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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

I/O-aware bandwidth allocation for petascale computing systems

In the Big Data era, the gap between the storage performance and an appli- cation's I/O requirement is increasing. I/O congestion caused by concurrent storage accesses from multiple applications is inevitable and severely harms the performance. Conventional approaches either focus on optimizing an ap- plication's access pattern individually or handle I/O requests on a low-level storage layer without any knowledge from the upper-level applications. In this paper, we present a novel I/O-aware bandwidth allocation framework to coordinate ongoing I/O requests on petascale computing systems. The motivation behind this innovation is that the resource management system has a holistic view of both the system state and jobs' activities and can dy- namically control the jobs' status or allocate resource on the y during their execution. We treat a job's I/O requests as periodical subjobs within its lifecycle and transform the I/O congestion issue into a classical scheduling problem. Based on this model, we propose a bandwidth management mech- anism as an extension to the existing scheduling system. We design several bandwidth allocation policies with different optimization objectives either on user-oriented metrics or system performance. We conduct extensive trace- based simulations using real job traces and I/O traces from a production IBM Blue Gene/Q system at Argonne National Laboratory. Experimental results demonstrate that our new design can improve job performance by more than 30%, as well as increasing system performance.

I/O congestion↗
DOE OSTI2015

Scalable fault tolerance runtime technology for petascale computers (Final Project Report)

With the massive number of components comprising the forthcoming petascale computer systems, hardware failures will be routinely encountered during execution of large-scale applications. Due to the multidisciplinary, multiresolution, and multiscale nature of scientific problems that drive the demand for high end systems, applications place increasingly differing demands on the system resources: disk, network, memory, and CPU. In addition to MPI, future applications are expected to use advanced programming models such as those developed under the DARPA HPCS program as well as existing global address space programming models such as Global Arrays, UPC, and Co-Array Fortran. While there has been a considerable amount of work in fault tolerant MPI with a number of strategies and extensions for fault tolerance proposed, virtually none of advanced models proposed for emerging petascale systems is currently fault aware. To achieve fault tolerance, development of underlying runtime and OS technologies able to scale to petascale level is needed. This project has evaluated range of runtime techniques for fault tolerance for advanced programming models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Final Report: Correctness Tools for Petascale Computing

In the course of developing parallel programs for leadership computing systems, subtle programming errors often arise that are extremely difficult to diagnose without tools. To meet this challenge, University of Maryland, the University of Wisconsin—Madison, and Rice University worked to develop lightweight tools to help code developers pinpoint a variety of program correctness errors that plague parallel scientific codes. The aim of this project was to develop software tools that help diagnose program errors including memory leaks, memory access errors, round-off errors, and data races. Research at Rice University focused on developing algorithms and data structures to support efficient monitoring of multithreaded programs for memory access errors and data races. This is a final report about research and development work at Rice University as part of this project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Petascale Computations for Large-Scale Atomic and Molecular Collisions. In: Sustained Simulations Performance.

Petaflop architectures are currently being utilized efficiently to perform large scale computations in Atomic, Molecular and Optical Collisions. We solve the Schrödinger or Dirac equation for the appropriate collision problem using the R-matrix or R-matrix with pseudo-states approach. We briefly outline the parallel methodology used and implemented for the current suite of Breit-Pauli and DARC codes. Various examples are shown of our theoretical results compared with those obtained from Synchrotron Radiation facilities and from Satellite observations. We also indicate future directions and implementation of the R-matrix codes on emerging GPU architectures.

Accurate Cross Section↗
DOE OSTI2015

Final Report for Foundational Tools for Petascale Computing

This project concentrated on various aspects of creating tool infrastructure to make it easier to program large-scale parallel computers. This project was collaborative with the University of Wisconsin and closely related to the project DE-SC0002606 (“Tools for the Development of High Performance Energy Applications and Systems”) . The research conducted during this project is summarized in this report. The complete details of the work are available in the ten publications listed at the end of the report. Many of the concepts created during this project have been incorporated into tools and made available as freely downloadable software (at www.dyninst.org). It also supported the Ph.D. studies of three students and one research staff member.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Petascale Computing: Impact on Future NASA Missions

This slide presentation reviews NASA's use of a new super computer, called Columbia, capable of operating at 62 Tera Flops. This computer is the 4th fastest computer in the world. This computer will serve all mission directorates. The applications that it would serve are: aerospace analysis and design, propulsion subsystem analysis, climate modeling, hurricane prediction and astrophysics and cosmology.

Brooks, Walter↗
DOE OSTI2015

Big Data: Next-Generation Machines for Big Science

Addressing the scientific grand challenges identified by the US Department of Energy’s (DOE’s) Office of Science’s programs alone demands a total leadership-class computing capability of 150 to 400 Pflops by the end of this decade. The successors to three of the DOE’s most powerful leadership-class machines are set to arrive in 2017 and 2018—the products of the Collaboration Oak Ridge Argonne Livermore (CORAL) initiative, a national laboratory–industry design/build approach to engineering nextgeneration petascale computers for grand challenge science. These mission-critical machines will enable discoveries in key scientific fields such as energy, biotechnology, nanotechnology, materials science, and high-performance computing, and serve as a milestone on the path to deploying exascale computing capabilities.

High-performance computing↗
DOE OSTI2016

Sanibel Symposium in the Petascale-Exascale Computational Era

The 56 th Sanibel Symposium was held February 14-19 2016 at the King and Prince Hotel, St. Simons Island, GA. It successfully brought quantum chemists and chemical and condensed matter physicists together in presentations, posters, and informal discussions bridging those two communities. The Symposium has had a significant role in preparing generations of quantum theorists. As computational potency and algorithmic sophistication have grown, the Symposium has evolved to emphasize more heavily computationally oriented method development in chemistry and materials physics, including nanoscience, complex molecular phenomena, and even bio-molecular methods and problems. Given this context, the 56 th Sanibel meeting systematically and deliberately had sessions focused on exascale computation. A selection of outstanding theoretical problems that need serious attention was included. Five invited sessions, two contributed sessions (hot topics), and a poster session were organized with the exascale theme. This was a historic milestone in the evolution of the Symposia. Just as years ago linear algebra, perturbation theory, density matrices, and band-structure methods dominated early Sanibel Symposia, the exascale sessions of the 56 th meeting contributed a transformative influence to add structure and strength to the computational physical science community in an unprecedented way. A copy of the full program of the 56 th Symposium is attached. The exascale sessions were Linear Scaling, Non-Adabatic Dynamics, Interpretive Theory and Models, Computation, Software, and Algorithms, and Quantum Monte Carlo. The Symposium Proceedings will be published in Molecular Physics (2017). Note that the Sanibel proceedings from 2015 and 2014 were published as Molecular Physics vol. 114, issue 3-4 (2016) and vol. 113, issue 3-4 (2015) respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The Institute for Sustained Performance, Energy, and Resilience Final Project Report

Over the course of the five years of the Scientific Discovery through Advanced Computation (SciDAC-3) program, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) exploited a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry, and materials science. The computing systems underpinning this work increased in performance potential from tens to hundreds of PFlop/s, but in the process evolving significantly from architectures in 2011, when SciDAC-3 began. Although Moore's law continues unabated, the end of Dennard scaling has necessitated a fundamental shift in computer architecture focused on power efficiency. To that end, processors are increasingly varied as they strive to satisfy performance, productivity, reliability, and energy efficiency in the face of divergent computational requirements. The diversity among these machines presents a number of challenges to merely porting today's scientific applications, much less achieving good performance. Therefore, at the beginning of SciDAC-3, USC and its collaborators anticipated that both vastly increased scale (e.g., more chips, more cores per chip, wider SIMD) and heterogeneity would exacerbate performance optimization challenges while simultaneously promoting the issues of energy and heterogeneity will exacerbate performance optimization challenges while simultaneously promoting the issues of energy consumption and resilience to the forefront. To ensure that DOE's computational scientists could successfully exploit emerging high performance computing (HPC) systems, DOE SC’s Advanced Scientific Computing Research Program (ASCR) funded the SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER). Led by USC, this was a broadly based project with expertise in compilers and system tools, performance engineering, energy management, and resilience. SUPER followed the successful model developed in the previous SciDAC-2 Performance Engineering Research Institute (PERI) of leveraging the research investments DOE and others have made and integrating the results to create new capabilities beyond the reach of any one group. To accomplish this, SUPER was organized into multi-institution teams conducting the research activities in performance portability, energy efficiency, exascale resilience, and overall optimization. SUPER researchers also collaborated with other SciDAC-3 institutes, 13 of the 19 Scientific Computation Application Partnerships (SAP), as well as the broader DOE computational sciences community. These collaborations both focused our research on the real challenges facing petascale scientific computing as well as ensured the broad and immediate impact of the results of our research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

eXascale PRogramming Environment and System Software (XPRESS)

Exascale systems, with a thousand times the compute capacity of today’s leading edge petascale computers, are expected to emerge during the next decade. Their software systems will need to facilitate the exploitation of exceptional amounts of concurrency in applications, and ensure that jobs continue to run despite the occurrence of system failures and other kinds of hard and soft errors. Adapting computations at runtime to cope with changes in the execution environment, as well as to improve power and performance characteristics, is likely to become the norm. As a result, considerable innovation is required to develop system support to meet the needs of future computing platforms. The XPRESS project aims to develop and prototype a revolutionary software system for extreme-­scale computing for both exascale and strong­scaled problems. The XPRESS collaborative research project will advance the state-­of-­the-­art in high performance computing and enable exascale computing for current and future DOE mission-­critical applications and supporting systems. The goals of the XPRESS research project are to: A. enable exascale performance capability for DOE applications, both current and future, B. develop and deliver a practical computing system software X-­stack, OpenX, for future practical DOE exascale computing systems, and C. provide programming methods and environments for effective means of expressing application and system software for portable exascale system execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Large-scale large eddy simulation of nuclear reactor flows: Issues and perspectives

Numerical simulation has been an intrinsic part of nuclear engineering research since its inception. In recent years a transition is occurring toward predictive, first-principle-based tools such as computational fluid dynamics. Even with the advent of petascale computing, however, such tools still have significant limitations. In the present work some of these issues, and in particular the presence of massive multiscale separation, are discussed, as well as some of the research conducted to mitigate them. Petascale simulations at high fidelity (large eddy simulation/direct numerical simulation) were conducted with the massively parallel spectral element code Nek5000 on a series of representative problems. These simulations shed light on the requirements of several types of simulation: (1) axial flow around fuel rods, with particular attention to wall effects; (2) natural convection in the primary vessel; and (3) flow in a rod bundle in the presence of spacing devices. Finally, the focus of the work presented here is on the lessons learned and the requirements to perform these simulations at exascale. Additional physical insight gained from these simulations is also emphasized.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Large-Scale Simulation of Nuclear Reactors: Issues and Perspectives

Numerical simulation has been an intrinsic part of nuclear engineering research since its inception. In recent years a transition is occurring toward predictive, first-principle-based tools such as computational fluid dynamics. Even with the advent of petascale computing, however, such tools still have significant limitations. In the present work some of these issues, and in particular the presence of massive multiscale separation, are discussed, as well as some of the research conducted to mitigate them. Petascale simulations at high fidelity (large eddy simulation/direct numerical simulation) were conducted with the massively parallel spectral element code Nek5000 on a series of representative problems. These simulations shed light on the requirements of several types of simulation: (1) axial flow around fuel rods, with particular attention to wall effects; (2) natural convection in the primary vessel; and (3) flow in a rod bundle in the presence of spacing devices. The focus of the work presented here is on the lessons learned and the requirements to perform these simulations at exascale. Additional physical insight gained from these simulations is also emphasized.

CFD↗
DOE OSTI2019

FFT, FMM, and multigrid on the road to exascale: Performance challenges and opportunities

FFT, FMM, and multigrid methods are widely used fast and highly scalable solvers for elliptic PDEs. However, emerging large-scale computing systems are introducing challenges in comparison to current petascale computers. Recent efforts (Dongarra et al. 2011) have identified several constraints in the design of exascale software that include massive concurrency, resilience management, exploiting the high performance of heterogeneous systems, energy efficiency, and utilizing the deeper and more complex memory hierarchy expected at exascale. In this paper, we perform a model-based comparison of the FFT, FMM, and multigrid methods in the context of these projected constraints. Finally, we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

SciDAC GSEP: Gyrokinetic Simulation of Energetic Particle Turbulence and Transport

Energetic particle (EP) confinement is a key physics issue for burning plasma experiment ITER, the crucial next step in the quest for clean and abundant energy, since ignition relies on self-heating by energetic fusion products (α-particles). Due to the strong coupling of EP with burning thermal plasmas, plasma confinement property in the ignition regime is one of the most uncertain factors when extrapolating from existing fusion devices to the ITER tokamak. EP population in current tokamaks are mostly produced by auxiliary heating such as neutral beam injection (NBI) and radio frequency (RF) heating. Remarkable progress in developing comprehensive EP simulation codes and understanding basic EP physics has been made by two concurrent SciDAC EP projects GSEP funded by the Department of Energy (DOE) Office of Fusion Energy Science (OFES), which have successfully established gyrokinetic turbulence simulation as a necessary paradigm shift for studying the EP confinement in burning plasmas. Verification and validation have rapidly advanced through close collaborations between simulation, theory, and experiment. Furthermore, productive collaborations with computational scientists have enabled EP simulation codes to effectively utilize current petascale computers and emerging exascale computers. We review here key physics progress in the GSEP projects regarding verification and validation of gyrokinetic simulations, nonlinear EP physics, EP coupling with thermal plasmas, and reduced EP transport models. Advances in high performance computing through collaborations with computational scientists that enable these large scale electromagnetic simulations are also highlighted. These results have been widely disseminated in numerous peer-reviewed publications including many Phys. Rev. Lett. papers and many invited presentations at prominent fusion conferences such as the biennial International Atomic Energy Agency (IAEA) Fusion Energy Conference and the annual meeting of the American Physics Society, Division of Plasma Physics (APS-DPP).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

PRIMA-X Final Report

The PRIMA-X (Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing) project is the successor of the DOE PRIMA (Performance Refactoring of Instrumentation, Measurement, and Analysis Technologies for Petascale Computing) project, which addressed the challenge of creating a core measurement infrastructure that would serve as a common platform for both integrating leading parallel performance systems (notably TAU and Scalasca) and developing next-generation scalable performance tools. The PRIMA-X project shifts the focus away from refactorization of robust performance tools towards a re-targeting of the parallel performance measurement and analysis architecture for extreme scales. The massive concurrency, asynchronous execution dynamics, hardware heterogeneity, and multi-objective prerequisites (performance, power, resilience) that identify exascale systems introduce fundamental constraints on the ability to carry forward existing performance methodologies. In particular, there must be a deemphasis of per-thread observation techniques to significantly reduce the otherwise unsustainable flood of redundant performance data. Instead, it will be necessary to assimilate multi-level resource observations into macroscopic performance views, from which resilient performance metrics can be attributed to the computational features of the application. This requires a scalable framework for node-level and system-wide monitoring and runtime analyses of dynamic performance information. Also, the interest in optimizing parallelism parameters with respect to performance and energy drives the integration of tool capabilities in the exascale environment further. Initially, PRIMA-X was a collaborative project between the University of Oregon (lead institution) and the German Research School for Simulation Sciences (GRS). Because Prof. Wolf, the PI at GRS, accepted a position as full professor at Technische Universität Darmstadt (TU Darmstadt) starting February 1st, 2015, the project ended at GRS on January 31st, 2015. This report reflects the work accomplished at GRS until then. The work of GRS is expected to be continued at TU Darmstadt. The first main accomplishment of GRS is the design of different thread-level aggregation techniques. We created a prototype capable of aggregating the thread-level information in performance profiles using these techniques. The next step will be the integration of the most promising techniques into the Score-P measurement system and their evaluation. The second main accomplishment is a substantial increase of Score-P’s scalability, achieved by improving the design of the system-tree representation in Score-P’s profile format. We developed a new representation and a distributed algorithm to create the scalable system tree representation. Finally, we developed a lightweight approach to MPI wait-state profiling. Former algorithms either needed piggy-backing, which can cause significant runtime overhead, or tracing, which comes with its own set of scaling challenges. Our approach works with local data only and, thus, is scalable and has very little overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

PRIMA-X - Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing

The PRIMA-X (Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing) project is the successor of the DOE PRIMA (Performance Refactoring of Instrumentation, Measurement, and Analysis Technologies for Petascale Computing) project, which addressed the challenge of creating a core measurement infrastructure that would serve as a common platform for both integrating leading parallel performance systems (notably TAU and Scalasca) and developing next-generation scalable performance tools. The PRIMA-X project shifts the focus away from refactorization of robust performance tools towards a re-targeting of the parallel performance measurement and analysis architecture for extreme scales. The massive concurrency, asynchronous execution dynamics, hardware heterogeneity, and multi-objective prerequisites (performance, power, resilience) that identify exascale systems introduce fundamental constraints on the ability to carry forward existing performance methodologies. In particular, there must be a deemphasis of per-thread observation techniques to significantly reduce the otherwise unsustainable flood of redundant performance data. Instead, it will be necessary to assimilate multi-level resource observations into macroscopic performance views, from which resilient performance metrics can be attributed to the computational features of the application. This requires a scalable framework for node-level and system-wide monitoring and runtime analyses of dynamic performance information. Also, the interest in optimizing parallelism parameters with respect to performance and energy drives the integration of tool capabilities in the exascale environment further. Initially, PRIMA-X was a collaborative project between the University of Oregon (lead institution) and the German Research School for Simulation Sciences (GRS). Because Prof. Wolf, the PI at GRS, accepted a position as full professor at Technische Universitaet Darmstadt (TU Darmstadt) starting February 1st, 2015, the work of GRS was continued at TU Darmstadt. This report covers the work at TU Darmstadt after the transition. The first main accomplishment of TU Darmstadt is the development of different techniques to aggregate performance data on the level of threads. TU Darmstadt evaluated different schemes designed at GRS during the first phase of this project and integrated them into Score-P, a widely used performance measurement framework for HPC applications. The second main accomplishment is a substantial increase of Score-P’s scalability, achieved by improving its internal representation of the underlying system. Third, we extended our performance-modeling tool Extra-P to automatically create models with more than one input parameter (e.g., process count and input size), which was previously impossible. These models allow the performance behavior of an application to be extrapolated to larger machines. Specific applications of the new multi-parameter capability realized in this project include modeling the isoefficiency function of task-based applications and a novel co-design methodology. Further extensions of Extra-P comprise online modeling functionality, automatic refinement of the model search space, and segmented performance modeling. Further contributions include new locality metrics for both shared- and distributed-memory applications, a new way of measuring the impact of inter-application inference on the execution time of an application, and finally an automatic method that selects appropriate OpenMP constructs for the parallelization of sequential code and classifies the affected variables based on their sharing semantics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Institute for Sustained Performance, Energy, and Resilience (SUPER): University of Utah Final Report

Over the course of this project, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) were exploiting a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry and material science. The computational systems underpinning this work increased in performance potential from tens to hundreds of Pflop/s, and evolved significantly from those in use at the beginning of the project in terms of available concurrency; wider use of accelerators such as graphics processing units(GPUs); and changes to the memory hierarchy including the incorporation of a new generation of persistent devices (e.g., phase change memory). To ensure that DOE's computational scientists can successfully exploit this emerging generation of high performance computing (HPC) systems, the University of Southern California (USC) assembled a broad team of computer scientists with the expertise to address the most pressing challenges of DOE's computing systems: (a) end-to-end performance optimization, including single-node performance, interprocessor communication, load balancing and I/O; (b) performance portability for heterogeneous systems, including accelerators; (c) minimizing energy consumption; (d) resilient computation; and, (e) exploiting new memory technology.

97 MATHEMATICS AND COMPUTING↗