliver power, petroleum, natural gas,water, and communications. Its economic health depends on a number of other infrastructure networks, some virtual and some real, that link residences, industries, commercial sectors, and transportation sectors. The continued prosperity and national security of the US depends on our ability to understand the vulnerabilities of and analyze the performance of both the individual infrastructures and the entire interconnected system of infrastructures. Only then can we respond to potential disruptions in a timely and effective manner. Collaborative efforts among Sandia, other government agencies, private industry, and academia have resulted in realistic models for many of the individual component infrastructures. In this paper, we propose an innovative modeling and analysis framework to study the entire system of physical and economic infrastructures. That framework uses the existing individual models together with system dynamics, functional models, and nonlinear optimization algorithms. We describe this framework and demonstrate its potential use to analyze, and propose a response for, a hypothetical disruption.

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The Sandia lightning simulator at Sandia National Laboratories can provide up to 200 kA for a simulated single lightning stroke, 100 kA for a subsequent stroke, and hundreds of Amperes of continuing current. It has recently been recommissioned after a decade of inactivity and the single-stroke capability demonstrated. The simulator capabilities, basic design components, upgrades, and diagnostic capabilities are discussed in this paper.

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Traditional reactive flow modeling provides a computational representation of shock initiation of energetic materials. Most reactive flow models require ad hoc assumptions to obtain robust simulations, assumptions that result from partitioning energy and volume change between constituents in a reactive mixture. For example, most models assume pressure and/or temperature equilibrium for the mixture. Many mechanical insults to energetic materials violate these approximations. Careful analysis is required to ensure that the model assumptions and limitations are not exceeded. One limitation is that the shock to detonation transition is replicated only for strong planar shocks. Many models require different parameters to match data from thin pulse, ramp wave, or multidimensional loading, an approach that fails for complex loading. To accurately simulate reaction under non-planar shock impact scenarios a new formalism is required. The continuum mixture theory developed by Baer and Nunziato is used to eliminate ad hoc assumptions and limitations of current reactive flow models. This modeling paradigm represents the multiphase nature of reacting condensed/gas mixtures. Comparisons between simulations and data are presented.

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Recent advances in magnetic loading techniques have permitted quasi-isentropes to be measured to unprecedented levels. However, the relevant equations for planar waves provide no information about transverse stresses, leaving the deviatoric (strength) behavior of an isentropically loaded material unknown. Because materials are much cooler under isentropic loading than under shock loading, they can remain solid and thus retain strength to very high pressures. Thus, to improve our ability to model material behavior under isentropic loading, techniques to measure strength are needed. In this paper, existing techniques for determining high-pressure strength will be discussed along with their limitations. A technique for assessing the strength of isentropically loaded materials will be presented and used to determine the strength of an aluminum alloy using data from the Z machine and gas gun experiments. These results will be compared to existing models for material strength. Finally, limitations of the technique and future work needed will be discussed.

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