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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 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the popular Markov Cluster Algorithm (MCL) and can cluster large-scale networks within hours using a few thousand CPU-equipped nodes. It relies on sparse matrix computations and heavily makes use of the sparse matrix-sparse matrix multiplication kernel (SpGEMM). The existing parallel algorithms in HipMCL are not scalable to Exascale architectures, both due to their communication costs dominating the runtime at large concurrencies and also due to their inability to take advantage of accelerators that are increasingly popular. In this work, we systematically remove scalability and performance bottlenecks of HipMCL. We enable GPUs by performing the expensive expansion phase of the MCL algorithm on GPU. Additionally, we propose a CPU-GPU joint distributed SpGEMM algorithm called pipelined Sparse SUMMA and integrate a probabilistic memory requirement estimator that is fast and accurate. Furthermore, we develop a new merging algorithm for the incremental processing of partial results produced by the GPUs, which improves the overlap efficiency and the peak memory usage. We also integrate a recent and faster algorithm for performing SpGEMM on CPUs. We validate our new algorithms and optimizations with extensive evaluations. With the enabling of the GPUs and integration of new algorithms, HipMCL is up to 12.4x faster, being able to cluster a network with 70 million proteins and 68 billion connections just under 15 minutes using 1024 nodes of ORNL's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Comfort in High-Performance Homes in a Hot-Humid Climate

"9IBACOS monitored 37 homes during the late summer and early fall of 2014 in a hot and humid climate to better understand indoor comfort conditions. These homes were constructed in the last several years by four home builders that offered a comfort and performance guarantee for the homes. The homes were located in one of four cities: Tampa, Florida; Orlando, Florida; Houston, Texas; and San Antonio, Texas. Temperature and humidity data were collected from the thermostat and each room of the house using small, battery-powered data loggers. To understand system runtime and its impact on comfort, supply air temperature also was measured on a 1-minute interval. Overall, the group of homes only exceeded a room-to-room temperature difference of 6 degrees F for 5% of the time. For 80% of the time, the rooms in each house were within 4 degrees F of each other. Additionally, the impact of system runtime on comfort is discussed. Finally, measurements made at the thermostat were used to better understand the occupant operation of each cooling system's thermostat setpoint. Builders were questioned on their perceived impact of offering a comfort and performance guarantee. Their feedback, which generally indicates a positive perception, has been summarized in the report.

"9residential↗

DOE OSTI2017

Automatic translation of MPI source into a latency-tolerant, data-driven form

Hiding communication behind useful computation is an important performance programming technique but remains an inscrutable programming exercise even for the expert. We present Bamboo, a code transformation framework that can realize communication overlap in applications written in MPI without the need to intrusively modify the source code. Bamboo reformulates MPI source into the form of a task dependency graph that expresses a partial ordering among tasks, enabling the program to execute in a data-driven fashion under the control of an external runtime system. Experimental results demonstrate that Bamboo significantly reduces communication delays while requiring only modest amounts of programmer annotation for a variety of applications and platforms, including those employing co-processors and accelerators. Moreover, Bamboo's performance meets or exceeds that of labor-intensive hand coding. The translator is more than a means of hiding communication costs automatically; it demonstrates the utility of semantic level optimization against a wellknown library.

Communication-computation↗

NASA NTRS1990

Validation environment for AIPS/ALS: Implementation and results

The work is presented which was performed in porting the Fault Injection-based Automated Testing (FIAT) and Programming and Instrumentation Environments (PIE) validation tools, to the Advanced Information Processing System (AIPS) in the context of the Ada Language System (ALS) application, as well as an initial fault free validation of the available AIPS system. The PIE components implemented on AIPS provide the monitoring mechanisms required for validation. These mechanisms represent a substantial portion of the FIAT system. Moreover, these are required for the implementation of the FIAT environment on AIPS. Using these components, an initial fault free validation of the AIPS system was performed. The implementation is described of the FIAT/PIE system, configured for fault free validation of the AIPS fault tolerant computer system. The PIE components were modified to support the Ada language. A special purpose AIPS/Ada runtime monitoring and data collection was implemented. A number of initial Ada programs running on the PIE/AIPS system were implemented. The instrumentation of the Ada programs was accomplished automatically inside the PIE programming environment. PIE's on-line graphical views show vividly and accurately the performance characteristics of Ada programs, AIPS kernel and the application's interaction with the AIPS kernel. The data collection mechanisms were written in a high level language, Ada, and provide a high degree of flexibility for implementation under various system conditions.

Segall, Zary↗

DOE OSTI2021

Evaluating adaptive and predictive power management strategies for optimizing visualization performance on supercomputers

Power is becoming an increasingly scarce resource on the next generation of supercomputers, and should be used wisely to improve overall performance. One strategy for improving power usage is hardware overprovisioning, i.e., systems with more nodes than can be run at full power simultaneously without exceeding the system-wide power limit. With this study, we compare two strategies for allocating power throughout an overprovisioned system – adaptation and prediction – in the context of visualization workloads. While adaptation has been suitable for workloads with more regular execution behaviors, it may not be as suitable on visualization workloads, since they can have variable execution behaviors. This study considers a total of 104 experiments, which vary the rendering workload, power budget, allocation strategy, and node concurrency, including tests processing data sets up to 1 billion cells and using up to 18,432 cores across 512 nodes. Overall, we find that prediction is a superior strategy for this use case, improving performance up to 27% compared to an adaptive strategy.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗

DOE OSTI2023

Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems

Challenging combinatorial optimization problems are ubiquitous in science and engineering. Several quantum methods for optimization have recently been developed, in different settings including both exact and approximate solvers. Addressing this field of research, this manuscript has three distinct purposes. First, we present an intuitive method for synthesizing and analyzing discrete (i.e., integer-based) optimization problems, wherein the problem and corresponding algorithmic primitives are expressed using a discrete quantum intermediate representation (DQIR) that is encoding-independent. This compact representation often allows for more efficient problem compilation, automated analyses of different encoding choices, easier interpretability, more complex runtime procedures, and richer programmability, as compared to previous approaches, which we demonstrate with a number of examples. Second, we perform numerical studies comparing several qubit encodings; the results exhibit a number of preliminary trends that help guide the choice of encoding for a particular set of hardware and a particular problem and algorithm. Our study includes problems related to graph coloring, the traveling salesperson problem, factory/machine scheduling, financial portfolio rebalancing, and integer linear programming. Third, we design low-depth graph-derived partial mixers (GDPMs) up to 16-level quantum variables, demonstrating that compact (binary) encodings are more amenable to QAOA than previously understood. We expect this toolkit of programming abstractions and low-level building blocks to aid in designing quantum algorithms for discrete combinatorial problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Evaluating the Practicability of Multiphase CFD for BWR Fuel Assembly Analysis

Multiphase computational fluid dynamics (M-CFD) models of a boiling water reactor (BWR) fuel assembly have been generated in the commercial CFD code, STAR-CCM+ Ver.11.04.010-R8. The Eulerian multiphase approach was employed, in combination with a baseline ‘Zero Closure model’ for two-phase flow boiling, applicable to high void fraction regimes. The capability and practicability of MCFD for BWR fuel assembly were evaluated against the international OECD/NRC BWR Full-size Finemesh Bundle Test (BFBT) benchmark data. The benchmark selected, BFBT-4101-61, is a steady-state full power case, with high void fraction conditions. Geometrical modeling and mesh construction of BWR assemblies introduce challenges in generating high quality computational meshes, while retaining a low cell count to allow acceptable runtimes. In order to evaluate the scalability of the CFD code, parallel CFD simulations were carried out with the High Performance Computing (HPC) system of the Idaho National Laboratory. M-CFD results display good agreement with the experimental data for both local void fraction distribution and exit quality. The parallel speedup factor is linearly proportional to the number of processors up to 500 cores, and retains over 92% efficiency with 1000 cores. The execution time of the simulation decreased exponentially with increasing number of processors while the cost of the simulation increased linearly. The proposed baseline closure, in combination with the parallel performance of the STAR-CCM+ code demonstrated promising capabilities for analyzing BWR fuel assemblies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Balancing Performance and Portability with Containers in HPC: An OpenSHMEM Example

There is a growing interest in using Linux containers to streamline software development and application deployment. A container enables the user to bundle the salient elements of the software stack from an application’s perspective. In this paper, we discuss initial experiences in using the Open MPI implementation of OpenSHMEM with containers on HPC resources. We provide a brief overview of two container runtimes, Docker & Singularity, highlighting elements that are of interest for HPC users. The Docker platform offers a rich set of services that are widely used in enterprise environments, whereas Singularity is an emerging container runtime that is specifically written for use on HPC systems. We describe our procedure for container assembly and deployment that strives to maintain the portability of the container-based application. We show performance results for the Graph500 benchmark running along the typical continuum of development testbed up to full production supercomputer (ORNL’s Titan). The results show consistent performance between the native and Singularity (container) tests. The results also showed an unexplained drop in performance when using the Cray Gemini network with Open MPI’s OpenSHMEM, which was unrelated to the container usage.

Naughton III, Thomas↗

DOE OSTI2023

Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs

ENRICO is a coupled application developed under the U.S. Department of Energy's Exascale Computing Project (ECP) targeting the modeling of advanced nuclear reactors. It couples radiation transport with heat and fluid simulation, including the high-fidelity, highresolution Monte-Carlo code Shift and the Computational fluid dynamics code NekRS. NekRS is a highly-performant open-source code for simulation of incompressible and low-Mach fluid flow, heat transfer, and combustion with a particular focus on turbulent flows in complex domains. It is based on rapidly convergent high-order spectral element discretizations that feature minimal numerical dissipation and dispersion. State-of-the-art multilevel preconditioners, efficient high-order time-splitting methods, and runtime-adaptive communication strategies are built on a fast OCCA-based kernel library, libParanumal, to provide scalability and portability across the spectrum of current and future high-performance computing platforms. On Frontier, Nek5000/RS has recently achieved an unprecedented milestone in breaching over 1 billion spectral elements and 350 billion degrees of freedom. Shift has demonstrated the capability to transport upwards of 1 billion particles per second in full core nuclear reactor simulations featuring complete temperature-dependent, continuous-energy physics on Frontier. Shift achieved a weak-scaling efficiency of 97.8% on 8192 nodes of Frontier and calculated 6 reactions in 214,896 fuel pin regions below 1% statistical error yielding first-of-a-kind resolution for a Monte Carlo transport application.

Hamilton, Steven P.↗

DOE OSTI2024

Circumventing superexponential runtimes for hard instances of quantum adiabatic optimization

Classical optimization problems can be solved by adiabatically preparing the ground state of a quantum Hamiltonian that encodes the problem. The performance of this approach is determined by the smallest gap encountered during the evolution. Here, we consider the maximum independent set problem, which can be efficiently encoded in the Hamiltonian describing a Rydberg atom array. We present a general construction of instances of the problem for which the minimum gap decays superexponentially with system size, implying a superexponentially large time to solution via adiabatic evolution. The small gap arises from locally independent choices which cause the system to initially evolve and localize into a configuration far from the solution in terms of Hamming distance. We investigate remedies to this problem. Specifically, we show that quantum quenches in these models can exhibit signatures of quantum many-body scars, which in turn, can circumvent the superexponential gaps. By quenching from a suboptimal configuration, states with a larger ground-state overlap can be prepared, illustrating the utility of quantum quenches as an algorithmic tool. Published by the American Physical Society 2024

Schiffer, Benjamin F. (ORCID:0000000189512157)↗

DOE OSTI2018

SHAD: the Scalable High-performance Algorithms and Data-structures Library

The unprecedented amount of data that needs to be processed in emerging data analytics applications poses novel challenges to industry and academia. Scalability and high performance become more than a desirable feature because, due to the scale and the nature of the problems, they draw the line between what is achievable and what is unfeasible. In this paper, we propose SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD adopts a modular design that confines low level details and promotes reuse. SHAD's core is built on an Abstract Runtime Interface which enhances portability and identifies the minimal set of features of the underlying system required by the framework. The core library includes common data-structures such as: Array, Vector, Map and Set. These are designed to accommodate significant amount of data which can be accessed in massively parallel environments, and used as building blocks for SHAD extensions, i.e. higher level software libraries. We have validated and evaluated our design with a performance and scalability study of the core components of the library. We have validated the design flexibility by proposing a Graph Library as an example of SHAD extension, which implements two different graph data-structures; we evaluate their performance with a set of graph applications. Experimental results show that the approach is promising in terms of both performance and scalability. On a distributed system with 320 cores, SHAD Arrays are able to sustain a throughput of 65 billion operations per second, while SHAD Maps sustain 1 billion of operations per second. Algorithms implemented using the Graph Library exhibit performance and scalability comparable to a custom solution, but with smaller development effort.

Castellana, Vito G.↗

DOE OSTI2019

Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems?

For a production high-performance computing (HPC) system, where storage devices are shared between multiple applications and managed in a best effort manner, I/O contention is often a major problem. In this paper, we propose a balanced messaging-based re-routing in conjunction with throttling at the middleware level. This work tackles two key challenges that have not been fully resolved in the past: whether I/O variability can be reduced on a QoS-less HPC storage system, and how to design a runtime scheduling system that can scale up to a large amount of cores. The proposed scheme uses a two-level messaging system to re-route I/O requests to a less congested storage location so that write performance is improved, while limiting the impact on read by throttling re-routing. An analytical model is derived to guide the setup of optimal throttling factor. We thoroughly analyze the virtual messaging layer overhead and explore whether the in-transit buffering is effective in managing I/O variability. Contrary to the intuition, in-transit buffer cannot completely solve the problem. It can reduce the absolute variability but not the relative variability. The proposed scheme is verified against a synthetic benchmark as well as being used by production applications.

Huang, Dan↗

NASA NTRS2018

Runtime Assurance Protection for Advanced Turbofan Engine Control

This paper describes technical progress made in the application of run time assurance (RTA) methods to turbofan engines with advanced propulsion control algorithms that are employed to improve engine performance. It is assumed that the advanced algorithms cannot be fully certified using current verification and validation approaches and therefore need to be continually monitored by an RTA system that ensures safe operation. However, current turbofan engine control systems utilize engine protection logic for safe combustion dynamics and stable airflow through the engine. It was determined that the engine protection logic should continue to be used to provide system safety and should be considered as a part of the overall RTA system. The additional function that an RTA system provides is to perform diagnostics on anomalous conditions to determine if these conditions are being caused by errors in the advanced controller. If this is the case, the RTA system switches operation to a trusted reversionary controller. Initial studies were performed to demonstrate this benefit. The other focus was to improve the performance of the engine protection logic, which was deemed too conservative and reduced engine performance during transient operations. It was determined that the conservative response was due to poor tuning of one of the controller channels within the protection logic. An automatic tuning algorithm was implemented to optimize the protection logic control gains based on minimizing tracking error. Improved tracking responses were observed with no change to the existing protection logic control architecture.

runtime monitoring↗

DOE OSTI2022

Accelerating the Inference of the Exa.TrkX Pipeline

Recently, graph neural networks (GNNs) have been successfully used for a variety of particle reconstruction problems in high energy physics, including particle tracking. The Exa.TrkX pipeline based on GNNs demonstrated promising performance in reconstructing particle tracks in dense environments. It includes five discrete steps: data encoding, graph building, edge filtering, GNN, and track labeling. All steps were written in Python and run on both GPUs and CPUs. In this work, we accelerate the Python implementation of the pipeline through customized and commercial GPU-enabled software libraries, and develop a C++ implementation for inferencing the pipeline. The implementation features an improved, CUDA-enabled fixed-radius nearest neighbor search for graph building and a weakly connected component graph algorithm for track labeling. GNNs and other trained deep learning models are converted to ONNX and inferenced via the ONNX Runtime C++ API. The complete C++ implementation of the pipeline allows integration with existing tracking software. We report the memory usage and average event latency tracking performance of our implementation applied to the TrackML benchmark dataset.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Quasielastic neutron scattering measurements and ab initio MD-simulations on single ion motions in molten NaF

The ionic stochastic motions in the molten alkali halide NaF are investigated by quasielastic neutron scattering and first principles molecular dynamics simulation. Quasielastic neutron scattering was employed to extract the diffusion behavior of the sodium ions in the melt. An extensive first principles based simulation on a box of up to 512 particles has been performed to complement the experimental data. From that large box, a smaller 64-particle box has then been simulated over a runtime of 60 ps. A good agreement between calculated and neutron data on the level of spectral shape has been obtained. The obtained sodium diffusion coefficients agree very well. The simulation predicts a fluorine diffusion coefficient similar to the sodium one. Applying the Nernst-Einstein equation, a remarkable large cross correlation between both ions can be deduced. The velocity cross correlations demonstrate a positive correlation between the ions over a period of 0.1 ps. That strong correlation is evidence that the unlike ions do not move completely statistically independent and have a strong association over a short period of time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Importance Sampling Model-Based Diffusion for Trajectory Optimization

Trajectory optimization for robotic systems remains a challenging problem. This is especially true for robotic systems featuring nonlinear dynamics and many degrees of freedom. Data-based or model-free diffusion has recently been popularized in the fields of artificial intelligence and trajectory optimization. Model-Based Diffusion provides a data-free method of trajectory optimization, trained at runtime on a system dynamics model, suitable for high-dimensional models. This paper examines how importance sampling can enhance the performance of Model-Based Diffusion for trajectory optimization. Here, we quantify the benefits of importance sampling across three long horizon planning tasks. These results show as much as a 13x improvement in sample efficiency depending on environment and optimization parameters.

Golembeski, Seth [Georgia Institute of Technology,↗

DOE OSTI2015

An Elegant Sufficiency: Load-Aware Differentiated Scheduling of Data Transfers

We investigate the file transfer scheduling problem, where transfers among different endpoints must be scheduled to maximize pertinent metrics. We propose two new algorithms that exploit the fact that the aggregate bandwidth obtained over a network or at a storage system tends to increase with the number of concurrent transfers—but only up to a certain limit. The first algorithm, SEAL, uses runtime information and data-driven models to approximate system load and adapt transfer schedules and concurrency so as to maximize performance while avoiding saturation. We implement this algorithm using GridFTP as the transfer protocol and evaluate it using real transfer logs in a production WAN environment. Results show that SEAL can improve average slowdowns and turnaround times by up to 25% and worst-case slowdown and turnaround times by up to 50%, compared with the best-performing baseline scheme. Our second algorithm, STEAL, further leverages user-supplied categorization of transfers as either “interactive” (requiring immediate processing) or “batch” (less time-critical). Results show that STEAL reduces the average slowdown of interactive transfers by 63% compared to the best-performing baseline and by 21% compared to SEAL. For batch transfers, compared to the best-performing baseline, STEAL improves by 18% the utilization of the bandwidth unused by interactive transfers. By elegantly ensuring a sufficient, but not excessive, allocation of concurrency to the right transfers, we significantly improve overall performance despite constraints.

Kettimuthu, Rajkumar↗