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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Domain decomposition in time for PDE-constrained optimization

Here, PDE-constrained optimization problems have a wide range of applications, but they lead to very large and ill-conditioned linear systems, especially if the problems are time dependent. In this paper we outline an approach for dealing with such problems by decomposing them in time and applying an additive Schwarz preconditioner in time, so that we can take advantage of parallel computers to deal with the very large linear systems. We then illustrate the performance of our method on a variety of problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Performance limits of ion extraction systems with non-circular apertures

A three-dimensional computer simulation is used to determine the perveance limitations of ion extraction systems with non-circular apertures. The objective of the study is to analyze the possibilities to improve mechanical strength of the ion optics made of carbon-carbon composite materials. Non-circular grid apertures are better suited to the physical structure of carbon-carbon composite materials, than conventionally used circular holes in a hexagonal pattern, because they allow a fewer number of cut fibers. However, the slit-type accelerating systems, usually regarded as the main alternative to the conventional ion optics, have an intolerably narrow range of operating perveance values at which there is no direct ion impingement on the acceleration grid. This paper presents results of comparative analysis of a number of different ion optical systems with non-circular apertures and conventional ion optical systems with circular apertures. It has been revealed that a relatively wide perveance range without direct ion impingement may be obtained with apertures shaped as a square with rounded corners. Numerical simulations show that this geometry may have equivalent perveance range as the traditional geometry with circular apertures while being more mechanically robust. In addition, such important characteristics, as the effective transparency for both the ions and the neutral atoms, the height of the potential barrier reflecting the downstream plasma electrons and the angular divergence of the beamlet also can be very close to these parameters for the optics with circular apertures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Advancing the Adoption of High Performance Computing for Time Domain Simulation

Time domain transient stability simulation of large interconnected power systems is becoming increasingly computationally intensive. With the addition of high levels of variable generation that can aggregately ramp over many hours, both the complexity and time horizon for which power system simulations will need to be conducted are increasing. Additionally, extended-term time domain simulation is required to analyze power system security when cascading events across the system span minutes or even hours. Analysis of these occurrences requires modeling power system dynamics over tens of minutes to many hours rather than tens of seconds. Because of the required high computational intensity, there are presently no stability modeling/simulation platforms that combine the needed computational capabilities with the required power system models relevant for representing and analyzing the potential reliability implications of phenomena that occurs over both short- and extended-term dynamic timeframes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

HPC Colony II: FAST_OS II: Operating Systems and Runtime Systems at Extreme Scale

HPC Colony II has been a 36-month project focused on providing portable performance for leadership class machines—a task made difficult by the emerging variety of more complex computer architectures. The project attempts to move the burden of portable performance to adaptive system software, thereby allowing domain scientists to concentrate on their field rather than the fine details of a new leadership class machine. To accomplish our goals, we focused on adding intelligence into the system software stack. Our revised components include: new techniques to address OS jitter; new techniques to dynamically address load imbalances; new techniques to map resources according to architectural subtleties and application dynamic behavior; new techniques to dramatically improve the performance of checkpoint-restart; and new techniques to address membership service issues at scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Architecture and performance of Perlmutter's 35 PB ClusterStor E1000 all-flash file system

NERSC's newest system, Perlmutter, features a 35 PB all-flash Lustre file system built on HPE Cray ClusterStor E1000. Here, we present its architecture, early performance figures, and performance considerations unique to this architecture. We demonstrate the performance of E1000 OSSes through low-level Lustre tests that achieve over 90% of the theoretical bandwidth of the SSDs at the OST and LNet levels. We also show end-to-end performance for both traditional dimensions of I/O performance (peak bulk-synchronous bandwidth) and nonoptimal workloads endemic to production computing (small, incoherent I/Os at random offsets) and compare them to NERSC's previous system, Cori, to illustrate that Perlmutter achieves the performance of a burst buffer and the resilience of a scratch file system. Finally, we discuss performance considerations unique to all-flash Lustre and present ways in which users and HPC facilities can adjust their I/O patterns and operations to make optimal use of such architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|Speedshop (Final Technical Report)

Peta-scale computing environments pose significant challenges for both system and application developers and addressing them required more than simply scaling up existing tera-scale solutions. Performance analysis tools play an important role in gaining this understanding, but previous monolithic tools with fixed feature sets have not sufficed. Instead, this project worked on the design, implementation, and evaluation of a general, flexible tool infrastructure supporting the construction of performance tools as “pipelines” of high-quality tool building blocks. These tool building blocks provide common performance tool functionality, and are designed for scalability, lightweight data acquisition and analysis, and interoperability. For this project, we built on Open|SpeedShop, a modular and extensible open source performance analysis tool set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Collaborative project. Ocean-atmosphere interaction from meso-to planetary-scale. Mechanisms, parameterization, and variability

This project aims to improve long term global climate simulations by resolving ocean mesoscale activity and the corresponding response in the atmosphere. The main computational objectives are; i) to perform and assess Community Earth System Model (CESM) simulations with the new Community Atmospheric Model (CAM) spectral element dynamical core; ii) use static mesh refinement to focus on oceanic fronts; iii) develop a new Earth System Modeling tool to investigate the atmospheric response to fronts by selectively filtering surface flux fields in the CESM coupler. The climate research objectives are 1) to improve the coupling of ocean fronts and the atmospheric boundary layer via investigations of dependency on model resolution and stability functions: 2) to understand and simulate the ensuing tropospheric response that has recently been documented in observations: and 3) to investigate the relationship of ocean frontal variability to low frequency climate variability and the accompanying storm tracks and extremes in high resolution simulations. This is a collaborative multi-institution project consisting of computational scientists, climate scientists and climate model developers. It specifically aims at DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Climate Science Performance, Data and Productivity on Titan

Climate Science models are flagship codes for the largest of high performance computing (HPC) resources, both in visibility, with the newly launched Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) effort, and in terms of significant fractions of system usage. The performance of the DOE ACME model is captured with application level timers and examined through a sizeable run archive. Performance and variability of compute, queue time and ancillary services are examined. As Climate Science advances in the use of HPC resources there has been an increase in the required human and data systems to achieve programs goals. A description of current workflow processes (hardware, software, human) and planned automation of the workflow, along with historical and projected data in motion and at rest data usage, are detailed. The combination of these two topics motivates a description of future systems requirements for DOE Climate Modeling efforts, focusing on the growth of data storage and network and disk bandwidth required to handle data at an acceptable rate.

Mayer, Benjamin W↗
DOE OSTI2019

LIVVkit 2.1: automated and extensible ice sheet model validation

A collection of scientific analyses, metrics, and visualizations for robustvalidation of ice sheet models is presented using the Land Ice Verificationand Validation toolkit (LIVVkit), version 2.1, and the LIVVkit Extensionsrepository (LEX), version 0.1. This software collection targets stand-aloneice sheet or coupled Earth system models, and handles datasets and analysesthat require high-performance computing and storage. LIVVkit aims to enableefficient and fully reproducible workflows for postprocessing, analysis, andvisualization of observational and model-derived datasets in a shareableformat, whereby all data, methodologies, and output are distributed to usersfor evaluation. Extending from the initial LIVVkit software framework, wedemonstrate Greenland ice sheet simulation validation metrics using thecoupled Community Earth System Model (CESM) as well as an idealizedstand-alone high-resolution Community Ice Sheet Model, version 2 (CISM2),coupled to the Albany/FELIX velocity solver (CISM-Albany or CISM-A). As oneexample of the capability, LIVVkit analyzes the degree to which modelscapture the surface mass balance (SMB) and identifies potential sources ofbias, using recently available in situ and remotely sensed data ascomparison. Related fields within atmosphere and land surface models, e.g.,surface temperature, radiation, and cloud cover, are also diagnosed. Appliedto the CESM1.0, LIVVkit identifies a positive SMB bias that is focusedlargely around Greenland's southwest region that is due to insufficientablation.

58 GEOSCIENCES↗
DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as p2r, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these miniapps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as \ptor, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these mini-apps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

Atif, Mohammad [Brookhaven] (ORCID:000000026889770↗
DOE OSTI2015

SU-E-T-152: Building An Ultrafast, Earthquake Proof Treatment Planning System

Purpose: Situated 20 miles from 5 major fault lines in California’s Bay Area, Stanford Universityhas a critical need for IT infrastructure planning to handle the high probability devastating earthquakes. Recently, a multi-million dollar project has been underway to overhaul Stanford’s radiation oncology information systems, maximizing planning system performance and providing true disaster recovery abilities. An overview of the project will be given with particular focus on lessons learned throughout the build. Methods: In this implementation, two isolated external datacenters provide geographical redundancy to Stanford’s main campus datacenter. Real-time mirroring is made of all data stored to our serial attached network (SAN) storage. In each datacenter, hardware/software virtualization was heavily implemented to maximize server efficiency and provide a robust mechanism to seamlessly migrate users in the event of an earthquake. System performance is routinely assessed through the use of virtualized data robots, able to log in to the system at scheduled times, perform routine planning tasks and report timing results to a performance dashboard. A substantial dose calculation framework (608 CPU cores) has been constructed as part of the implementation. Results: Migration to a virtualized server environment with a high performance SAN has resulted in up to a 45% speed up of common treatment planning tasks. Switching to a 608 core DCF has resulted in a 280% speed increase in dose calculations. Server tuning was found to further improved read/write performance by 20%. Disaster recovery tests are carried out quarterly and, although successful, remain time consuming to perform and verify functionality. Conclusion: Achieving true disaster recovery capabilities is possible through server virtualization, support from skilled IT staff and leadership. Substantial performance improvements are also achievable through careful tuning of server resources and disk read/write operations. Developing a streamlined method to comprehensively test failover is a key requirement to the system’s success.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

An advanced joint inversion system for CO 2 storage modeling with large date sets for characterization and real-time monitoring-enhancing storage performance and reducing failure risks under uncertainties

As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO 2 storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic, tracer and thermal tests before CO 2 injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO 2 storage examples.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2013

Performance implications from sizing a VM on multi-core systems: A Data analytic application s view

In this paper, we present a quantitative performance analysis of data analytics applications running on multi-core virtual machines. Such environments form the core of cloud computing. In addition, data analytics applications, such as Cassandra and Hadoop, are becoming increasingly popular on cloud computing platforms. This convergence necessitates a better understanding of the performance and cost implications of such hybrid systems. For example, the very rst step in hosting applications in virtualized environments, requires the user to con gure the number of virtual processors and the size of memory. To understand performance implications of this step, we benchmarked three Yahoo Cloud Serving Benchmark (YCSB) workloads in a virtualized multi-core environment. Our measurements indicate that the performance of Cassandra for YCSB workloads does not heavily depend on the processing capacity of a system, while the size of the data set is critical to performance relative to allocated memory. We also identi ed a strong relationship between the running time of workloads and various hardware events (last level cache loads, misses, and CPU migrations). From this analysis, we provide several suggestions to improve the performance of data analytics applications running on cloud computing environments.

Lim, Seung-Hwan↗
DOE OSTI2013

Optimized Hypervisor Scheduler for Parallel Discrete Event Simulations on Virtual Machine Platforms

With the advent of virtual machine (VM)-based platforms for parallel computing, it is now possible to execute parallel discrete event simulations (PDES) over multiple virtual machines, in contrast to executing in native mode directly over hardware as is traditionally done over the past decades. While mature VM-based parallel systems now offer new, compelling benefits such as serviceability, dynamic reconfigurability and overall cost effectiveness, the runtime performance of parallel applications can be significantly affected. In particular, most VM-based platforms are optimized for general workloads, but PDES execution exhibits unique dynamics significantly different from other workloads. Here we first present results from experiments that highlight the gross deterioration of the runtime performance of VM-based PDES simulations when executed using traditional VM schedulers, quantitatively showing the bad scaling properties of the scheduler as the number of VMs is increased. The mismatch is fundamental in nature in the sense that any fairness-based VM scheduler implementation would exhibit this mismatch with PDES runs. We also present a new scheduler optimized specifically for PDES applications, and describe its design and implementation. Experimental results obtained from running PDES benchmarks (PHOLD and vehicular traffic simulations) over VMs show over an order of magnitude improvement in the run time of the PDES-optimized scheduler relative to the regular VM scheduler, with over 20 reduction in run time of simulations using up to 64 VMs. The observations and results are timely in the context of emerging systems such as cloud platforms and VM-based high performance computing installations, highlighting to the community the need for PDES-specific support, and the feasibility of significantly reducing the runtime overhead for scalable PDES on VM platforms.

Yoginath, Srikanth B↗
DOE OSTI2012

Improving High-Performance Sparse Libraries Using Compiler-Assisted Specialization: A PETSc Case Study

Computers with hardware accelerators, also referred to as hybrid-core systems, speedup applications by offloading certain compute operations that can run faster on accelerators. Thus, it is not surprising that many of top500 supercomputers use accelerators. However, in addition to procurement cost, significant programming and porting effort is required to realize the potential benefit of such accelerators. Hence, before building such a system it is prudent to answer the question 'what is the projected performance benefit from accelerators for the workloads of interest?'. We address this question by way of a performance-modeling framework that predicts realizable application performance on accelerators rapidly and accurately without going to the considerable effort of porting and tuning. The modeling framework first automatically identifies commonly found compute patterns in scientific applications which we term idioms, which may benefit by accelerator technology. Next the framework models the predicted speedup of those idioms if they were to be ported to and run on hardware accelerators. As a proof of concept we characterize two kinds of accelerators 1) the FPGA accelerators on a Convey HC-1 system and 2) an NVIDIA FERMI GPU accelerator. We model performance of the idioms gather/scatter and stream and our predictions show that where these occur in two full-scale HPC applications, Milc and HYCOM, gather/scatter speeds up by as much as 15X, and stream by as much as 14X, whereas the overall compute time of Milc improves by 3.4% and HYCOM by 20%.

Computer Science↗
DOE OSTI2021

FY 2021 Mid-Year HPC Utilization Report M3UF-21IN0701018

Idaho National Laboratory (INL), supported by the Department of Energy Office of Nuclear Energy (DOE-NE) through the Nuclear Science User Facilities, provides access to supercomputer systems and data storage along with support staff for system management, software installation, cybersecurity and user support to the broader DOE-NE user community. Users include individuals at universities, industry, and government laboratories enabling a wide range of research and development and mission-supporting activities. The availability of high-performance computing (HPC) capabilities is a key foundation of collaboration and innovation in nuclear energy systems research. HPC resources and INL directly support the mission and objectives of DOE-NE. From October 2020 through March 2021, INL HPC capabilities were utilized by a diverse set of computing and applied researchers, for a wide range of research and engineering activities. This report focuses on current INL HPC systems and utilization from October 1, 2020 through March 31, 2021.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗