Publications

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This report summarizes accomplishments of a three-year project focused on developing technical capabilities for measuring and modeling neuronal processes at the nanoscale. It was successfully demonstrated that nanoprobes could be engineered that were biocompatible, and could be biofunctionalized, that responded within the range of voltages typically associated with a neuronal action potential. Furthermore, the Xyce parallel circuit simulator was employed and models incorporated for simulating the ion channel and cable properties of neuronal membranes. The ultimate objective of the project had been to employ nanoprobes in vivo, with the nematode C elegans, and derive a simulation based on the resulting data. Techniques were developed allowing the nanoprobes to be injected into the nematode and the neuronal response recorded. To the authors's knowledge, this is the first occasion in which nanoparticles have been successfully employed as probes for recording neuronal response in an in vivo animal experimental protocol.

This report describes efforts to automate the biasing of coupled electron-photon Monte Carlo particle transport calculations. The approach was based on weight-windows biasing. Weight-window settings were determined using adjoint-flux Monte Carlo calculations. A variety of algorithms were investigated for adaptivity of the Monte Carlo tallies. Tree data structures were used to investigate spatial partitioning. Functional-expansion tallies were used to investigate higher-order spatial representations.

This report details the accomplishments of the 'Building More Powerful Less Expensive Supercomputers Using Processing-In-Memory (PIM)' LDRD ('PIM LDRD', number 105809) for FY07-FY09. Latency dominates all levels of supercomputer design. Within a node, increasing memory latency, relative to processor cycle time, limits CPU performance. Between nodes, the same increase in relative latency impacts scalability. Processing-In-Memory (PIM) is an architecture that directly addresses this problem using enhanced chip fabrication technology and machine organization. PIMs combine high-speed logic and dense, low-latency, high-bandwidth DRAM, and lightweight threads that tolerate latency by performing useful work during memory transactions. This work examines the potential of PIM-based architectures to support mission critical Sandia applications and an emerging class of more data intensive informatics applications. This work has resulted in a stronger architecture/implementation collaboration between 1400 and 1700. Additionally, key technology components have impacted vendor roadmaps, and we are in the process of pursuing these new collaborations. This work has the potential to impact future supercomputer design and construction, reducing power and increasing performance. This final report is organized as follow: this summary chapter discusses the impact of the project (Section 1), provides an enumeration of publications and other public discussion of the work (Section 1), and concludes with a discussion of future work and impact from the project (Section 1). The appendix contains reprints of the refereed publications resulting from this work.

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The Richtmyer-Meshkov instability after reshock is investigated in shock tube experiments at the Wisconsin Shock Tube Laboratory using planar laser imaging and a new high speed interface tracking technique. The interface is a 50-50% volume fraction mixture of helium and argon stratified over pure argon. This interface has an Atwood number of 0.29 and near single mode, two-dimensional, standing wave perturbation with an average amplitude of 0.35 cm and a wavelength of 19.4 cm. The incident shock wave of Mach number 1.92 accelerates the interface before it is reshocked by a reflected Mach 1.70 shock wave. The amplitude growth after reshock is reported for variations in this initial amplitude, and several amplitude growth rate models are compared to the experimental growth rate after reshock. A new growth model is introduced, based on a model of circulation deposition calculated from one-dimensional gas dynamics parameters. This model is shown to compare well with the amplitude growth rate after reshock and the circulation over a half-wavelength of the interface after the first shock wave and after reshock.

Ultrafast electronic switches fabricated from defective material have been used for several decades in order to produce picosecond electrical transients and TeraHertz radiation. Due to the ultrashort recombination time in the photoconductor materials used, these switches are inefficient and are ultimately limited by the amount of optical power that can be applied to the switch before self-destruction. The goal of this work is to create ultrafast (sub-picosecond response) photoconductive switches on GaAs that are enhanced through plasmonic coupling structures. Here, the plasmonic coupler primarily plays the role of being a radiation condenser which will cause carriers to be generated adjacent to metallic electrodes where they can more efficiently be collected.

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HOPSPACK (Hybrid Optimization Parallel Search PACKage) solves derivative-free optimization problems using an open source, C++ software framework. The framework enables parallel operation using MPI or multithreading, and allows multiple solvers to run simultaneously and interact to find solution points. HOPSPACK comes with an asynchronous pattern search solver that handles general optimization problems with linear and nonlinear constraints, and continuous and integer-valued variables. This user manual explains how to install and use HOPSPACK to solve problems, and how to create custom solvers within the framework.

Functional brain imaging is of great interest for understanding correlations between specific cognitive processes and underlying neural activity. This understanding can provide the foundation for developing enhanced human-machine interfaces, decision aides, and enhanced cognition at the physiological level. The functional near infrared spectroscopy (fNIRS) based event-related optical signal (EROS) technique can provide direct, high-fidelity measures of temporal and spatial characteristics of neural networks underlying cognitive behavior. However, current EROS systems are hampered by poor signal-to-noise-ratio (SNR) and depth of measure, limiting areas of the brain and associated cognitive processes that can be investigated. We propose to investigate a flexible, tunable, multi-spectral fNIRS EROS system which will provide up to 10x greater SNR as well as improved spatial and temporal resolution through significant improvements in electronics, optoelectronics and optics, as well as contribute to the physiological foundation of higher-order cognitive processes and provide the technical foundation for miniaturized portable neuroimaging systems.

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Large relational datasets such as national-scale social networks and power grids present different computational challenges than do physical simulations. Sandia's distributed-memory supercomputers are well suited for solving problems concerning the latter, but not the former. The reason is that problems such as pattern recognition and knowledge discovery on large networks are dominated by memory latency and not by computation. Furthermore, most memory requests in these applications are very small, and when the datasets are large, most requests miss the cache. The result is extremely low utilization. We are unlikely to be able to grow out of this problem with conventional architectures. As the power density of microprocessors has approached that of a nuclear reactor in the past two years, we have seen a leveling of Moores Law. Building larger and larger microprocessor-based supercomputers is not a solution for informatics and network infrastructure problems since the additional processors are utilized to only a tiny fraction of their capacity. An alternative solution is to use the paradigm of massive multithreading with a large shared memory. There is only one instance of this paradigm today: the Cray MTA-2. The proposal team has unique experience with and access to this machine. The XMT, which is now being delivered, is a Red Storm machine with up to 8192 multithreaded 'Threadstorm' processors and 128 TB of shared memory. For many years, the XMT will be the only way to address very large graph problems efficiently, and future generations of supercomputers will include multithreaded processors. Roughly 10 MTA processor can process a simple short paths problem in the time taken by the Gordon Bell Prize-nominated distributed memory code on 32,000 processors of Blue Gene/Light. We have developed algorithms and open-source software for the XMT, and have modified that software to run some of these algorithms on other multithreaded platforms such as the Sun Niagara and Opteron multi-core chips.

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Palacios and Kitten are new open source tools that enable applications, whether ported or not, to achieve scalable high performance on large machines. They provide a thin layer over the hardware to support both full-featured virtualized environments and native code bases. Kitten is an OS under development at Sandia that implements a lightweight kernel architecture to provide predictable behavior and increased flexibility on large machines, while also providing Linux binary compatibility. Palacios is a VMM that is under development at Northwestern University and the University of New Mexico. Palacios, which can be embedded into Kitten and other OSes, supports existing, unmodified applications and operating systems by using virtualization that leverages hardware technologies. We describe the design and implementation of both Kitten and Palacios. Our benchmarks show that they provide near native, scalable performance. Palacios and Kitten provide an incremental path to using supercomputer resources that is not performance-compromised.

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Large scale geostorage options for fuels including natural gas and petroleum offer substantial buffer capacity to meet or hedge against supply disruptions. This same notion may be applied to large scale hydrogen storage to meet industrial or transportation sector needs. This study develops an assessment tool to calculate the potential ‘gate-to-gate’ life cycle costs for large scale hydrogen geostorage options in salt caverns, and continues to develop modules for depleted oil/gas reservoirs and aquifers. The U.S. Department of Energy has an interest in these types of storage to assess the geological, geomechanical and economic viability for this type of hydrogen storage. Understanding, and looking to quantify, the value of large-scale storage in a larger hydrogen supply and demand infrastructure may prove extremely beneficial for larger infrastructure modeling efforts when looking to identify the most efficient means to fuel a hydrogen demand (e.g., industrial or transportation-centric demand). Drawing from the knowledge gained in the underground large scale storage options for natural gas and petroleum in the U.S., the potential to store relatively large volumes of CO₂ in geological formations, the hydrogen storage assessment modeling will continue to build on these strengths while maintaining modeling transparency such that other modeling efforts may draw from this project.

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Direct measurements of cosmic-ray neutron intensity were recorded with a neutron scatter camera developed at SNL. The instrument used in this work is a prototype originally designed for nuclear non-proliferation work, but in this project it was used to characterize the response of ambient neutrons in the 0.5-10 MeV range to water located on or above the land surface. Ambient neutron intensity near the land surface responds strongly to the presence of water, suggesting the possibility of an indirect method for monitoring soil water content, snow water equivalent depth, or canopy intercepted water. For environmental measurements the major advantage of measuring neutrons with the scatter camera is the limited (60{sup o}) field of view that can be obtained, which allows observations to be conducted at a previously unattainable spatial scales. This work is intended to provide new measurements of directional fluxes which can be used in the design of new instruments for passively and noninvasively observing land-surface water. Through measurements and neutron transport modeling we have demonstrated that such a technique is feasible.

We have designed and built electrostatically actuated microvalves compatible with integration into a PDMS based microfluidic system. The key innovation for electrostatic actuation was the incorporation of carbon nanotubes into the PDMS valve membrane, allowing for electrostatic charging of the PDMS layer and subsequent discharging, while still allowing for significant distention of the valveseat for low voltage control of the system. Nanoparticles were applied to semi-cured PDMS using a stamp transfer method, and then cured fully to make the valve seats. DC actuation in air of these valves yielded operational voltages as low as 15V, by using a supporting structure above the valve seat that allowed sufficient restoring forces to be applied while not enhancing actuation forces to raise the valve actuation potential. Both actuate to open and actuate to close valves have been demonstrated, and integrated into a microfluidic platform, and demonstrated fluidic control using electrostatic valves.