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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Performance monitoring for new phase dynamic optimization of instruction dispatch cluster configuration

In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Method and apparatus for offloading compute resources to a flash co-processing appliance

Solid-State Drive (SSD) burst buffer nodes are interposed into a parallel supercomputing cluster to enable fast burst checkpoint of cluster memory to or from nearby interconnected solid-state storage with asynchronous migration between the burst buffer nodes and slower more distant disk storage. The SSD nodes also perform tasks offloaded from the compute nodes or associated with the checkpoint data. For example, the data for the next job is preloaded in the SSD node and very fast uploaded to the respective compute node just before the next job starts. During a job, the SSD nodes perform fast visualization and statistical analysis upon the checkpoint data. The SSD nodes can also perform data reduction and encryption of the checkpoint data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Architecture and method for a burst buffer using flash technology

A parallel supercomputing cluster includes compute nodes interconnected in a mesh of data links for executing an MPI job, and solid-state storage nodes each linked to a respective group of the compute nodes for receiving checkpoint data from the respective compute nodes, and magnetic disk storage linked to each of the solid-state storage nodes for asynchronous migration of the checkpoint data from the solid-state storage nodes to the magnetic disk storage. Each solid-state storage node presents a file system interface to the MPI job, and multiple MPI processes of the MPI job write the checkpoint data to a shared file in the solid-state storage in a strided fashion, and the solid-state storage node asynchronously migrates the checkpoint data from the shared file in the solid-state storage to the magnetic disk storage and writes the checkpoint data to the magnetic disk storage in a sequential fashion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A skyrmionic topology perspective on Lehmann clusters

When two parallel coplanar dislocations with opposite Burgers vectors are brought into collision by the action of stress in solid crystals, they annihilate each other. In cholesterics with pitch p, under certain conditions, colliding dislocations with Burgers vectors b = p and b = − p are immune against annihilation and form stable twin-like pairs known as Lehmann clusters. We point out that this immunity is due to the escape of the director field into the third dimension. We show that from a topological point of view, Lehmann clusters can be seen as skyrmion tubes embedded in a helicoidal background, and their extremities have the topology of monopoles.

Pieranski, Pawel [Univ. Paris-Saclay, Orsay (Franc↗
DOE OSTI2014

PGP: parallel prokaryotic proteogenomics pipeline for MPI clusters, high-throughput batch clusters and multicore workstations

Summary: We present the first public release of our proteogenomic annotation pipeline. We have previously used our original unreleased implementation to improve the annotation of 46 diverse prokaryotic genomes by discovering novel genes, post-translational modifications and correcting the erroneous annotations by analyzing proteomic mass-spectrometry data. This public version has been redesigned to run in a wide range of parallel Linux computing environments and provided with the automated configuration, build and testing facilities for easy deployment and portability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Memory Optimization for Phase-field Simulations

Phase-field simulations are computationally and memory intensive applications. Many of the phase-field simulations being conducted in support of NEAMS were not capable of running on “normal clusters” with 2-4GB of RAM per core, and instead required specialized “big-memory” clusters with 64GB per core. To address this issue, the MOOSE team developed a new Python-based utility called MemoryLogger, and applied it to locate, diagnose, and eradicate memory bottlenecks within the MOOSE framework. MemoryLogger allows for a better understanding of the memory usage of an application being run in parallel across a cluster. Memory usage information is captured for every individual process in a parallel job, and communicated to the head node of the cluster. Console text output from the application itself is automatically matched with this memory usage information to produce a detailed picture of memory usage over time, making it straightforward to identify the subroutines which contribute most to the application’s peak memory usage. The information produced by the MemoryLogger quickly and effectively narrows the search for memory optimizations to the most data-intensive parts of the simulation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Reverse computation is presented here as an important future direction in addressing the challenge of fault tolerant execution on very large cluster platforms for parallel computing. As the scale of parallel jobs increases, traditional checkpointing approaches suffer scalability problems ranging from computational slowdowns to high congestion at the persistent stores for checkpoints. Reverse computation can overcome such problems and is also better suited for parallel computing on newer architectures with smaller, cheaper or energy-efficient memories and file systems. Initial evidence for the feasibility of reverse computation in large systems is presented with detailed performance data from a particle simulation scaling to 65,536 processor cores and 950 accelerators (GPUs). Reverse computation is observed to deliver very large gains relative to checkpointing schemes when nodes rely on their host processors/memory to tolerate faults at their accelerators. A comparison between reverse computation and checkpointing with measurements such as cache miss ratios, TLB misses and memory usage indicates that reverse computation is hard to ignore as a future alternative to be pursued in emerging architectures.

Perumalla, Kalyan S↗
DOE OSTI2015

First frontier field constraints on the cosmic star formation rate density AT z ~ 10—the impact of lensing shear on completeness of high-redshift galaxy samples

In this work, we search the complete Hubble Frontier Field data set of Abell 2744 and its parallel field for $z\sim 10$ sources to further refine the evolution of the cosmic star formation rate density (SFRD) between $z\sim 8$ and $z\sim 10$. We independently confirm two images of the recently discovered triply imaged $z\sim 9.8$ source by Zitrin et al. and set an upper limit for similar $z\sim 10$ galaxies with red colors of ${J}_{125}-{H}_{160}\gt 1.2$ in the parallel field of Abell 2744. We utilize extensive simulations to derive the effective selection volume of Lyman-break galaxies at $z\sim 10$, both in the lensed cluster field and in the adjacent parallel field. Particular care is taken to include position-dependent lensing shear to accurately account for the expected sizes and morphologies of highly magnified sources. We show that both source blending and shear reduce the completeness at a given observed magnitude in the cluster, particularly near the critical curves. These effects have a significant, but largely overlooked, impact on the detectability of high-redshift sources behind clusters, and substantially reduce the expected number of highly magnified sources. The detections and limits from both pointings result in an SFRD which is consistent within the uncertainties with previous estimates at $z\sim 10$ from blank fields. The combination of these new results with all other estimates is also consistent with a rapidly declining SFRD in the 170 Myr from $z\sim 8$ to $z\sim 10$ as predicted by cosmological simulations and dark-matter halo evolution in ΛCDM. Once biases introduced by magnification-dependent completeness are accounted for, the full six cluster and parallel Frontier Field program will be an extremely powerful new data set to probe the evolution of the galaxy population at $z\gt 8$ before the advent of the James Webb Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Integrin nanoclusters can bridge thin matrix fibres to form cell–matrix adhesions

Integrin-mediated cell-matrix adhesions are key to sensing the geometry and rigidity of extracellular environments and influence vital cellular processes. In vivo, the extracellular matrix is composed of fibrous arrays. To understand the fibre geometries that are required for adhesion formation, we patterned nanolines of various line widths and arrangements in single, crossing or paired arrays with the integrin-binding peptide Arg-Gly-Asp. Single thin lines (width ≤ 30 nm) did not support cell spreading or formation of focal adhesions, despite the presence of a high density of Arg-Gly-Asp, but wide lines (>40 nm) did. Using super-resolution microscopy, we observed stable, dense integrin clusters formed on parallel (within 110 nm) or crossing thin lines (mimicking a matrix mesh) similar to those on continuous substrates. These dense clusters bridged the line pairs by recruiting activated but unliganded integrins, as verified by integrin mutants unable to bind ligands that coclustered with ligand-bound integrins when present in an active extended conformation. Furthermore, in a fibrous extracellular matrix mesh, stable integrin nano-clusters bridge between thin (≤ 30 nm) matrix fibres and bring about downstream consequences of cell motility and growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Automated pipeline framework for processing of large-scale building energy time series data

Commercial buildings account for one third of the total electricity consumption in the United States and a significant amount of this energy is wasted. Therefore, there is a need for “virtual” energy audits, to identify energy inefficiencies and their associated savings opportunities using methods that can be non-intrusive and automated for application to large populations of buildings. Here we demonstrate virtual energy audits applied to large populations of buildings’ time-series smart-meter data using a systematic approach and a fully automated Building Energy Analytics (BEA) Pipeline that unifies, cleans, stores and analyzes building energy datasets in a non-relational data warehouse for efficient insights and results. This BEA pipeline is based on a custom compute job scheduler for a high performance computing cluster to enable parallel processing of Slurm jobs. Within the analytics pipeline, we introduced a data qualification tool that enhances data quality by fixing common errors, while also detecting abnormalities in a building’s daily operation using hierarchical clustering. We analyze the HVAC scheduling of a population of 816 buildings, using this analytics pipeline, as part of a cross-sectional study. With our approach, this sample of 816 buildings is improved in data quality and is efficiently analyzed in 34 minutes, which is 85 times faster than the time taken by a sequential processing. The analytical results for the HVAC operational hours of these buildings show that among 10 building use types, food sales buildings with 17.75 hours of daily HVAC cooling operation are decent targets for HVAC savings. Overall, this analytics pipeline enables the identification of statistically significant results from population based studies of large numbers of building energy time-series datasets with robust results. These types of BEA studies can explore numerous factors impacting building energy efficiency and virtual building energy audits. This approach enables a new generation of data-driven buildings energy analysis at scale.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Coupled‐cluster singles, doubles and perturbative triples with density fitting approximation for massively parallel heterogeneous platforms

Abstract A high‐performance implementation of the coupled‐cluster singles, doubles, and perturbative triples [CCSD(T)] is developed in the Massively Parallel Quantum Chemistry program. Novel features include: (1) reduced memory requirements via a density‐fitting (DF) CCSD implementation utilizing distributed lazy evaluation for tensors with more than two unoccupied indices and (2) the ability to utilize efficiently many‐core nodes (Intel Xeon Phi) and heterogeneous nodes with multiple NVIDIA GPUs on each node. All data that are greater than quadratic in the system size are distributed among processes. Excellent strong scaling is observed on distributed‐memory computers equipped with conventional CPUs, Intel Xeon Phi processors, and heterogeneous nodes with multiple NVIDIA GPUs Canonical CCSD(T) energies can be evaluated for systems containing 200 electrons and 1000 basis functions in a few days using a small size commodity cluster, with even larger computations possible on leadership‐class computing resources.

Peng, Chong↗
DOE OSTI2013

Parallel implementation of three-dimensional molecular dynamic simulation for laser-cluster interaction

The objective of this article is to report the parallel implementation of the 3D molecular dynamic simulation code for laser-cluster interactions. The benchmarking of the code has been done by comparing the simulation results with some of the experiments reported in the literature. Scaling laws for the computational time is established by varying the number of processor cores and number of macroparticles used. The capabilities of the code are highlighted by implementing various diagnostic tools. To study the dynamics of the laser-cluster interactions, the executable version of the code is available from the author.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Noniterative Multireference Coupled Cluster Methods on Heterogeneous CPU-GPU Systems

A novel parallel algorithm for non-iterative multireference coupled cluster (MRCC) theories, which merges recently introduced reference-level parallelism (RLP) [K. Bhaskaran-Nair, J.Brabec, E. Aprà, H.J.J. van Dam, J. Pittner, K. Kowalski, J. Chem. Phys. 137, 094112 (2012)] with the possibility of accelerating numerical calculations using graphics processing unit (GPU) is presented. We discuss the performance of this algorithm on the example of the MRCCSD(T) method (iterative singles and doubles and perturbative triples), where the corrections due to triples are added to the diagonal elements of the MRCCSD (iterative singles and doubles) effective Hamiltonian matrix. The performance of the combined RLP/GPU algorithm is illustrated on the example of the Brillouin-Wigner (BW) and Mukherjee (Mk) state-specific MRCCSD(T) formulations.

Brillouin-Wigner↗
DOE OSTI2026

Speedup of UEDGE Parameter Scans Using Machine-Learning Optimized OpenMP Parallelization and a Continuation Solver

This article presents the OpenMP parallelization of the preconditioning Jacobian assembly and right‐hand side residual evaluation in UEDGE. A continuation algorithm, utilizing the internal NKSOL implicit Jacobian‐Free Newton‐Krylov solver to efficiently scan physical parameters, is also presented. The implemented parallelization reduces the computational time for a benchmark scan run on 32 threads by compared to the serial version when using trained random forest regression models to identify the optimal decomposition of the system of equations. Random forest regression models applied to the UEDGE time‐dependent and continuation solver algorithms did not yield meaningful improvement in computational performance. A benchmark DIII‐D gas injection rate scan in the 0.35–0.75 kA interval, performed on a test cluster using the parallelized code and continuation solver, produced 1066 steady‐state solutions with a 22 s average wall‐clock computational time per steady‐state solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

We present Π4U,{sup 1} an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

How Cloud is Accelerating Research at NREL

This presentation coincides with AWS's announcement of their new Parallel Computing Service (PCS) which allows for easy creation of HPC-style clusters in their AWS cloud computing platform. I helped them beta test this service before it was made generally available in August. AWS asked if we would be interested in discussing our experience with the PCS service, and our experience with HPC workloads in the cloud in general, so this slideshow discusses a brief history of scientific computing at NREL and shares a bit of our experiences and approach to utilizing cloud services for HPC-style workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Glass-like energy and property landscape of Pt nanoclusters

Pt nanoclusters play an important role in catalysis-related applications. Essential to their activities are their geometries and energy landscapes. In this work, we studied the energy landscapes of Pt clusters using a parallel differential evolution optimization algorithm and an accelerated ab initio atomic relaxation method, which allowed us to explore unprecedentedly large numbers of geometry local minima at ab initio level. We found many lower-energy isomers with low symmetry in their geometry. The energy landscapes were demonstrated to be glass-like with a large number of local minimum structures close to the global minimum. The electronic and magnetic properties of most glass-like local minima were dramatically different from the global minimum, and they should be observed in the experimental measurements. The connections between these local minima were further analyzed using data mining techniques.

Chen, Zhanghui↗