Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Supercomputer”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

SNL software manual for the ACS Data Analytics Project.

In the ACS Data Analytics Project (also known as 'YumYum'), a supercomputer is modeled as a graph of components and dependencies, jobs and faults are simulated, and component fault rates are estimated using the graph structure and job pass/fail outcomes. This report documents the successful completion of all SNL deliverables and tasks, describes the software written by SNL for the project, and presents the data it generates. Readers should understand what the software tools are, how they fit together, and how to use them to reproduce the presented data and additional experiments as desired. The SNL YumYum tools provide the novel simulation and inference capabilities desired by ACS. SNL also developed and implemented a new algorithm, which provides faster estimates, at finer component granularity, on arbitrary directed acyclic graphs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Recovery Act: SeaMicro Volume Server Power Reduction Research Development

Cloud data centers are projected to be the fastest growing segment of the server market through 2015, according to IDC. Increasingly people and businesses rely on the Cloud to deliver digital content quickly and efficiently. Recovery Act funding from the Department of Energy has helped SeaMicro's technologies enhance the total cost of operation, performance and energy efficiency in large data center and Cloud environments. SeaMicro's innovative supercomputer fabric connects thousands of processor cores, memory, storage and input/output traffic. The company's fabric supports multiple processor instruction sets. Current systems featuring SeaMicro technology typically use one quarter the power and take one sixth the space of traditional servers with the same compute performance, yet deliver up to 12 times the bandwidth per core. Mozilla and eHarmony are two customers successfully using SeaMicro's technology. Numerous non-public customers have been successfully using the SeaMicro product in test and production facilities. As a result of the Recovery Act funding from the U.S. Department of Energy, more than 50 direct jobs were created at SeaMicro. To date, they primarily have been high-value, engineering jobs. Hardware, software and manufacturing engineering positions have been created, as well as sales and sales engineering. The positions have allowed SeaMicro to significantly accelerate engineering development and accelerate commercialization. As a result, commercialization and delivery to market are months ahead of initial schedule. Additional jobs were indirectly created through the development of the SeaMicro product. Through many years of research and hard work prior to receipt of public funding, SeaMicro was awarded 2 patents for its work. SeaMicro's product led the way for industry leaders to reconsider the market for low power servers and create new product lines. With valuable support of the U.S. Department of Energy and through SeaMicro's product, the market has been reshaped by the company's unique approach and ground breaking technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

NEAMS Update: Quarterly Report for October - December 2011

The Advanced Modeling and Simulation Office within the DOE Office of Nuclear Energy (NE) has been charged with revolutionizing the design tools used to build nuclear power plants during the next 10 years. To accomplish this, the DOE has brought together the national laboratories, U.S. universities, and the nuclear energy industry to establish the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program. The mission of NEAMS is to modernize computer modeling of nuclear energy systems and improve the fidelity and validity of modeling results using contemporary software environments and high-performance computers. NEAMS will create a set of engineering-level codes aimed at designing and analyzing the performance and safety of nuclear power plants and reactor fuels. The truly predictive nature of these codes will be achieved by modeling the governing phenomena at the spatial and temporal scales that dominate the behavior. These codes will be executed within a simulation environment that orchestrates code integration with respect to spatial meshing, computational resources, and execution to give the user a common 'look and feel' for setting up problems and displaying results. NEAMS is building upon a suite of existing simulation tools, including those developed by the federal Scientific Discovery through Advanced Computing and Advanced Simulation and Computing programs. NEAMS also draws upon existing simulation tools for materials and nuclear systems, although many of these are limited in terms of scale, applicability, and portability (their ability to be integrated into contemporary software and hardware architectures). NEAMS investments have directly and indirectly supported additional NE research and development programs, including those devoted to waste repositories, safeguarded separations systems, and long-term storage of used nuclear fuel. NEAMS is organized into two broad efforts, each comprising four elements. The quarterly highlights October-December 2011 are: (1) Version 1.0 of AMP, the fuel assembly performance code, was tested on the JAGUAR supercomputer and released on November 1, 2011, a detailed discussion of this new simulation tool is given; (2) A coolant sub-channel model and a preliminary UO{sub 2} smeared-cracking model were implemented in BISON, the single-pin fuel code, more information on how these models were developed and benchmarked is given; (3) The Object Kinetic Monte Carlo model was implemented to account for nucleation events in meso-scale simulations and a discussion of the significance of this advance is given; (4) The SHARP neutronics module, PROTEUS, was expanded to be applicable to all types of reactors, and a discussion of the importance of PROTEUS is given; (5) A plan has been finalized for integrating the high-fidelity, three-dimensional reactor code SHARP with both the systems-level code RELAP7 and the fuel assembly code AMP. This is a new initiative; (6) Work began to evaluate the applicability of AMP to the problem of dry storage of used fuel and to define a relevant problem to test the applicability; (7) A code to obtain phonon spectra from the force-constant matrix for a crystalline lattice has been completed. This important bridge between subcontinuum and continuum phenomena is discussed; (8) Benchmarking was begun on the meso-scale, finite-element fuels code MARMOT to validate its new variable splitting algorithm; (9) A very computationally demanding simulation of diffusion-driven nucleation of new microstructural features has been completed. An explanation of the difficulty of this simulation is given; (10) Experiments were conducted with deformed steel to validate a crystal plasticity finite-element code for bodycentered cubic iron; (11) The Capability Transfer Roadmap was completed and published as an internal laboratory technical report; (12) The AMP fuel assembly code input generator was integrated into the NEAMS Integrated Computational Environment (NiCE). More details on the planned NEAMS computing environment is given; and (13) The NEAMS program website (neams.energy.gov) is nearly ready to launch.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Cielo Computational Environment Usage Model: With Mappings to ACE Requirements for the General Availability User Environment Capabilities (Release V.1.1)

Cielo is a massively parallel supercomputer funded by the DOE/NNSA Advanced Simulation and Computing (ASC) program, and operated by the Alliance for Computing at Extreme Scale (ACES), a partnership between Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL). The primary Cielo compute platform is physically located at Los Alamos National Laboratory. This Cielo Computational Environment Usage Model documents the capabilities and the environment to be provided for the Q1 FY12 Level 2 Cielo Capability Computing (CCC) Platform Production Readiness Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model is focused on the needs of the ASC user working in the secure computing environments at Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory, or Sandia National Laboratories, but also addresses the needs of users working in the unclassified environment. The Cielo Computational Environment Usage Model maps the provided capabilities to the tri-Lab ASC Computing Environment (ACE) Version 8.0 requirements. The ACE requirements reflect the high performance computing requirements for the Production Readiness Milestone user environment capabilities of the ASC community. A description of ACE requirements met, and those requirements that are not met, are included in each section of this document. The Cielo Computing Environment, along with the ACE mappings, has been issued and reviewed throughout the tri-Lab community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Hopper Workload Analysis

The National Energy Research Scientific Computing (NERSC) Center is the primary computing facility for the United States Department of Energy, Office of Science. With over 5,000 users and over 600 different applications utilizing NERSC systems, it is critically important to examine the workload running on NERSCs large supercomputers in order to procure systems that perform well for a broad workload. In this paper we show the breakdown of the NERSC workload by science area, algorithm, memory, thread usage and more. We also describe the methods used to collect data from NERSCs Hopper (Cray XE6) system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Scalability under a Power Bound using the GREMLINs Framework

With the move towards exascale, system and software developers will have to deal with issues of extreme parallelism. The system properties affected most by the increase in node and core count are the shared resources on node and across the system. The increase in parallelism leads to reduced memory and bandwidth when regarding individual cores. Since power is a limiting factor for supercomputers, and power is not fully utilized in current systems, overprovisioning compute resources is a viable approach to maximized power utilization. To maximize system performance in regard to these changing conditions, it is necessary to understand how resource restrictions impact performance and system behavior. For the purpose of understanding anticipated system properties the GREMLINs Framework was developed. The framework gives the opportunity to add power restrictions, hinder memory properties and introduce faults to study resilience, among others. These features give the opportunity to use current petascale technology to study problems system designers and software developers will have to face when moving towards exascale and beyond. This work describes the initial release of the GREMLINs Framework, developed for this work, and shows how it can be used to study the scaling behavior of proxy applications. These proxy applications represent a selection of HPC workloads important to the scientific community. The proxy applications studied are AMG2013, an algebraic multi-grid linear system solver, CoMD, a classical molecular dynamics proxy application and NEKBONE, an application that uses a high order spectral element method to solve the Navier-Stokes equations. The main interest of these studies lies in analysis regarding their power behavior at scale under a power bound. These findings show how the GREMLINs Framework can help systems and software designers to attain better application performance and can also be used as basis for CPU power balancing tools to use power more efficiently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of already annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

University of Colorado - Center for Research and Education in Wind (CREW): Cooperative Research and Development Final Report, CRADA Number CRD-11-446

Enabled by petascale supercomputing, the next generation of computer models for wind energy will simulate a vast range of scales and physics, spanning from turbine structural dynamics and blade-scale turbulence to mesoscale atmospheric flow. A single model covering all scales and physics is not feasible. Thus, these simulations will require the coupling of different models/codes, each for different physics, interacting at their domain boundaries.

17 WIND ENERGY↗
DOE OSTI2015

Scientific Computing Strategic Plan for the Idaho National Laboratory

Scientific computing is a critical foundation of modern science. Without innovations in the field of computational science, the essential missions of the Department of Energy (DOE) would go unrealized. Taking a leadership role in such innovations is Idaho National Laboratory’s (INL’s) challenge and charge, and is central to INL’s ongoing success. Computing is an essential part of INL’s future. DOE science and technology missions rely firmly on computing capabilities in various forms. Modeling and simulation, fueled by innovations in computational science and validated through experiment, are a critical foundation of science and engineering. Big data analytics from an increasing number of widely varied sources is opening new windows of insight and discovery. Computing is a critical tool in education, science, engineering, and experiments. Advanced computing capabilities in the form of people, tools, computers, and facilities, will position INL competitively to deliver results and solutions on important national science and engineering challenges. A computing strategy must include much more than simply computers. The foundational enabling component of computing at many DOE national laboratories is the combination of a showcase like data center facility coupled with a very capable supercomputer. In addition, network connectivity, disk storage systems, and visualization hardware are critical and generally tightly coupled to the computer system and co located in the same facility. The existence of these resources in a single data center facility opens the doors to many opportunities that would not otherwise be possible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Iowa State University – Final Report for SciDAC3/NUCLEI project

The Iowa State University (ISU) contributions to the NUCLEI project are focused on developing, implementing and running an efficient and scalable configuration interaction code (Many-Fermion Dynamics – nuclear or MFDn) for leadership class supercomputers addressing forefront research problems in low-energy nuclear physics. We investigate nuclear structure and reactions with realistic nucleon-nucleon (NN) and three-nucleon (3N) interactions. We select a few highlights from our work that has produced a total of more than 82 refereed publications and more than 109 invited talks under SciDAC3/NUCLEI.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Optimizing Performance of Combustion Chemistry Solvers on Intel's Many Integrated Core (MIC) Architectures

This work investigates novel algorithm designs and optimization techniques for restructuring chemistry integrators in zero and multidimensional combustion solvers, which can then be effectively used on the emerging generation of Intel's Many Integrated Core/Xeon Phi processors. These processors offer increased computing performance via large number of lightweight cores at relatively lower clock speeds compared to traditional processors (e.g. Intel Sandybridge/Ivybridge) used in current supercomputers. This style of processor can be productively used for chemistry integrators that form a costly part of computational combustion codes, in spite of their relatively lower clock speeds. Performance commensurate with traditional processors is achieved here through the combination of careful memory layout, exposing multiple levels of fine grain parallelism and through extensive use of vendor supported libraries (Cilk Plus and Math Kernel Libraries). Important optimization techniques for efficient memory usage and vectorization have been identified and quantified. These optimizations resulted in a factor of ~ 3 speed-up using Intel 2013 compiler and ~ 1.5 using Intel 2017 compiler for large chemical mechanisms compared to the unoptimized version on the Intel Xeon Phi. The strategies, especially with respect to memory usage and vectorization, should also be beneficial for general purpose computational fluid dynamics codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

LATE POP III STAR FORMATION DURING THE EPOCH OF REIONIZATION: RESULTS FROM THE RENAISSANCE SIMULATIONS

We present results on the formation of Population III (Pop III) stars at redshift 7.6 from the Renaissance Simulations, a suite of extremely high-resolution and physics-rich radiation transport hydrodynamics cosmological adaptive-mesh refinement simulations of high-redshift galaxy formation performed on the Blue Waters supercomputer. In a survey volume of about 220 comoving Mpc{sup 3}, we found 14 Pop III galaxies with recent star formation. The surprisingly late formation of Pop III stars is possible due to two factors: (i) the metal enrichment process is local and slow, leaving plenty of pristine gas to exist in the vast volume; and (ii) strong Lyman–Werner radiation from vigorous metal-enriched star formation in early galaxies suppresses Pop III formation in (“not so”) small primordial halos with mass less than ∼3 × 10{sup 7} M {sub ⊙}. We quantify the properties of these Pop III galaxies and their Pop III star formation environments. We look for analogs to the recently discovered luminous Ly α emitter CR7, which has been interpreted as a Pop III star cluster within or near a metal-enriched star-forming galaxy. We find and discuss a system similar to this in some respects, however, the Pop III star cluster is far less massive and luminous than CR7 is inferred to be.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A new multi-energy neutrino radiation-hydrodynamics code in full general relativity and its application to the gravitational collapse of massive stars

We present a new multi-dimensional radiation-hydrodynamics code for massive stellar core-collapse in full general relativity (GR). Employing an M1 analytical closure scheme, we solve spectral neutrino transport of the radiation energy and momentum based on a truncated moment formalism. Regarding neutrino opacities, we take into account a baseline set in state-of-the-art simulations, in which inelastic neutrino–electron scattering, thermal neutrino production via pair annihilation, and nucleon–nucleon bremsstrahlung are included. While the Einstein field equations and the spatial advection terms in the radiation-hydrodynamics equations are evolved explicitly, the source terms due to neutrino–matter interactions and energy shift in the radiation moment equations are integrated implicitly by an iteration method. To verify our code, we first perform a series of standard radiation tests with analytical solutions that include the check of gravitational redshift and Doppler shift. A good agreement in these tests supports the reliability of the GR multi-energy neutrino transport scheme. We then conduct several test simulations of core-collapse, bounce, and shock stall of a 15M{sub ⊙} star in the Cartesian coordinates and make a detailed comparison with published results. Our code performs quite well to reproduce the results of full Boltzmann neutrino transport especially before bounce. In the postbounce phase, our code basically performs well, however, there are several differences that are most likely to come from the insufficient spatial resolution in our current 3D-GR models. For clarifying the resolution dependence and extending the code comparison in the late postbounce phase, we discuss that next-generation Exaflops class supercomputers are needed at least.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

WOMBAT: A Scalable and High-performance Astrophysical Magnetohydrodynamics Code

We present a new code for astrophysical magnetohydrodynamics specifically designed and optimized for high performance and scaling on modern and future supercomputers. We describe a novel hybrid OpenMP/MPI programming model that emerged from a collaboration between Cray, Inc. and the University of Minnesota. This design utilizes MPI-RMA optimized for thread scaling, which allows the code to run extremely efficiently at very high thread counts ideal for the latest generation of multi-core and many-core architectures. Such performance characteristics are needed in the era of “exascale” computing. We describe and demonstrate our high-performance design in detail with the intent that it may be used as a model for other, future astrophysical codes intended for applications demanding exceptional performance.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1992

SNS programming environment user's guide

This document briefly describes the computing environment for the Supercomputing Network Subsystem (SNS) of the Central Scientific Computing Complex of the Langley Research Center. The major SNS computers are a CRAY-2, a CRAY Y-MP, a CONVEX C-210, and a CONVEX C-220. It describes the software that is common to all of these computers, including; the UNIX operating system, graphics, networking utilities, mass storage, and mathematical libraries. It also describes file management, validation, SNS configuration, documentation and customer services. The document is intended for all SNS users as a ready reference to frequently asked questions and to more detailed information contained within the vendor manuals. It is appropriate for both the novice and the experienced user.

Supercomputing↗
NASA NTRS1998

Object-Oriented Scientific Programming with Fortran 90

Fortran 90 is a modern language that introduces many important new features beneficial for scientific programming. We discuss our experiences in plasma particle simulation and unstructured adaptive mesh refinement on supercomputers, illustrating the features of Fortran 90 that support the object-oriented methodology.

Fortran 90 Supercomputing Object-Oriented Adaptive↗
NASA NTRS2013

Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

tropical cyclone interannual variability↗
NASA NTRS2015

From Pixels to Planets

The Kepler Mission was launched in 2009 as NASAs first mission capable of finding Earth-size planets in the habitable zone of Sun-like stars. Its telescope consists of a 1.5-m primary mirror and a 0.95-m aperture. The 42 charge-coupled devices in its focal plane are read out every half hour, compressed, and then downlinked monthly. After four years, the second of four reaction wheels failed, ending the original mission. Back on earth, the Science Operations Center developed the Science Pipeline to analyze about 200,000 target stars in Keplers field of view, looking for evidence of periodic dimming suggesting that one or more planets had crossed the face of its host star. The Pipeline comprises several steps, from pixel-level calibration, through noise and artifact removal, to detection of transit-like signals and the construction of a suite of diagnostic tests to guard against false positives. The Kepler Science Pipeline consists of a pipeline infrastructure written in the Java programming language, which marshals data input to and output from MATLAB applications that are executed as external processes. The pipeline modules, which underwent continuous development and refinement even after data started arriving, employ several analytic techniques, many developed for the Kepler Project. Because of the large number of targets, the large amount of data per target and the complexity of the pipeline algorithms, the processing demands are daunting. Some pipeline modules require days to weeks to process all of their targets, even when run on NASA's 128-node Pleiades supercomputer. The software developers are still seeking ways to increase the throughput. To date, the Kepler project has discovered more than 4000 planetary candidates, of which more than 1000 have been independently confirmed or validated to be exoplanets. Funding for this mission is provided by NASAs Science Mission Directorate.

supercomputers↗