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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

PaRSEC: A Software Framework for Performance and Productivity on Hybrid, Manycore Platforms

As the era of computer architectures dominated by serial processors ends, the convergence of several unprecedented challenges suggests that closing the longstanding "application–architecture performance gap" will become more challenging than ever. To address this problem, the Parallel Runtime Scheduling and Execution Control (PaRSEC) project created a modular software framework that achieved two major objectives: first, it built a task-based runtime capable of delivering portable performance to a wide range of science and engineering applications at all levels of the platform pyramid, including the upcoming 100 Pflop/s systems and then exascale; and second, it supported and facilitated the work of developers in migrating their legacy codes and writing entirely new ones for the emerging hybrid and massively parallel manycore processor system designs. PaRSEC will support multiple domain-specific languages capable of increasing the developers' productivity while also providing the runtime with the constructs and flexibility necessary to exploit the maximal parallelism from parallel applications. Extensive preliminary research in dense linear algebra showed convincingly that a parameterized task graph representation that symbolically describes the algorithm content can achieve the project's twofold objective within that domain. The research also strongly suggested that this powerful method could be generalized to a far-wider variety of applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Swarm Verification

Reportedly, supercomputer designer Seymour Cray once said that he would sooner use two strong oxen to plow a field than a thousand chickens. Although this is undoubtedly wise when it comes to plowing a field, it is not so clear for other types of tasks. Model checking problems are of the proverbial "search the needle in a haystack" type. Such problems can often be parallelized easily. Alas, none of the usual divide and conquer methods can be used to parallelize the working of a model checker. Given that it has become easier than ever to gain access to large numbers of computers to perform even routine tasks it is becoming more and more attractive to find alternate ways to use these resources to speed up model checking tasks. This paper describes one such method, called swarm verification.

grid computing↗
DOE OSTI2016

Distributed Halide

Many image processing tasks are naturally expressed as a pipeline of small computational kernels known as stencils. Halide is a popular domain-specific language and compiler designed to implement image processing algorithms. Halide uses simple language constructs to express what to compute and a separate scheduling co-language for expressing when and where to perform the computation. This approach has demonstrated performance comparable to or better than hand-optimized code. Until now, however, Halide has been restricted to parallel shared memory execution, limiting its performance for memory-bandwidth-bound pipelines or large-scale image processing tasks. We present an extension to Halide to support distributed-memory parallel execution of complex stencil pipelines. These extensions compose with the existing scheduling constructs in Halide, allowing expression of complex computation and communication strategies. Existing Halide applications can be distributed with minimal changes, allowing programmers to explore the tradeoff between recomputation and communication with little effort. Approximately 10 new of lines code are needed even for a 200 line, 99 stage application. On nine image processing benchmarks, our extensions give up to a 1.4× speedup on a single node over regular multithreaded execution with the same number of cores, by mitigating the effects of non-uniform memory access. The distributed benchmarks achieve up to 18× speedup on a 16 node testing machine and up to 57× speedup on 64 nodes of the NERSC Cori supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Data-parallel Python for High Energy Physics Analyses

In this paper, we explore features available in Python which are useful for data reduction tasks in High Energy Physics (HEP). Highlevel abstractions in Python are convenient for implementing data reduction tasks. However, in order for such abstractions to be practical, the efficiency of their performance must also be high. Because the data sets we process are typically large, we care about both I/O performance and in-memory processing speed. In particular, we evaluate the use of data-parallel programming, using MPI and numpy, to process a large experimental data set (42 TiB) stored in an HDF5 file. We measure the speed of processing of the data, distinguishing between the time spent reading data and the time spent processing the data in memory, and demonstrate the scalability of both, using up to 1200 KNL nodes (76800 cores) on Cori at NERSC

Paterno, Marc↗
DOE OSTI2017

Partial differential equations preconditioner resilient to soft and hard faults

We present a domain-decomposition-based preconditioner for the solution of partial differential equations (PDEs) that is resilient to both soft and hard faults. The algorithm reformulates the PDE as a sampling problem, followed by a solution update through data manipulation that is resilient to both soft and hard faults. This reformulation allows us to recast the problem as a set of independent tasks, and exploit data locality to reduce global communication. We discuss two different parallel implementations: (a) a single program multiple data (SPMD) version based on a one-to-one mapping between subdomain and MPI processes responsible for both state and computation; and (b) an asynchronous server–client implementation where all state information is held by the servers and clients are designed solely as computational units. We present a scalability comparison of both implementations under nominal conditions, showing efficiency within ~80% for up to 12,000 cores. We present a resilience analysis under different fault scenarios based on the server–client implementation. This framework provides resiliency to hard faults such that if a client crashes, it stops asking for work, and the servers simply distribute the work among all of the other clients alive. Erroneous subdomain solves (e.g. due to soft faults) appear as corrupted data, which is either rejected if that causes a task to fail, or is seamlessly filtered out during the regression stage through a suitable noise model. Three different types of faults are modeled: hard faults modeling nodes (or clients) crashing; soft faults occurring during the communication of the tasks between server and clients; and soft faults occurring during task execution. We demonstrate the resiliency of the approach for a 2D elliptic PDE, and explore the effect of the faults at various failure rates.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Fast synchronization-free algorithms for parallel sparse triangular solves with multiple right-hand sides

The sparse triangular solve kernels, SpTRSV and SpTRSM, are important building blocks for a number of numerical linear algebra routines. Parallelizing SpTRSV and SpTRSM on today's many-core platforms, such as GPUs, is not an easy task since computing a component of the solution may depend on previously computed components, enforcing a degree of sequential processing. As a consequence, most existing work introduces a preprocessing stage to partition the components into a group of level-sets or colour-sets so that components within a set are independent and can be processed simultaneously during the subsequent solution stage. However, this class of methods requires a long preprocessing time as well as significant runtime synchronization over-heads between the sets. To address this, we

HPC↗
DOE OSTI2017

ISAVS: Interactive Scalable Analysis and Visualization System

Modern science is inundated with ever increasing data sizes as computational capabilities and image acquisition techniques continue to improve. For example, simulations are tackling ever larger domains with higher fidelity, and high-throughput microscopy techniques generate larger data that are fundamental to gather biologically and medically relevant insights. As the image sizes exceed memory, and even sometimes local disk space, each step in a scientific workflow is impacted. Current software solutions enable data exploration with limited interactivity for visualization and analytic tasks. Furthermore analysis on HPC systems often require complex hand-written parallel implementations of algorithms that suffer from poor portability and maintainability. We present a software infrastructure that simplifies end-to-end visualization and analysis of massive data. First, a hierarchical streaming data access layer enables interactive exploration of remote data, with fast data fetching to test analytics on subsets of the data. Second, a library simplifies the process of developing new analytics algorithms, allowing users to rapidly prototype new approaches and deploy them in an HPC setting. Third, a scalable runtime system automates mapping analysis algorithms to whatever computational hardware is available, reducing the complexity of developing scaling algorithms. Here, we demonstrate the usability and performance of our system using a use case from neuroscience: filtering, registration, and visualization of tera-scale microscopy data. We evaluate the performance of our system using a leadership-class supercomputer, Shaheen II.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Development of a flight software testing methodology

The research to develop a testing methodology for flight software is described. An experiment was conducted in using assertions to dynamically test digital flight control software. The experiment showed that 87% of typical errors introduced into the program would be detected by assertions. Detailed analysis of the test data showed that the number of assertions needed to detect those errors could be reduced to a minimal set. The analysis also revealed that the most effective assertions tested program parameters that provided greater indirect (collateral) testing of other parameters. In addition, a prototype watchdog task system was built to evaluate the effectiveness of executing assertions in parallel by using the multitasking features of Ada.

Mccluskey, E. J.↗
NASA NTRS1990

Evaluation and selection of assembly plans

Two criteria are introduced for the evaluation and selection of assembly plans. The first criterion is to maximize the number of different sequences encompassed by the assembly plan. The second criterion is to maximize the amount of parallelism (i.e., simultaneity) that is possible in the execution of the assembly tasks. While the metrics corresponding to the criteria used in previous work can be expressed as a sum of terms, each being a function of a task or a state, the metrics corresponding to the criteria introduced are more complex functions of the whole assembly plan. An algorithm that performs a heuristic search for the best assembly plan over the AND/OR graph representation of assembly plans introduced in previous work is presented. Admissible heuristics for each of the two criteria are presented.

Homem De Mello, L. S.↗
NASA NTRS1991

Pulmonary function in microgravity: KC-135 experience

We have commenced a KC-135 program that parallels and proceeds our Spacelab (SLS-1) pulmonary function experiment. Our first task was to elucidate the affect of normal gravitation on the shape of the maximum expiratory flow volume (MEFV) curve. Nine normal subjects performed multiple MEFV maneuvers at 0-G, 1-G, and approximately 1.7-G. The MEFV curves for each subject were filtered, aligned at RV, and ensemble-averaged to produce an average MEFV curve for each state, allowing differences to be studied. Most subjects showed a decrease in the FVC at 0-G, which we attribute to an increased intrathoracic blood volume. In most of these subjects, the mean lung volume associated with a given flow was lower at 0-G, over about the upper half of the vital capacity. This is similar to the change previously reported during heat out immersion and is consistent with the known affect of engorgement of the lung with blood, on elastic recoil. There were also consistent but highly individual changes in the position and magnitude of detailed features of the curve, the individual patterns being similar to those previously reported on transition from the erect to the supine position. This supports the idea that the location and motion of choke points which determine the detailed individual configuration of MEFV curves, can be significantly influenced by gravitational forces, presumably via the effects of change in longitudinal tension on local airway pressure-diameter behavior and wave speed. We have developed a flight mass spectrometer and have commenced a study of single breath gradients in gas exchange, inert gas washouts, and rebreathing cardiac outputs and lung volumes at 0-G, 1-G, and 1.7-G. Comparison of our results with those from SLS-1 should identify the opportunities and limitations of the KC-135 as an accessible microgravity resource.

Guy, Harold J.↗
NASA NTRS2015

2nd Generation QUATARA Flight Computer Project

Single core flight computer boards have been designed, developed, and tested (DD&T) to be flown in small satellites for the last few years. In this project, a prototype flight computer will be designed as a distributed multi-core system containing four microprocessors running code in parallel. This flight computer will be capable of performing multiple computationally intensive tasks such as processing digital and/or analog data, controlling actuator systems, managing cameras, operating robotic manipulators and transmitting/receiving from/to a ground station. In addition, this flight computer will be designed to be fault tolerant by creating both a robust physical hardware connection and by using a software voting scheme to determine the processor's performance. This voting scheme will leverage on the work done for the Space Launch System (SLS) flight software. The prototype flight computer will be constructed with Commercial Off-The-Shelf (COTS) components which are estimated to survive for two years in a low-Earth orbit.

Falker, Jay↗
DOE OSTI2023

Towards Lightweight Data Integration Using Multi-Workflow Provenance and Data Observability

Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a crucial role in scientific discovery, especially in the current AI era, by enabling Responsible AI development, FAIR, Reproducibility, and User Steering. However, the heterogeneous nature of science poses challenges such as dealing with multiple supporting tools, cross-facility environments, and efficient HPC execution. Building on data observability, adapter system design, and provenance, we propose MIDA: an approach for lightweight runtime Multi-workflow Integrated Data Analysis. MIDA defines data observability strategies and adaptability methods for various parallel systems and machine learning tools. With observability, it intercepts the dataflows in the background without requiring instrumentation while integrating domain, provenance, and telemetry data at runtime into a unified database ready for user steering queries. We conduct experiments showing end-to-end multi-workflow analysis integrating data from Dask and MLFlow in a real distributed deep learning use case for materials science that runs on multiple environments with up to 276 GPUs in parallel. We show near-zero overhead running up to 100,000 tasks on 1,680 CPU cores on the Summit supercomputer.

Santos Souza, Renan↗
DOE OSTI2017

Real-time supervisory control implementation of SmAHTR power plant - 143

This paper discusses an implementation of a supervisory control system for a nuclear power plant model using Small modular Advanced High Temperature Reactors (SmAHTR). The simulation operates in real-time using a network of computer agents, implemented on Raspberry Pi's (RPi's), where each major task is performed by one or more RPi's running calculations in parallel. The system architecture contains local, module, master, and operator actions to automate all aspects of the plant. Local level controllers run individual control loops to ensure the desired reference signals are met. The module level controllers set the local level reference signals within each SMR unit and detect sensor and actuator failures to adjust those reference signals as needed. Master level controllers balance plant power by calculating required heat power from each reactor and electric power from each generator and sending that data to the module controllers. Finally, the operator level contains an operator interface to summarize data and faults gathered through the controller levels, with options to review plant and reactor details as desired. This control implementation allows the plant to run autonomously, load follow a desired electrical power curve, and detect a growing number of fault scenarios. Ultimately, this type of supervisory control system will reduce labor-intensive surveillance and testing and allow fewer operators to more safely monitor an entire plant. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Optimization and Augmentation for Data Parallel Contour Trees

Contour trees are used for topological data analysis in scientific visualization. While originally computed with serial algorithms, recent work has introduced a vector-parallel algorithm. Furthermore, this algorithm is relatively slow for fully augmented contour trees which are needed for many practical data analysis tasks. We therefore introduce a representation called the hyperstructure that enables efficient searches through the contour tree and use it to construct a fully augmented contour tree in data parallel, with performance on average 6 times faster than the state-of-the-art parallel algorithm in the TTK topological toolkit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Science & Technology - Other Topics↗
NASA NTRS1996

Parallel Simulation of Unsteady Turbulent Flames

Time-accurate simulation of turbulent flames in high Reynolds number flows is a challenging task since both fluid dynamics and combustion must be modeled accurately. To numerically simulate this phenomenon, very large computer resources (both time and memory) are required. Although current vector supercomputers are capable of providing adequate resources for simulations of this nature, the high cost and their limited availability, makes practical use of such machines less than satisfactory. At the same time, the explicit time integration algorithms used in unsteady flow simulations often possess a very high degree of parallelism, making them very amenable to efficient implementation on large-scale parallel computers. Under these circumstances, distributed memory parallel computers offer an excellent near-term solution for greatly increased computational speed and memory, at a cost that may render the unsteady simulations of the type discussed above more feasible and affordable.This paper discusses the study of unsteady turbulent flames using a simulation algorithm that is capable of retaining high parallel efficiency on distributed memory parallel architectures. Numerical studies are carried out using large-eddy simulation (LES). In LES, the scales larger than the grid are computed using a time- and space-accurate scheme, while the unresolved small scales are modeled using eddy viscosity based subgrid models. This is acceptable for the moment/energy closure since the small scales primarily provide a dissipative mechanism for the energy transferred from the large scales. However, for combustion to occur, the species must first undergo mixing at the small scales and then come into molecular contact. Therefore, global models cannot be used. Recently, a new model for turbulent combustion was developed, in which the combustion is modeled, within the subgrid (small-scales) using a methodology that simulates the mixing and the molecular transport and the chemical kinetics within each LES grid cell. Finite-rate kinetics can be included without any closure and this approach actually provides a means to predict the turbulent rates and the turbulent flame speed. The subgrid combustion model requires resolution of the local time scales associated with small-scale mixing, molecular diffusion and chemical kinetics and, therefore, within each grid cell, a significant amount of computations must be carried out before the large-scale (LES resolved) effects are incorporated. Therefore, this approach is uniquely suited for parallel processing and has been implemented on various systems such as: Intel Paragon, IBM SP-2, Cray T3D and SGI Power Challenge (PC) using the system independent Message Passing Interface (MPI) compiler. In this paper, timing data on these machines is reported along with some characteristic results.

Menon, Suresh↗
DOE OSTI2016

X: A Comprehensive Analytic Model for Parallel Machines

To continuously comply with Moore’s Law, modern parallel machines become increasingly complex. Effectively tuning application performance for these machines therefore becomes a daunting task. Moreover, identifying performance bottlenecks at application and architecture level, as well as evaluating various optimization strategies, are becoming extremely difficult when the entanglement of numerous correlated factors is being presented. To tackle these challenges, we present a visual analytical model named “X”. It is intuitive and sufficiently flexible to track all the typical features of a parallel machine.

Modeling and Performance Analysis↗
NASA NTRS1989

A real time, FEM based optimal control algorithm and its implementation using parallel processing hardware (transistors) in a microprocessor environment

There is an evident need to discover a means of establishing reliable, implementable controls for systems that are plagued by nonlinear and, or uncertain, model dynamics. The development of a generic controller design tool for tough-to-control systems is reported. The method utilizes a moving grid, time infinite element based solution of the necessary conditions that describe an optimal controller for a system. The technique produces a discrete feedback controller. Real time laboratory experiments are now being conducted to demonstrate the viability of the method. The algorithm that results is being implemented in a microprocessor environment. Critical computational tasks are accomplished using a low cost, on-board, multiprocessor (INMOS T800 Transputers) and parallel processing. Progress to date validates the methodology presented. Applications of the technique to the control of highly flexible robotic appendages are suggested.

Patten, William Neff↗