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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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All sources NASA NTRS DOE OSTI

DOE OSTI2025

VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics

VerifyIO is a tool designed for verifying I/O consistency semantics in High-Performance Computing (HPC) applications. It addresses the challenges of ensuring correctness and portability across different I/O consistency models, such as POSIX, Commit, Session, and MPI-IO. By analyzing execution traces, detecting conflicts, and verifying synchronization adherence, VerifyIO provides actionable insights for both application developers and I/O library designers.

Wang, Chen [Lawrence Livermore National Laboratory↗

DOE OSTI2024

VerifyIO: Ensuring Correctness of Consistency Semantics in Parallel I/O

Abstract—High-performance computing (HPC) applications generate and consume substantial amounts of data, typically managed by parallel file systems. These applications access file systems either through the POSIX interface or by using highlevel I/O libraries. While the POSIX consistency model remains dominant in HPC, emerging file systems and popular I/O libraries increasingly adopt alternative consistency models that relax semantics in various ways, creating significant challenges for correctness and portability. This paper addresses these challenges by proposing a trace-driven I/O consistency verification workflow, implemented in our open-source tool, VerifyIO, which collects execution traces, detects data conflicts, and verifies proper synchronization against specified consistency models. Our extensive evaluation of 91 test case executions across three widely used I/O libraries with four I/O consistency models reveals critical consistency issues at both application and implementation levels.

Consistency Semantics↗

DOE OSTI2025

Recorder trace files of 91 built-in tests from three widely-used I/O libraries (Dec 24, 2024)

This dataset contains the Recorder trace files of 91 built-in tests from three widely-used I/O libraries. It was utilized in our IPDPS'25 paper, "VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics". The dataset can be used to reproduce the results presented in the paper and to conduct additional analyses

Wang, Chen [Lawrence Livermore National Laboratory↗

NASA NTRS1990

Prefetching in file systems for MIMD multiprocessors

The question of whether prefetching blocks on the file into the block cache can effectively reduce overall execution time of a parallel computation, even under favorable assumptions, is considered. Experiments have been conducted with an interleaved file system testbed on the Butterfly Plus multiprocessor. Results of these experiments suggest that (1) the hit ratio, the accepted measure in traditional caching studies, may not be an adequate measure of performance when the workload consists of parallel computations and parallel file access patterns, (2) caching with prefetching can significantly improve the hit ratio and the average time to perform an I/O (input/output) operation, and (3) an improvement in overall execution time has been observed in most cases. In spite of these gains, prefetching sometimes results in increased execution times (a negative result, given the optimistic nature of the study). The authors explore why it is not trivial to translate savings on individual I/O requests into consistently better overall performance and identify the key problems that need to be addressed in order to improve the potential of prefetching techniques in the environment.

Kotz, David F.↗

DOE OSTI2024

Formal Definitions and Performance Comparison of Consistency Models for Parallel File Systems

The semantics of HPC storage systems are defined by the consistency models to which they abide. Storage consistency models have been less studied than their counterparts in memory systems, with the exception of the POSIX standard and its strict consistency model. The use of POSIX consistency imposes a performance penalty that becomes more significant as the scale of parallel file systems increases and the access time to storage devices, such as node-local solid storage devices, decreases. While some efforts have been made to adopt relaxed storage consistency models, these models are often defined informally and ambiguously as by-products of a particular implementation. Here in this work, we establish a connection between memory consistency models and storage consistency models and revisit the key design choices of storage consistency models from a high-level perspective. Further, we propose a formal and unified framework for defining storage consistency models and a layered implementation that can be used to easily evaluate their relative performance for different I/O workloads. Finally, we conduct a comprehensive performance comparison of two relaxed consistency models on a range of commonly seen parallel I/O workloads, such as checkpoint/restart of scientific applications and random reads of deep learning applications. We demonstrate that for certain I/O scenarios, a weaker consistency model can significantly improve the I/O performance. For instance, in small random reads that are typically found in deep learning applications, session consistency achieved a 5x improvement in I/O bandwidth compared to commit consistency, even at small scales.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Defining and satisfying the computing requirements of the EOS scientific computing facilities at NASA/MSFC

The computing requirements of the individual scientific computing facilities (SCFs) have been evaluated. The requirements under consideration include CPU-intensive vector and scalar processing, visualization, data storage, connectivity, and I/O peripherals. A hierarchy consisting of shared and individual resources is proposed to most effectively meet the total SCF computing requirements. This hierarchy includes a supercomputer class vector processor; a high-end scalar multiprocessor workstation; a high-speed, large capacity file server; a few medium to high-end visualization workstations; and low to medium range personal graphics workstations.

Botts, Michael E.↗

NASA NTRS1991

A user-oriented synthetic workload generator

A user oriented synthetic workload generator that simulates users' file access behavior based on real workload characterization is described. The model for this workload generator is user oriented and job specific, represents file I/O operations at the system call level, allows general distributions for the usage measures, and assumes independence in the file I/O operation stream. The workload generator consists of three parts which handle specification of distributions, creation of an initial file system, and selection and execution of file I/O operations. Experiments on SUN NFS are shown to demonstrate the usage of the workload generator.

Kao, Wei-Lun↗

DOE OSTI2025

Optimizing Management of Persistent Data Structures in High-Performance Analytics

Large-scale data analytics workflows ingest massive input data into various data structures, including graphs and key-value datastores. These data structures undergo multiple transformations and computations and are typically reused in incremental and iterative analytics workflows. Persisting in-memory views of these data structures enables reusing them beyond the scope of a single program run while avoiding repetitive raw data ingestion overheads. Memory-mapped I/O enables persisting in-memory data structures without data serialization and deserialization overheads. However, memory-mapped I/O lacks the key feature of persisting consistent snapshots of these data structures for incremental ingestion and processing. The obstacles to efficient virtual memory snapshots using memory-mapped I/O include background writebacks outside the application’s control, and the significantly high storage footprint of such snapshots. To address these limitations, we present Privateer, a memory and storage management tool that enables storage-efficient virtual memory snapshotting while also optimizing snapshot I/O performance. Here, we integrated Privateer into Metall, a state-of-the-art persistent memory allocator for C++, and the Lightning Memory-Mapped Database (LMDB), a widely-used key-value datastore in data analytics and machine learning. Privateer optimized application performance by 1.22× when storing data structure snapshots to node-local storage, and up to 16.7× when storing snapshots to a parallel file system. Privateer also optimizes storage efficiency of incremental data structure snapshots by up to 11× using data deduplication and compression.

Computer science↗

NASA NTRS1975

Low cost computer subsystem for the Solar Electric Propulsion Stage (SEPS)

The Solar Electric Propulsion Stage (SEPS) subsystem which consists of the computer, custom input/output (I/O) unit, and tape recorder for mass storage of telemetry data was studied. Computer software and interface requirements were developed along with computer and I/O unit design parameters. Redundancy implementation was emphasized. Reliability analysis was performed for the complete command computer sybsystem. A SEPS fault tolerant memory breadboard was constructed and its operation demonstrated.

Source record↗

NASA NTRS2010

High-Intensity Radiated Field Fault-Injection Experiment for a Fault-Tolerant Distributed Communication System

Safety-critical distributed flight control systems require robustness in the presence of faults. In general, these systems consist of a number of input/output (I/O) and computation nodes interacting through a fault-tolerant data communication system. The communication system transfers sensor data and control commands and can handle most faults under typical operating conditions. However, the performance of the closed-loop system can be adversely affected as a result of operating in harsh environments. In particular, High-Intensity Radiated Field (HIRF) environments have the potential to cause random fault manifestations in individual avionic components and to generate simultaneous system-wide communication faults that overwhelm existing fault management mechanisms. This paper presents the design of an experiment conducted at the NASA Langley Research Center's HIRF Laboratory to statistically characterize the faults that a HIRF environment can trigger on a single node of a distributed flight control system.

Yates, Amy M.↗

NASA NTRS1997

Virtual Instrument Simulator for CERES

A benchtop virtual instrument simulator for CERES (Clouds and the Earth's Radiant Energy System) has been built at NASA, Langley Research Center in Hampton, VA. The CERES instruments will fly on several earth orbiting platforms notably NASDA's Tropical Rainfall Measurement Mission (TRMM) and NASA's Earth Observing System (EOS) satellites. CERES measures top of the atmosphere radiative fluxes using microprocessor controlled scanning radiometers. The CERES Virtual Instrument Simulator consists of electronic circuitry identical to the flight unit's twin microprocessors and telemetry interface to the supporting spacecraft electronics and two personal computers (PC) connected to the I/O ports that control azimuth and elevation gimbals. Software consists of the unmodified TRW developed Flight Code and Ground Support Software which serves as the instrument monitor and NASA/TRW developed engineering models of the scanners. The CERES Instrument Simulator will serve as a testbed for testing of custom instrument commands intended to solve in-flight anomalies of the instruments which could arise during the CERES mission. One of the supporting computers supports the telemetry display which monitors the simulator microprocessors during the development and testing of custom instrument commands. The CERES engineering development software models have been modified to provide a virtual instrument running on a second supporting computer linked in real time to the instrument flight microprocessor control ports. The CERES Instrument Simulator will be used to verify memory uploads by the CERES Flight Operations TEAM at NASA. Plots of the virtual scanner models match the actual instrument scan plots. A high speed logic analyzer has been used to track the performance of the flight microprocessor. The concept of using an identical but non-flight qualified microprocessor and electronics ensemble linked to a virtual instrument with identical system software affords a relatively inexpensive simulation system capable of high fidelity.

Chapman, John J.↗

DOE OSTI2025

Preliminary Study on Fine-Grained Power and Energy Measurements on Grace Hopper GH200 with Open-Source Performance Tools

The increasing adoption of tightly integrated, heterogeneous architectures, combined with the slowdown of Moore’s law, has made application power and energy-driven optimizations critical to efficiently use high-performance computing systems. This paper introduces a newly developed open-source toolkit that seamlessly integrates the Linux real-time hardware monitoring program hwmon with the Performance Application Programming Interface and the Score-P performance measurement system, thereby enabling fine-grained power and energy measurements for high-performance computing applications. Our primary target platform is the Wombat test bed, which is a system based on the NVIDIA GH200 superchip. The toolkit can capture transient power peaks with high temporal resolution (50 ms) and, thanks to Score-P integration, can map power metrics to specific code regions, thereby providing actionable information on power-intensive operations and inefficiencies. The toolkit also provides a holistic view of both the power and the energy consumption of the entire GH200 superchip by covering all major components: the Grace CPU, the Hopper GPU, and the I/O subsystem. Experiments that use Locally Self-consistent Multiple Scattering, which is an application for first-principles calculations of materials developed at Oak Ridge National Laboratory, have demonstrated the tool’s ability to identify transient power spikes and uncover opportunities for energy-aware optimizations. Additionally, we introduce a Python-based utility for converting Open Trace Format 2 traces to Parquet format, thus enabling advanced data analysis for numerical integration methods applied to power data for accurate energy profiling.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗

DOE OSTI2021

Battle of the Defaults: Extracting Performance Characteristics of HDF5 under Production Load

Popular parallel I/O libraries, such as HDF5, provide tuning parameters to obtain superior performance. However, the selection of effective parameters on production systems is complex due to the interdependence of I/O software and file system layers. Hence, application developers typically use the default parameters and often experience poor I/O performance. This work conducts a benchmarking-based analysis on the HDF5 behaviors with a wide variety of I/O patterns to extract performance characteristics under the production workload. To make the analysis well controlled, we exercise I/O benchmarks on POSIX-IO, MPI-IO, and HDF5 using the same I/O patterns and in the same jobs. To address high performance variability in production environments, we repeat the benchmarks across I/O patterns, storage devices, and time intervals. Based on the results, we identified consistent HDF5 behaviors that appropriate configurations and operations on dataset layout and file-metadata placement can improve performance significantly. We apply our findings and evaluate the tuned I/O library on two supercomputers: Summit and Cori. The results show that our tuned parameters can achieve more than 10× I/O performance speedup than that with default parameters on both systems, suggesting the effectiveness, stability, and generality of our solution.

Xie, Bing↗

NASA NTRS1980

Single-chip microcomputer application in high-altitude balloon orientation system

This paper describes the application of a single-chip microcomputer in a high-altitude balloon instrumentation system. The system, consisting of a magnetometer, a stepping motor, a microcomputer and a gray code shaft encoder, is used to provide an orientation reference to point a scientific instrument at an object in space. The single-chip microcomputer, Intel's 8748, consisting of a CPU, program memory, data memory and I/O ports, is used to control the orientation of the system.

Lim, T. S.↗

NASA NTRS2002

SIDS-toADF File Mapping Manual

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The SIDS-toADF File Mapping Manual specifies the exact manner in which, under CGNS conventions, CFD data structures (the SIDS) are to be stored in (i.e., mapped onto) the file structure provided by the database manager (ADF). The result is a conforming CGNS database. Adherence to the mapping conventions guarantees uniform meaning and location of CFD data within ADF files, and thereby allows the construction of universal software to read and write the data.

McCarthy, Douglas↗

NASA NTRS1998

CGNS Mid-Level Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: - The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; - The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; - The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and - The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The CGNS Mid-level Library was designed to ease the implementation of CGNS by providing developers with a collection of handy I/O functions. Since knowledge of the ADF core is not required to use this library, it will greatly facilitate the task of interfacing with CGNS. There are currently 48 user callable functions that comprise the Mid-level library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Poirier, Diane↗

DOE OSTI2023

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems

Monitoring and analyzing a wide range of I/O activities in an HPC cluster is important in maintaining mission-critical performance in a large-scale, multi-user, parallel storage system. Center-wide I/O traces can provide high-level information and fine-grained activities per application or per user running in the system. Studying such large-scale traces can provide helpful insights into the system. It can be used to develop predictive methods for making predictive decisions, adjusting scheduling policies, or providing decisions for the design of next-generation systems. However, sharing real-world I/O traces to expedite such research efforts leaves a few concerns; i) the cost of sharing the large traces is expensive due to this large size, and ii) privacy concern is an issue.We address such issues by building an end-to-end machine learn- ing (ML) workflow that can generate I/O traces for large-scale HPC applications. We leverage ML based feature selection and gener- ative models for I/O trace generation. The generative models are trained on I/O traces collected by the darshan I/O characterization tool over a period of one year. We present a two-step generation process consisting of two deep-learning models, called the feature generator and the trace generator. The combination of two-step generative models provides robustness by reducing the bias of the model and accounting for the stochastic nature of the I/O traces across different runs of an application. We evaluate the performance of the generative models and show that the two-step model can generate time-series I/O traces with less than 20% root mean square error.

Paul, Arnab↗