Search NASA⌕ Search

SEARCH · Search NASA

Results for “Parallel Process Execution”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Heterogeneous graphics processing unit for scheduling thread groups for execution on variable width SIMD units

A compute unit configured to execute multiple threads in parallel is presented. The compute unit includes one or more single instruction multiple data (SIMD) units and a fetch and decode logic. The SIMD units have differing numbers of arithmetic logic units (ALUs), such that each SIMD unit can execute a different number of threads. The fetch and decode logic is in communication with each of the SIMD units, and is configured to assign the threads to the SIMD units for execution based on such differing numbers of ALUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The LISE package: solvers for static and time-dependent superfluid local density approximation equations in three dimensions

Nuclear implementation of the density functional theory (DFT) is at present the only microscopic framework applicable to the whole nuclear landscape. The extension of DFT to superfluid systems in the spirit of the Kohn-Sham approach, the superfluid local density approximation (SLDA) and its extension to time-dependent situations, time-dependent superfluid local density ap- proximation (TDSLDA), have been extensively used to describe various static and dynamical problems in nuclear physics, neutron star crust, and cold atom systems. In this paper, we present the codes that solve the static and time-dependent SLDA equations in three-dimensional coordinate space without any symmetry restriction. These codes are fully parallelized with the message passing interface (MPI) library and take advantage of graphic processing units (GPU) for accelerating execution. The dynamic codes have checkpoint/restart capabilities and for initial conditions one can use any generalized Slater determinant type of wave function. The code can describe a large number of physical problems: nuclear fission, collisions of heavy ions, the interaction of quantized vor- tices with nuclei in the nuclear star crust, excitation of superfluid fermion systems by time dependent external fields, quantum shock waves, domain wall generation and propagation, the dynamics of the Anderson-Bogoliubov-Higgs mode, dynamics of fragmented condensates, vortex rings dynamics, generation and dynamics of quantized vortices, their crossing and recombinations and the incipient phases of quantum turbulence.

Jin, Shi↗
NASA NTRS1991

Planning and Resource Management in an Intelligent Automated Power Management System

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

Morris, Robert A.↗
DOE OSTI2021

ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing

The next generation HPC and data centers are likely to be reconfigurable and data-centric due to the trend of hardware specialization and the emergence of data-driven applications. In this work, we propose ARENA – an asynchronous reconfigurable accelerator ring architecture as a potential scenario on how the future HPC and data centers will be like. Despite using the coarse-grained reconfigurable arrays (CGRAs) as the substrate platform, our key contribution is not only the CGRA-cluster design itself, but also the ensemble of a new architecture and programming model that enables asynchronous tasking across a cluster of reconfigurable nodes, so as to bring specialized computation to the data rather than the reverse. We presume distributed data storage without asserting any prior knowledge on the data distribution. Hardware specialization occurs at runtime when a task finds the majority of data it requires are available at the present node. In other words, we dynamically generate specialized CGRA accelerators where the data reside. The asynchronous tasking for bringing computation to data is achieved by circulating the task token, which describes the dataflow graphs to be executed for a task, among the CGRA cluster connected by a fast ring network. Evaluations on a set of HPC and data-driven applications across different domains show that ARENA can provide better parallel scalability with reduced data movement (53.9 percent). Compared with contemporary compute-centric parallel models, ARENA can bring on average 4.37× speedup. The synthesized CGRAs and their task-dispatchers only occupy 2.93mm 2 chip area under 45nm process technology and can run at 800MHz with on average 759.8mW power consumption. ARENA also supports the concurrent execution of multi-applications, offering ideal architectural support for future high-performance parallel computing and data analytics systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Initial operating capability for the hypercluster parallel-processing test bed

The NASA Lewis Research Center is investigating the benefits of parallel processing to applications in computational fluid and structural mechanics. To aid this investigation, NASA Lewis is developing the Hypercluster, a multi-architecture, parallel-processing test bed. The initial operating capability (IOC) being developed for the Hypercluster is described. The IOC will provide a user with a programming/operating environment that is interactive, responsive, and easy to use. The IOC effort includes the development of the Hypercluster Operating System (HYCLOPS). HYCLOPS runs in conjunction with a vendor-supplied disk operating system on a Front-End Processor (FEP) to provide interactive, run-time operations such as program loading, execution, memory editing, and data retrieval. Run-time libraries, that augment the FEP FORTRAN libraries, are being developed to support parallel and vector processing on the Hypercluster. Special utilities are being provided to enable passage of information about application programs and their mapping to the operating system. Communications between the FEP and the Hypercluster are being handled by dedicated processors, each running a Message-Passing Kernel, (MPK). A shared-memory interface allows rapid data exchange between HYCLOPS and the communications processors. Input/output handlers are built into the HYCLOPS-MPK interface, eliminating the need for the user to supply separate I/O support programs on the FEP.

Cole, Gary L.↗
DOE OSTI2024

Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel

GNU Parallel is a versatile and powerful tool for process parallelization widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, particularly focusing on its scalability and efficiency in executing large-scale high-throughput high-performance computing (HT-HPC) workflows. Through real-world examples, we highlight GNU Parallel’s performance across various HPC workloads, including GPU computing, container-based workloads, and node-local NVMe storage. Our results on two leading supercomputers, OLCF’s Frontier and NERSC’s Perlmutter, showcase GNU Parallel’s rapid process dispatching ability and its capacity to maintain low overhead even at extreme scales. We explore GNU Parallel’s application in massive parallel file transfers using a scheduled Data Transfer Node (DTN) cluster, emphasizing its broad utility in diverse scientific workflows. Beyond its direct application as a viable workflow manager, GNU Parallel can be employed in conjunction with other workflow systems as a "last-mile" parallelizing driver and as a quick prototyping tool to design and extract parallel profiles from application executions. We then argue that the potential for GNU Parallel to transform workflow management at extreme scales is substantial, paving the way for more efficient and effective scientific discoveries.

Maheshwari, Ketan↗
NASA NTRS1989

The FORCE - A highly portable parallel programming language

This paper explains why the FORCE parallel programming language is easily portable among six different shared-memory multiprocessors, and how a two-level macro preprocessor makes it possible to hide low-level machine dependencies and to build machine-independent high-level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared-memory multiprocessor executing them.

Jordan, Harry F.↗
NASA NTRS1988

Problems in characterizing barrier performance

The barrier is a synchronization construct which is useful in separating a parallel program into parallel sections which are executed in sequence. The completion of a barrier requires cooperation among all executing processes. This requirement not only introduces the wait for the slowest process delay which is inherent in the definition of the synchronization, but also has implications for the efficient implementation and measurement of barrier performance in different systems. Types of barrier implementation and their relationship to different multiprocessor environments are described. Then the problem of measuring the performance of barrier implementations on specific machine architecture is discussed. The fact that the barrier synchronization requires the cooperation of all processes makes the problem of performance measurement similarly global. Making non-intrusive measurements of sufficient accuracy can be tricky on systems offering only rudimentary measurement tools.

Jordan, Harry F.↗
NASA NTRS2004

MER SPICE Interface

MER SPICE Interface is a software module for use in conjunction with the Mars Exploration Rover (MER) mission and the SPICE software system of the Navigation and Ancillary Information Facility (NAIF) at NASA's Jet Propulsion Laboratory. (SPICE is used to acquire, record, and disseminate engineering, navigational, and other ancillary data describing circumstances under which data were acquired by spaceborne scientific instruments.) Given a Spacecraft Clock value, MER SPICE Interface extracts MER-specific data from SPICE kernels (essentially, raw data files) and calculates values for Planet Day Number, Local Solar Longitude, Local Solar Elevation, Local Solar Azimuth, and Local Solar Time (UTC). MER SPICE Interface was adapted from a subroutine, denoted m98SpiceIF written by Payam Zamani, that was intended to calculate SPICE values for the Mars Polar Lander. The main difference between MER SPICE Interface and m98SpiceIf is that MER SPICE Interface does not explicitly call CHRONOS, a time-conversion program that is part of a library of utility subprograms within SPICE. Instead, MER SPICE Interface mimics some portions of the CHRONOS code, the advantage being that it executes much faster and can efficiently be called from a pipeline of events in a parallel processing environment.

Sayfi, Elias↗
NASA NTRSDate not supplied

Spectral Proper Orthogonal Decomposition of uPSP Measurements in Recent NASA Ames Wind Tunnel Test

This paper discusses Spectral Proper Orthogonal Decomposition (SPOD) of the Unsteady Pressure-Sensitive Paint (uPSP) measurements in recent NASA Ames wind tunnel test. The uPSP measurements were collected using Innovative Scientific Solutions, Inc. (ISSI) porous, fast-response pressure-sensitive paint, 40 ISSI four-inch air-cooled Light-Emitting Diodes, and 8 Phantom v2512 high-speed cameras at 10,000 frames per second in the uPSP Launch Vehicle Demonstration Test (LVDT) of the Space Launch System (SLS) vehicle in the 11-by 11-foot transonic test section of the Unitary Plan Wind Tunnel at NASA Ames Research Center in April 2024. SPOD is derived from a space-time proper orthogonal decomposition problem for statistically stationary flows. SPOD modes are determined in the frequency domain. Each SPOD mode oscillates at a single frequency. SPOD can be viewed as an extension of the Discrete Fourier Transform composition and the Dynamic Mode Decomposition. In this paper, the outputs of SPOD of the uPSP measurements in the uPSP LVDT are presented and the effectiveness of SPOD in the identification, diagnosis and analysis of the aerodynamic and aeroacoustic phenomena is demonstrated. The unsteady and dynamic property of the pressure field on the surface of the SLS Block 1B crew vehicle is presented with the visualization of the SPOD modes of the uPSP measurements in the tests of a Mach sweep run of the uPSP LVDT. The SPOD outputs were generated with the execution in parallel of a code in Python, with the library of Message Passing Interface for parallel processing, on the NASA Pleiades supercomputer. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities Portfolio Office.

Aeroacoustics↗
DOE OSTI2020

ECP ST Capability Assessment Report (CAR) for VTK-m (FY20)

The ECP/VTK-m project is providing the core capabilities to perform scientific visualization on Exascale architectures. The ECP/VTK-m project fills the critical feature gap of performing visualization and analysis on processors like graphics-based processors. The results of this project will be delivered in tools like ParaView, Vislt, and Ascent as well as in stand-alone form. Moreover, these projects are depending on this ECP effort to be able to make effective use of ECP architectures. One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyper threading and vector operations require even more parallel processing to leverage each core's full potential. VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures. The ECP/VTK-m project is building up the VTK-m codebase with the necessary visualization algorithm implementations that run across the varied hardware platforms to be leveraged at the Exascale. We will be working with other ECP projects, such as ALPINE, to integrate the new VTK-m code into production software to enable visualization on our HPC systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

MLP: A Parallel Programming Alternative to MPI for New Shared Memory Parallel Systems

Recent developments at the NASA AMES Research Center's NAS Division have demonstrated that the new generation of NUMA based Symmetric Multi-Processing systems (SMPs), such as the Silicon Graphics Origin 2000, can successfully execute legacy vector oriented CFD production codes at sustained rates far exceeding processing rates possible on dedicated 16 CPU Cray C90 systems. This high level of performance is achieved via shared memory based Multi-Level Parallelism (MLP). This programming approach, developed at NAS and outlined below, is distinct from the message passing paradigm of MPI. It offers parallelism at both the fine and coarse grained level, with communication latencies that are approximately 50-100 times lower than typical MPI implementations on the same platform. Such latency reductions offer the promise of performance scaling to very large CPU counts. The method draws on, but is also distinct from, the newly defined OpenMP specification, which uses compiler directives to support a limited subset of multi-level parallel operations. The NAS MLP method is general, and applicable to a large class of NASA CFD codes.

Taft, James R.↗
DOE OSTI2020

A Sparse Tensor Benchmark Suite for CPUs and GPUs

Tensor computations present significant performance chal- lenges that impact a wide spectrum of applications ranging from machine learning, healthcare analytics, social network analysis, data mining to quantum chemistry and signal processing. Efforts to improve the perfor- mance of tensor computations include exploring data layout, execution scheduling, and parallelism in common tensor kernels. This work presents a benchmark suite for arbitrary-order sparse tensor kernels using state- of-the-art tensor formats: coordinate (COO) and hierarchical coordinate (HiCOO) on CPUs and GPUs. It presents a set of reference tensor kernel implementations that are compatible with real-world tensors and power law tensors extended from synthetic graph generation techniques. We also propose Roofline performance models for these kernels to provide insights of computer platforms from sparse tensor view. This benchmark suite along with the synthetic tensor generator is publicly available.

Li, Jiajia↗
NASA NTRS1994

Task scheduling in dataflow computer architectures

Dataflow computers provide a platform for the solution of a large class of computational problems, which includes digital signal processing and image processing. Many typical applications are represented by a set of tasks which can be repetitively executed in parallel as specified by an associated dataflow graph. Research in this area aims to model these architectures, develop scheduling procedures, and predict the transient and steady state performance. Researchers at NASA have created a model and developed associated software tools which are capable of analyzing a dataflow graph and predicting its runtime performance under various resource and timing constraints. These models and tools were extended and used in this work. Experiments using these tools revealed certain properties of such graphs that require further study. Specifically, the transient behavior at the beginning of the execution of a graph can have a significant effect on the steady state performance. Transformation and retiming of the application algorithm and its initial conditions can produce a different transient behavior and consequently different steady state performance. The effect of such transformations on the resource requirements or under resource constraints requires extensive study. Task scheduling to obtain maximum performance (based on user-defined criteria), or to satisfy a set of resource constraints, can also be significantly affected by a transformation of the application algorithm. Since task scheduling is performed by heuristic algorithms, further research is needed to determine if new scheduling heuristics can be developed that can exploit such transformations. This work has provided the initial development for further long-term research efforts. A simulation tool was completed to provide insight into the transient and steady state execution of a dataflow graph. A set of scheduling algorithms was completed which can operate in conjunction with the modeling and performance tools previously developed. Initial studies on the performance of these algorithms were done to examine the effects of application algorithm transformations as measured by such quantities as number of processors, time between outputs, time between input and output, communication time, and memory size.

Katsinis, Constantine↗
NASA NTRS1987

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Carroll, Chester C.↗
DOE OSTI2024

Data-flow parallelism for high-energy and nuclear physics frameworks

The processing tasks of an event-processing workflow in high-energy and nuclear physics (HENP) can typically be represented as a directed acyclic graph formed according to the data flow—i.e. the data dependencies among algorithms executed as part of the workflow. With this representation, an HENP framework can optimally execute a workflow, exploiting the parallelism inherent among independent tasks. Despite such a natural description of a workflow, most HENP frameworks do not make use of technologies that provide concurrent execution of graph-based tasking structures. In this talk, we describe Fermilab efforts to adopt a graph-based technology (specifically Intel’s oneTBB flow graph) for meeting the framework needs of its experiments, notably DUNE. Building on the Meld project as presented at CHEP2023, we demonstrate that all common processing idioms supported by current frameworks can naturally be supported by oneTBB’s data-flow technology, optimally leveraging the concurrent capabilities of the machine. In addition, we discuss collaborative efforts between Fermilab and the Intel oneTBB development team, who is considering improvements to the flow-graph technology to better support HENP use cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2000

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

Ecer, A.↗
DOE OSTI2024

Data-flow parallelism for high-energy and nuclear physics computing frameworks

The processing tasks of a scientific workflow in high-energy and nuclear physics (HENP) can typically be represented as a directed acyclic graph formed according to the data flow—i.e. the data dependencies among algorithms executed as part of the workflow. With this representation, an HENP computing framework can optimally execute a workflow, exploiting the parallelism inherent among independent tasks. Despite such a natural description of a workflow, most HENP frameworks do not make use of technologies that provide concurrent execution of graph-based tasking structures. In this session, we describe Fermilab efforts to adopt a graph-based technology (specifically Intel’s oneTBB flow graph) for meeting the framework needs of its experiments, notably DUNE. After introducing the physics DUNE intends to explore, we will show that all common processing idioms supported by current HENP frameworks can naturally be supported by oneTBB’s data-flow technology, optimally leveraging the concurrent capabilities of the machine. In addition, we discuss collaborative efforts between Fermilab and the Intel oneTBB development team, who is considering improvements to the flow-graph technology to better support HENP use cases.

43 PARTICLE ACCELERATORS↗