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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Evaluation of CHO Benchmarks on the Arria 10 FPGA using Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. Benchmarking of OpenCL-based framework is an effective way for analyzing the performance of system by studying the execution of the benchmark applications. CHO is a suite of benchmark applications that provides support for OpenCL [1]. The authors presented CHO as an OpenCL port of the CHStone benchmark. Using Altera OpenCL (AOCL) compiler to synthesize the benchmark applications, they listed the resource usage and performance of each kernel that can be successfully synthesized by the compiler. In this report, we evaluate the resource usage and performance of the CHO benchmark applications using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board that features an Arria 10 FPGA device. The focus of the report is to have a better understanding of the resource usage and performance of the kernel implementations using Arria-10 FPGA devices compared to Stratix-5 FPGA devices. In addition, we also gain knowledge about the limitations of the current compiler when it fails to synthesize a benchmark application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Modular autopilot design and development featuring bayesian non-parametric adaptive control

According to an embodiment, there is provided an onboard integrated computational system for an unmanned aircraft system (“Stabilis” autopilot). This is an integrated suite of hardware, software, and data-to-decisions services that are designed to meet the needs of business and research developers of UAS. Stabilis is designed to accelerate the development of any UAS platform and avionics system; it does so with hardware modularity and software adaptation. The Stabilis offers multiple technological advantages technological advantages including: Plug-and-adapt functionality; Data-to-decisions capability; and, On board parallelization capability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems

The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A Survey Of Architectural Approaches for Managing Embedded DRAM and Non-volatile On-chip Caches

Recent trends of CMOS scaling and increasing number of on-chip cores have led to a large increase in the size of on-chip caches. Since SRAM has low density and consumes large amount of leakage power, its use in designing on-chip caches has become more challenging. To address this issue, researchers are exploring the use of several emerging memory technologies, such as embedded DRAM, spin transfer torque RAM, resistive RAM, phase change RAM and domain wall memory. In this paper, we survey the architectural approaches proposed for designing memory systems and, specifically, caches with these emerging memory technologies. To highlight their similarities and differences, we present a classification of these technologies and architectural approaches based on their key characteristics. We also briefly summarize the challenges in using these technologies for architecting caches. We believe that this survey will help the readers gain insights into the emerging memory device technologies, and their potential use in designing future computing systems.

classification↗
DOE OSTI2017

The Approximability of Partial Vertex Covers in Trees.

Motivated by applications in risk management of computational systems, we focus our attention on a special case of the partial vertex cover problem, where the underlying graph is assumed to be a tree. Here, we consider four possible versions of this setting, depending on whether vertices and edges are weighted or not. Two of these versions, where edges are assumed to be unweighted, are known to be polynomial-time solvable (Gandhi, Khuller, and Srinivasan, 2004). However, the computational complexity of this problem with weighted edges, and possibly with weighted vertices, has not been determined yet. The main contribution of this paper is to resolve these questions, by fully characterizing which variants of partial vertex cover remain intractable in trees, and which can be efficiently solved. In particular, we propose a pseudo-polynomial DP-based algorithm for the most general case of having weights on both edges and vertices, which is proven to be NPhard. This algorithm provides a polynomial-time solution method when weights are limited to edges, and combined with additional scaling ideas, leads to an FPTAS for the general case. A secondary contribution of this work is to propose a novel way of using centroid decompositions in trees, which could be useful in other settings as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Extreme-scale workflows: A perspective from the JLESC international community

The Joint Laboratory for Extreme-Scale Computing (JLESC) focuses on software challenges in high-performance computing systems to meet the needs of today’s science campaigns, which often require large resources, consist of multiple tasks, and generate vast amounts of data. In this context, extreme-scale workflows have been the key factor in enabling scientific discoveries by helping scientists automate the dependencies and data exchanges between workflow tasks, instead of managing those manually. Here, in this paper, we present representative extreme-scale workflows and feature workflow systems developed by JLESC participating institutions. We present lessons learned while developing these tools, alongside with the open challenges and future research directions in the field of extreme-scale workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

SciDAC3 SUPER Performance Institute, University of Oregon Contributions (Final Report)

The SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER) focused on developing technology and leveraging expertise towards ensuring that computational scientists could successfully exploit existing and emerging DOE high performance computing systems. To achieve this goal, SUPER was organized into research thrusts focusing on performance engineering, auto-tuning, performance tools, energy efficiency, resilience and multi-objective optimization, with a target of facilitating effective utilization of near term HPC systems. As described in this summary document, our teams’ significant insights into both application- and architecture-awareness drove numerous innovations across our stated research areas, while significantly improving the performance, portability, and functionality of numerous SciDAC partnership applications, enabling scientific simulation at unprecedented scale. Additionally, the tools, methodologies, and collaborations developed under this project will continue paying dividends as we face the challenges of forthcoming multi-petascale and exascale computing technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

OpenMP Target Task: Tasking and Target Offloading on Heterogeneous Systems

This work evaluated the use of OpenMP tasking with target GPU offloading as a potential solution for programming productivity and performance on heterogeneous systems. Also, it is proposed a new OpenMP specification to make the implementation of heterogeneous codes simpler by using OpenMP target task, which integrates both OpenMP tasking and target GPU offloading in a single OpenMP pragma. As a test case, the authors used one of the most popular and widely used Basic Linear Algebra Subprogram Level-3 routines: triangular solver (TRSM). To benefit from the heterogeneity of the current high-performance computing systems, the authors propose a different parallelization of the algorithm by using a nonuniform decomposition of the problem. This work used target GPU offloading inside OpenMP tasks to address the heterogeneity found in the hardware. This new approach can outperform the state-of-the-art algorithms, which use a uniform decomposition of the data, on both the CPU-only and hybrid CPU-GPU systems, reaching speedups of up to one order of magnitude. The performance that this approach achieves is faster than the IBM ESSL math library on CPU and competitive relative to a highly optimized heterogeneous CUDA version. One node of Oak Ridge National Laboratory’s supercomputer, Summit, was used for performance analysis.

Valero Lara, Pedro↗
DOE OSTI2023

Distributed out-of-memory NMF on CPU/GPU architectures

We propose an efficient distributed out-of-memory implementation of the non-negative matrix factorization (NMF) algorithm for heterogeneous high-performance-computing systems. The proposed implementation is based on prior work on NMFk, which can perform automatic model selection and extract latent variables and patterns from data. In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems. The resulting algorithm is optimized for out-of-memory problems where the memory required to factorize a given matrix is greater than the available GPU memory. Memory complexity is reduced by batching/tiling strategies, and sparse and dense matrix operations are significantly accelerated with GPU cores (or tensor cores when available). Input/output latency associated with batch copies between host and device is hidden using CUDA streams to overlap data transfers and compute asynchronously, and latency associated with collective communications (both intra-node and inter-node) is reduced using optimized NVIDIA Collective Communication Library (NCCL) based communicators. Benchmark results show significant improvement, from 32X to 76x speedup, with the new implementation using GPUs over the CPU-based NMFk. Good weak scaling was demonstrated on up to 4096 multi-GPU cluster nodes with approximately 25,000 GPUs when decomposing a dense 340 Terabyte-size matrix and an 11 Exabyte-size sparse matrix of density 10 -6 .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Event triggering in the IceCube data acquisition system

In order to detect cosmic ray air showers and neutrinos, the software data acquisition (DAQ) system of the IceCube Neutrino Observatory forms triggers on patterns of Cherenkov light deposition in the detector based on temporal and/or spatial coincidences. Here we describe the algorithms used for triggering, as well as the fast merging algorithm used to combine the time-ordered hit streams from the optical modules. We also present recently implemented and planned modifications of the DAQ that take advantage of our newly upgraded multi-core computer systems at the South Pole.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Large-Scale Calculations for Material Sciences Using Accelerators to Improve Time- and Energy-to-Solution

A major impediment to deploying next-generation high-performance computational systems is the required electrical power, often measured in units of megawatts. The solution to this problem is driving the introduction of novel machine architectures, such as those employing many-core processors and specialized accelerators. In this article, we describe the use of a hybrid accelerated architecture to achieve both reduced time to solution and the associated reduction in the electrical cost for a state-of-the-art materials science computation.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, Implementation Strategy for a Distribution Management System

Electric distribution utilities encounter many challenges to successful deployment of Distribution Management Systems (DMSs). The key challenges are documented in this report, along with suggestions for overcoming them. This report offers a recommended list of activities for implementing a DMS. It takes a strategic approach to implementing DMS from a project management perspective. The project management strategy covers DMS planning, procurement, design, building, testing, Installation, commissioning, and system integration issues and solutions. It identifies the risks that are associated with implementation and suggests strategies for utilities to use to mitigate them or avoid them altogether. Attention is given to common barriers to successful DMS implementation. This report begins with an overview of the implementation strategy for a DMS and proceeds to put forward a basic approach for procuring hardware and software for a DMS; designing the interfaces with external corporate computing systems such as EMS, GIS, OMS, and AMI; and implementing a complete solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Cybersecurity Assessment Methodology for International Safeguards

International nuclear safeguards are technical measures implemented by the International Atomic Energy Agency (IAEA) to verify the correctness and completeness of declarations made by States about their nuclear activities. The systems used to verify such activities include electronic and digital hardware and software components capable of data collection, processing, analysis, storage and transmission. Despite increasing efforts to protect digital systems against unauthorized access or attack through cybersecurity measures, these systems are not immune to cyber exploitation that could compromise their integrity or reliability. Previous versions of these systems did not include capabilities that exist today, such as BluetoothTM and GPS. The inclusion of these new capabilities, as well as new data processing and storage mechanisms, adds new attack vectors and opportunities for adversaries to exploit the devices that did not previously exist. As mentioned in the above referenced Cybersecurity for Safeguards study, cyber-domain vulnerabilities present risks to the equipment used to perform the international nuclear safeguards mission. The IAEA has produced guidance on the protection of nuclear facilities and their computer systems against cyber threats, but these documents do not specifically address the risks to safeguards or safeguards equipment. In response, the U.S. Department of Energy National Nuclear Security Administration (DOE/NNSA) Office of International Nuclear Safeguards/Safeguards Technology Development (NA-241) sponsored Sandia National Laboratories (Sandia, SNL) and the Idaho National Laboratory (Idaho, INL) to conduct a one-year study to evaluate cyber related vulnerabilities in safeguards equipment and develop recommendations for the mitigation of any identified risks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Trinity Center of Excellence Co-Design Best Practices

Co-design between application developers and the vendors providing high-performance computing systems is essential to efficiently using current-generation HPC systems and shaping next-generation architectures. Application developers are faced with the challenge of effectively orchestrating many hardware threads and exploiting vector instructions, which can require code modifications. Will refactoring applications for current-generation systems apply to future-generation systems? Is there help available for this enormous task? Over the past 10 years, a partnership has evolved to address these issues. Centers of Excellence are mutually beneficial collaborations between application developers and vendors; vendors receive a better understanding of the needs of their users, and users receive a better understanding of the characteristics of the hardware, system software, and tools available to address their challenges. Lastly, this article describes the partnership between two vendors, Cray and Intel, and the application teams working together in the Trinity Center of Excellence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Thermodynamic properties and phase stability of the Ba-Bi system: A combined computational and experimental study

The thermodynamic properties and phase stability of the Ba-Bi system are investigated computationally and experimentally in the present work. The enthalpies of formation and the finite temperature thermodynamic properties of seven compounds are predicted by first-principles calculations based on density functional theory (DFT), indicating five compounds (BaBi 3 , Ba 11 Bi 10 , Ba 4 Bi 3 , Ba 5 Bi 3 , and Ba 2 Bi) to be stable. Phase relations at 773 K and 858 K with composition x Ba = 0.90 are established by isothermal annealing and powder X-ray diffraction (XRD) to clarify the previously observed phase transition at 796 K. The extremely low chemical activity of Ba in liquid for a wide range of temperatures and compositions indicates very strong short-range ordering in the liquid phase which is modeled in the present work by introducing the Ba 4 Bi 3 and BaBi 3 associates in the liquid phase. Both thermodynamic and phase equilibrium data are then used to evaluate the model parameters in Gibbs energy functions of the five stable compounds and three solution phases of liquid, bcc, and rhombohedral phases by the CALPHAD (CALculation of PHAse Diagram) technique. Here the present work shows that the Ba-Bi system consists of three eutectic reactions, two peritectic reactions, one peritectoid reaction, and two congruent reactions, as well as that the concentrations of associates are very high in the liquid phase with very low concentration of atomic Ba, which provides the fundamental understanding as to why Bi can be used to remove Ba ions from molten salt solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

System and method for optimizing hydrocarbon production from subsurface reservoirs

A method is described for subsurface hydrocarbon reservoir characterization including receiving a time-lapse electromagnetic (EM) dataset and a flow dataset; inverting the time-lapse EM dataset using a parametric inversion that models steel well casings to determine a volume of fluid-changed reservoir; inverting the time-lapse EM dataset and the flow dataset using a joint inversion that honors the volume of the fluid-changed reservoir to determine relative permeability and capillary pressure; and characterizing flow characteristics in the volume of the fluid-changed reservoir. The method may be executed by a computer system.

Hoversten, Gary Michael↗