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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development of the Suited Injury Modes and Effects Analysis for Identification of Top Injury Risks in Lunar Missions and Training

A new Exploration Extravehicular Activity Suit (xEVAS) is being designed to replace the current Extravehicular Mobility Unit (EMU) for the National Aeronautics and Space Administration’s (NASA’s) Artemis program to return astronauts to the lunar surface. This new suit will allow for increased range of motion compared the current EMU and Apollo era suits and will have additional features that will enhance the health and safety of exploration. With the design of lunar missions and the xEVAS progressing, it is important to consider possible injuries and injury mechanisms that could occur in the suit. To address these concerns, the suited Injury Modes and Effects Analysis (IMEA) was developed to outline suited injury scenarios and rank them based on risk score. The IMEA documents possible scenarios and underlying mechanisms of injury while wearing an extravehicular activity (EVA) suit. Tasks during lunar surface EVA as well as training events to prepare for lunar missions were considered as history has shown that more suit injuries occur during training than in flight. Each scenario is ranked with a consequence and likelihood scoring based on our current understanding of the suit and Artemis design reference missions to identify high-risk cases that will drive further work in suited injury. Injuries, mechanisms of injury, and mitigation strategies are evaluated within each scenario. The Suited Injury Summit was held on January 5, 2022, to vet the IMEA with external experts. This was an all-day virtual meeting with the suited injury team, ergonomists, suit engineers, safety engineers, the flight operations directorate, flight doctors, astronauts, astronaut strength, conditioning, and rehabilitation specialists (ASCRS), and external subject matter experts (SMEs). External SMEs consisted of surgeons with varying specialties. The intent of this meeting was to walk through the top injury risks identified in the analysis, identify any gaps that were not captured, and discuss mitigations. With participation from all groups, countless lessons-learned came from the Summit meeting. Using the lessons-learned and discussion from the Summit, the top 10 risks have been identified: neutral buoyancy laboratory training, hand/glove injuries, poor suit fit, field training, specific EVA tasks/design of task, boots/ankle injuries, falls from heights, background radiation, repetitive contact, and ambulation/long-distance ambulation. Mitigation steps have also been determined for each of the top risks. The IMEA and documentation of top risks is a living document. Yearly meetings are planned to update the analysis and reevaluate top risks and mitigations. The IMEA is being used to drive work in suited injury, and this work will continue to evolve with IMEA and lunar mission updates.

Tessa Reiber↗
DOE OSTI2014

Advanced Research Projects Agency-Energy Annual Report for FY2013

This report presents a summary of the activities of the Advanced Research Projects Agency-Energy (ARPA-E) during Fiscal Year 2013 (FY2013). In FY2013, ARPA-E issued funding solicitations and selected projects for three new programs covering a broad array of energy technologies, including: $36 million to develop transformational energy storage technologies for electric vehicles; $32 million to develop cost-effective, energy-efficient manufacturing techniques for processing and recycling lightweight metals; and $34 million to develop transformational biological technologies to convert natural gas to liquids for transportation fuels. ARPA-E announced two additional funding opportunities in FY2013 with project selections that were ultimately announced in FY2014. These programs include $27 million to develop next-generation power switching devices that improve energy efficiency in a wide range of applications – including new lighting technologies, computer power supplies, industrial motor drives, and automobiles – and $30 million to advance solar energy beyond current photovoltaic (PV) and concentrated solar power (CSP) technologies. Altogether, technologies funded through these five programs have the potential to transform the way we generate, use, and store energy. In September 2013, ARPA-E also began utilizing Innovative Development in Energy-Related Applied Science (OPEN IDEAS), a rolling open solicitation that will allow ARPA-E to quickly support innovative applied energy research that has the potential to lead to new focused programs. In addition to these new programs, ARPA-E hosted the fourth annual Energy Innovation Summit from February 25-27, 2013. The Summit brought together leaders from academia, government, and business to discuss the foremost energy issues, showcase the latest technology innovations, and cultivate relationships to help advance cutting-edge technologies to market. The event drew over 2,200 attendees from 49 states and 26 countries and featured over 150 speakers and keynote addresses. At the Summit, ARPA-E recognized several preliminary indicators of likely project success, including that 17 projects had attracted over $450 million in private sector follow-on funding after ARPA-E's initial investment of approximately $70 million. Finally, ARPA-E continued to focus on providing awardees with practical training and critical business information as part of the Agency's Technology-to-Market program. This support equips projects with a clear understanding of market needs to guide technical development and help projects succeed.

Martin, C.↗
DOE OSTI2016

Sandia MEMS Visualization Tools v. 3.0

This is a revision to the Sandia MEMS Visualization Tools. It replaces all previous versions. New features in this version: Support for AutoCAD 2014 and 2015 . This CD contains an integrated set of electronic files that: a) Provides a 2D Process Visualizer that generates cross-section images of devices constructed using the SUMMiT V fabrication process. b) Provides a 3D Visualizer that generates 3D images of devices constructed using the SUMMiT V fabrication process. c) Provides a MEMS 3D Model generator that creates 3D solid models of devices constructed using the SUMMiT V fabrication process. While there exists some files on the CD that are used in conjunction with software package AutoCAD , these files are not intended for use independent of the CD. Note that the customer must purchase his/her own copy of AutoCAD to use with these files.

Yarberry, Victor↗
DOE OSTI2020

International Symposium on Transport Security of Nuclear and other Radioactive Material; Tokyo, Japan, November 2019

As an outcome of the Fourth Nuclear Security Summit of 2016, held in Washington D.C., the Governments of Australia, Canada, Czech Republic, Finland, France, Hungary, Italy, Japan, Kazakhstan, Morocco, Spain, the Republic of Korea, Thailand, the United Kingdom, and the United States reaffirmed, through INFCIRC/909, their will to further improve the overall security in the transport of nuclear and other radioactive materials. With this goal in mind, each expressed their commitment to further exchange national practices with other countries through the IAEA and the Global Initiative to Combat Nuclear Terrorism (GICNT). They also committed to actively support the IAEA as the central organization for coordinating activities and developing guidance documents and to support the GICNT and the Global Partnership Against the Spread of Weapons and Materials of Mass Destruction in developing and implementing its nuclear transport security activities. Both of these organizations address the commitments regarding nuclear transport security as outcomes of the Nuclear Security Summit 2016. In an effort to continue the momentum from the Nuclear Security Summit, the Government of Japan, in cooperation with the Integrated Support Center for Nuclear Nonproliferation and Nuclear Security of Japan Atomic Energy Agency (ISCN/JAEA), hosted the International Transport Security Symposium in November 2019. With over fifty countries invited to attend, the event exchanged and promoted good practices in several topical area sessions related to the security of nuclear and other radioactive material in transport. Topical sessions included Laws and Regulatory Framework, Physical Protection Systems, Response Actions, and Insider/Information Security. The Symposium built support for transport security and encouraged IAEA Member States to actively work regionally and internationally with the IAEA’s transport security programme through the practical implementation and incorporation of IAEA Nuclear Security Series recommendations and guidance into their national frameworks for transport security. From these sessions, to the host detailed a recommended path forward for future engagements in the security of nuclear and radioactive material in transport. The paper will discuss the Symposium’s outcomes and highlight the forward momentum made by both signatories and non-signatories for the strengthening of all the critical elements of a State’s transport security regime, including physical protection systems, insider threats to the nuclear and radioactive material supply chains, planning and capabilities for law enforcement response to malicious transport security events, and employment of technology to address critical vulnerabilities to the transport of nuclear and other radioactive materials.

Holt, Katherine↗
DOE OSTI2022

From PeleC to PeleACC, to PeleC++

PeleC is an Exascale Computing Project application for simulating compressible combustion in complex geometries. It has been built on top of the popular AMReX library. In the beginning of the Exascale Computing Project, PeleC was focused on KNL. It uses a mixture of C++, C, and kernels written in Fortran to obtain performance by focusing on vectorization. Recently we have taken two approaches in deciding PeleC's future for obtaining performance on exascale GPU machines. In the first programming model, we decorated the Fortran kernels with OpenACC directives. This expedited our ability to run at large scales on Summit's GPUs, where we achieved a significant speedup over the CPUs on Summit. The second programming model involved rewriting the Fortran kernels in C++ and using AMReX's Kokkos-like lambda abstractions for running on the GPU. This resulted in similar speedups on Summit's GPUs over merely utilizing the CPUs. Both approaches involved AMReX's management of memory transfers between the device and host. In this work, we compare and contrast the benefits and pitfalls to both programming approaches regarding performance, performance portability, and productivity. We also discuss advantages we have found in taking the time to modernize our code and why have chosen a specific pathway to prepare our code for the future DOE exascale machines.

exascale computing↗
DOE OSTI2023

Studying performance portability of LAMMPS across diverse GPU-based platforms

The molecular dynamics simulation software, LAMMPS, utilizes the Kokkos acceleration library to port computation to a diverse set of architectures including those based on GPU accelerators. In addition to Kokkos, LAMMPS contains a vast code base that leverages the CUDA application programming interface using library functions such as cuFFT, CUDA's fast-fourier transform (FFT) library, and, more recently, also support for AMD's Heterogeneous Interface for Portability (HIP) that is rapidly growing. While preparing LAMMPS tests for the AMD GPU-based test system precursors to Frontier, we investigated several strategies for accelerating LAMMPS on AMD GPUs, using the AMD Instinct MI100 and MI250X. In this work, we integrated the HIP FFT library, hipFFT, into the particle-particle particle-mesh (PPPM) long-range solver, which allowed the porting of PPPM calculations to the GPUs. Kokkos behavior on the MI100 and MI250X was also investigated through the package kokkos command of LAMMPS, targeting communication, memory usage, and particle grid decomposition. The Tersoff, Reax, Lennard-Jones (LJ), EAM, Granular, and PPPM potentials were investigated in this effort, and results from these experiments are provided. In conclusion, the selected potentials were run on Spock (AMD Instinct MI100), Crusher (AMD Instinct MI250X), AFW HPC11 (NVIDIA A100) and Summit (NVIDIA V100), for comparison. Operational roofline models were constructed and analyzed for the Tersoff, Reax, and Lennard–Jones potentials on Crusher and Summit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Three practical workflow schedulers for easy maximum parallelism

Runtime scheduling and workflow systems are an increasingly popular algorithmic component in HPC because they allow full system utilization with relaxed synchronization requirements. There are so many special-purpose tools for task scheduling, one might wonder why more are needed. Use cases seen on the Summit supercomputer needed better integration with MPI and greater flexibility in job launch configurations. Preparation, execution, and analysis of computational chemistry simulations at the scale of tens of thousands of processors revealed three distinct workflow patterns. A separate job scheduler was implemented for each one using extremely simple and robust designs: file-based, task-list based, and bulk-synchronous. Comparing to existing methods shows unique benefits of this work, including simplicity of design, suitability for HPC centers, short startup time, and well-understood per-task overhead. All three new tools have been shown to scale to full utilization of Summit, and have been made publicly available with tests and documentation. This work presents a complete characterization of the minimum effective task granularity for efficient scheduler usage scenarios. Here, these schedulers have the same bottlenecks, and hence similar task granularities as those reported for existing tools following comparable paradigms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Bringing Safety to Chemistry for Life

Recently, the chemistry enterprise as a whole has experienced a monumental shift in the way that it understands and approaches safety, both within society and as part of the science of chemistry. The American Chemical Society (ACS) has embraced this change and has committed to modelling it by incorporating “safety” into its core values. In early 2018, a Safety Summit involving stakeholders from across the chemistry enterprise was convened to consider strategies for “accelerating the adoption of an ethos of safety across the chemical enterprise”. The summit concluded in a better understanding of the factors influencing the implementation of safe chemical practices, programs in progress to effect change in this area, and gaps where additional effort is needed. Opportunities were identified where the ACS could make a meaningful impact on chemical safety and which aligned with the goals of the Society. Here, we will describe how the ACS strategic plan addresses the chemical safety challenges in relation to both historical influences and the current environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Analysis of OpenMP 4.5 Offloading in Implementations: Correctness and Overhead

The OpenMP language features have been evolving to meet the rapid development in hardware platforms. This journal focuses on evaluating implementations of OpenMP 4.5 target offload features in compilers such as Clang, XL and GCC that are an integral part of the software harness on supercomputers and clusters. We use Summit (Top supercomputer in the world as of November 2018) as one of our experimental setup. Such an effort is particularly critical on such supercomputers as that is being widely used by application developers to run their scientific codes at scale. Our tests not only evaluate the OpenMP implementations but also expose ambiguities within the OpenMP 4.5 specification. We also assess the overhead of the different OpenMP runtimes in relationship to the different directives and clauses. This helps in assessing the interaction of different OpenMP directives independent of other application artifacts. We are aware that the implementations are constantly evolving and Summit is advertised as having only partial OpenMP 4.x support. This is a synergistic effort to help identify and fix bugs in features’ implementations that are required by applications and prevent deployment delays later on. Going forward, we also plan to interact with standard benchmarking organizations like SPEC/HPG to donate our tests and mini-apps/kernels for potential inclusion in the next release versions of SPEC benchmark suite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High performance sparse multifrontal solvers on modern GPUs

Here, we have ported the numerical factorization and triangular solve phases of the sparse direct solver STRUMPACK to GPU. STRUMPACK implements sparse LU factorization using the multifrontal algorithm, which performs most of its operations in dense linear algebra operations on so-called frontal matrices of various sizes. Our GPU implementation off-loads these dense linear algebra operations, as well as the sparse scatter–gather operations between frontal matrices. For the larger frontal matrices, our GPU implementation relies on vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs and rocBLAS and rocSOLVER for AMD GPUs. For the smaller frontal matrices we developed custom CUDA and HIP kernels to reduce kernel launch overhead. Overall, high performance is achieved by identifying submatrix factorizations corresponding to sub-trees of the multifrontal assembly tree which fit entirely in GPU memory. The multi-GPU setting uses SLATE (Software for Linear Algebra Targeting Exascale) as a modern GPU-aware replacement for ScaLAPACK. On 4 nodes of SUMMIT the code runs ~10X faster when using all 24 V100 GPUs compared to when it only uses the 168 POWER9 cores. On 8 SUMMIT nodes, using 48 V100 GPUs, the sparse solver reaches over 50TFlop/s. Compared to SuperLU, on a single V100, for a set of 17 matrices our implementation is faster for all but one matrix, and is on average 5X (median 4X) faster

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Celeritas: Accelerating Geant4 with GPUs

Celeritas [1] is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Lumi- nosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6 and 32 faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.

Johnson, Seth R.↗
DOE OSTI2024

Plant, insect, and fungi fossils under the center of Greenland’s ice sheet are evidence of ice-free times

The persistence and size of the Greenland Ice Sheet (GrIS) through the Pleistocene is uncertain. This is important because reconstructing changes in the GrIS determines its contribution to sea level rise during prior warm climate periods and informs future projections. To understand better the history of Greenland’s ice, we analyzed glacial till collected in 1993 from below 3 km of ice at Summit, Greenland. The till contains plant fragments, wood, insect parts, fungi, and cosmogenic nuclides showing that the bed of the GrIS at Summit is a long-lived, stable land surface preserving a record of deposition, exposure, and interglacial ecosystems. Knowing that central Greenland was tundra-covered during the Pleistocene informs the understanding of Arctic biosphere response to deglaciation.

58 GEOSCIENCES↗
DOE OSTI2024

Exploring the Landscape of Distributed Graph Clustering on Leadership Supercomputers

The rapid growth of large-scale datasets in fields like biology and social networks has driven the need for advanced graph analytics techniques. Community detection, a fundamental task in graph analytics, identifies closely connected groups of nodes within a network, providing valuable insights across various disciplines. This study focuses on two classic community detection methods, the Louvain algorithm and Markov Clustering (MCL), and evaluates the performance of two prominent distributed community detection algorithms: HiPDPL-GPU, our prior implementation, and HipMCL. We conduct experiments on GPU-accelerated heterogeneous HPC systems, Summit and Frontier, to assess their performance under varying conditions. Our objective is to identify the strengths and weaknesses of these algorithms in terms of scalability, and quality of solutions. We evaluate these algorithms on a diverse set of 70+ networks spanning 13 domains, with sizes ranging up to 4.2 billion edges. Our results demonstrate that HiPDPL-GPU consistently outperforms HipMCL, especially for large-scale networks. HiPDPL-GPU achieves significantly faster runtimes (47x to 1439x), higher modularity scores, and improved scalability. These findings highlight HiPDPL-GPU as a promising solution for efficient and effective large-scale graph analytics in diverse application domains, and provide insights into the feasibility of using MCL-based approaches for certain application domains.

Community detection, graph algorithms↗
DOE OSTI2025

Scaling Ultrahigh-Resolution E3SM Land Model for Leadership-Class Supercomputers

This paper presents advancements in scaling the ultrahigh-resolution E3SM Land Model (uELM) for deployment on leadership-class supercomputers, addressing the increased demand for km-scale Earth system modeling. By focusing on km-scale ELM simulations, we enhance predictive capabilities for climate interactions, facilitating improved responses to climate change impacts on energy systems, agriculture, and water resources. Our approach leverages innovative software architecture optimizations, sophisticated data handling techniques, and advanced parallel processing, achieving strong scalability on two leadership supercomputers (2400 nodes (105,600 cores) on Summit, and 1200 nodes (76,800 cores) on Frontier). Results from extensive scalability assessments on the Summit and Frontier also demonstrate outstanding I/O performance (close to 400 GB/s write throughput) and the model's ability to efficiently handle increasing computational demands. This study not only establishes uELM's capability for high-resolution simulations over vast geographical domains, but also sets a foundation for future Earth system modeling breakthroughs.

Wang, Dali [ORNL] (ORCID:0000000168065108)↗
DOE OSTI2019

A Co-Design Study Of Fusion Whole Device Modeling Using Code Coupling

Complex workflows consisting of multiple simulation and analysis codes running concurrently through in-memory coupling is becoming popular due to inherent advantages in online management of large-scale data, resilience, and the code development process. However, orchestrating such a multi-application workflow to efficiently utilize resources on a heterogeneous architecture is challenging. In this paper, we present our results with running the Fusion Whole Device Modeling benchmark workflow on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory. We explore various resource distribution and process placement mechanisms, including sharing compute nodes between processes from separate applications. We show that fine-grained process placement can have a significant impact towards efficient utilization of the compute power of a node on Summit, and conclude that sophisticated tools for performing co-design studies of multi-application workflows can play an important role towards efficient orchestration of such workflows.

Choi, Jong Youl↗
DOE OSTI2022

Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications

The present work investigates the modeling of preexascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple “kernel” approximation for data production at each time step. Results show that MACSio can simulate actual AMReX nonlinear “static” I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems.

Godoy, William↗
DOE OSTI2018

167-PFlops Deep Learning for Electron Microscopy: From Learning Physics to Atomic Manipulation

An artificial intelligence system called MENNDL, which used 25,200 Nvidia Volta GPUs on Oak Ridge National Laboratory’s Summit machine, automatically designed an optimal deep learning network in order to extract structural information from raw atomic-resolution microscopy data. In a few hours, MENNDL creates and evaluates millions of networks using a scalable, parallel, asynchronous genetic algorithm augmented with a support vector machine to automatically find a superior deep learning network topology and hyper-parameter set than a human expert can find in months. For the application of electron microscopy, the system furthers the goal of improving our understanding of the electron-beam-matter interactions and real-time image-based feedback, which enables a huge step beyond human capacity toward nanofabricating materials automatically. Finally, MENNDL has been scaled to the 4,200 available nodes of Summit achieving a measured 152.5 PFlops, with an estimated sustained performance of 167 PFlops when the entire machine is available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Design, Deployment, and Evaluation of the CORAL Pre-Exascale Systems

CORAL, the Collaboration of Oak Ridge, Argonne and Livermore, is fielding two similar IBM systems, Summit and Sierra, with NVIDIA GPUs that will replace the existing Titan and Sequoia systems. Summit and Sierra are currently ranked No. 1 and No. 3, respectively on the Top500 list. We discuss the design and key differences of the systems. Our evaluation of the systems highlights the following. Applications that fit in HBM see the most benefit and may prefer more GPUs; however, for some applications, the CPU-GPU bandwidth is more important than the number of GPUs. The node-local burst buffer scales linearly, and can achieve a 4X improvement over the parallel file system for large jobs; smaller jobs, however, may benefit from writing directly to the PFS. Finally, several CPU, network and memory bound analytics and GPU-bound deep learning codes achieve up to a 11X and 79X speedup/node, respectively over Titan.

Vazhkudai, Sudharshan↗