SEARCH · Engineering Papers

Results for “distributed parallelization”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,189 records · Page 66

All sources NASA NTRS DOE OSTI

NASA NTRS1993

Blasim: A computational tool to assess ice impact damage on engine blades

A portable computer called BLASIM was developed at NASA LeRC to assess ice impact damage on aircraft engine blades. In addition to ice impact analyses, the code also contains static, dynamic, resonance margin, and supersonic flutter analysis capabilities. Solid, hollow, superhybrid, and composite blades are supported. An optional preprocessor (input generator) was also developed to interactively generate input for BLASIM. The blade geometry can be defined using a series of airfoils at discrete input stations or by a finite element grid. The code employs a coarse, fixed finite element mesh containing triangular plate finite elements to minimize program execution time. Ice piece is modeled using an equivalent spherical objective that has a high velocity opposite that of the aircraft and parallel to the engine axis. For local impact damage assessment, the impact load is considered as a distributed force acting over a region around the impact point. The average radial strain of the finite elements along the leading edge is used as a measure of the local damage. To estimate damage at the blade root, the impact is treated as an impulse and a combined stress failure criteria is employed. Parametric studies of local and root ice impact damage, and post-impact dynamics are discussed for solid and composite blades.

Reddy, E. S.↗

NASA NTRS1994

On bottleneck partitioning k-ary n-cubes

Graph partitioning is a topic of extensive interest, with applications to parallel processing. In this context graph nodes typically represent computation, and edges represent communication. One seeks to distribute the workload by partitioning the graph so that every processor has approximately the same workload, and the communication cost (measured as a function of edges exposed by the partition) is minimized. Measures of partition quality vary; in this paper we consider a processor's cost to be the sum of its computation and communication costs, and consider the cost of a partition to be the bottleneck, or maximal processor cost induced by the partition. For a general graph the problem of finding an optimal partitioning is intractable. In this paper we restrict our attention to the class of k-art n-cube graphs with uniformly weighted nodes. Given mild restrictions on the node weight and number of processors, we identify partitions yielding the smallest bottleneck. We also demonstrate by example that some restrictions are necessary for the partitions we identify to be optimal. In particular, there exist cases where partitions that evenly partition nodes need not be optimal.

Nicol, David M.↗

NASA NTRS1995

Ensuring correct rollback recovery in distributed shared memory systems

Distributed shared memory (DSM) implemented on a cluster of workstations is an increasingly attractive platform for executing parallel scientific applications. Checkpointing and rollback techniques can be used in such a system to allow the computation to progress in spite of the temporary failure of one or more processing nodes. This paper presents the design of an independent checkpointing method for DSM that takes advantage of DSM's specific properties to reduce error-free and rollback overhead. The scheme reduces the dependencies that need to be considered for correct rollback to those resulting from transfers of pages. Furthermore, in-transit messages can be recovered without the use of logging. We extend the scheme to a DSM implementation using lazy release consistency, where the frequency of dependencies is further reduced.

Janssens, Bob↗

NASA NTRS1999

HPF Implementation of ARC3D

We present an HPF (High Performance Fortran) implementation of ARC3D code along with the profiling and performance data on SGI Origin 2000. Advantages and limitations of HPF as a parallel programming language for CFD applications are discussed. For achieving good performance results we used the data distributions optimized for implementation of implicit and explicit operators of the solver and boundary conditions. We compare the results with MPI and directive based implementations.

Frumkin, Michael↗

DOE OSTI2023

Toward local core outlet temperature monitoring in gas-cooled nuclear reactors using distributed fiber-optic temperature sensors

Gas-cooled nuclear reactors operate at temperatures up to 950 °C with significant spatial variations in power generation and coolant flow through hundreds of parallel flow channels, resulting in complex mixing at the core outlet. The high temperatures and complex mixing can damage downstream components, challenge reactor calorimetry for power determination, and result in significant conservatism in calculated peak fuel temperatures, which ultimately limits the total power output. Directly measuring each gas stream individually is unrealistic using single point thermocouples, requiring more robust sensing techniques. Fiber-optic sensors are resilient to high temperatures (up to 1,000 °C) and radiation damage. Moreover, distributed measurements can be made along the length of one fiber, making them potential candidates for monitoring local core outlet temperatures to improve core calorimetry and identify hot channels. Here, to the authors’ knowledge, this manuscript is the first to report spatially distributed fiber optic temperature measurements to quantify mixing at the outlet of a relevant orifice plate under prototypic temperature and flow regimes to assess the feasibility of using fiber-optic sensors for distributed measurements of coolant temperature in gas-cooled reactors. A single optical fiber captured dynamic changes in local temperatures, whereas the mixed outlet temperature exhibited a muted response and could not identify which channels were responsible for the change in the mixed outlet temperature. The discussion focuses on potential challenges for deploying distributed optical fibers in gas-cooled reactors, including the effects of vibrations, radiation-induced signal attenuation and drift, and routing of the fiber while minimizing flow obstructions.

42 ENGINEERING↗

NASA NTRS1996

An Evaluation of Architectural Platforms for Parallel Navier-Stokes Computations

We study the computational, communication, and scalability characteristics of a computational fluid dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architecture platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and distributed memory multiprocessors with different topologies - the IBM SP and the Cray T3D. We investigate the impact of various networks connecting the cluster of workstations on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.

Jayasimha, D. N.↗

NASA NTRS2004

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Jost, Gabriele↗

NASA NTRS1994

Statistical study of ULF wave occurrence in the dayside magnetosphere

Ultralow-frequency (ULF) waves are observed almost everywhere in the dayside magnetosphere. The mechanism by which these waves are generated and transformed in the dayside magnetosphere is still not understood. Here we report a statistical study of these waves based on magnetic field data from the International Sun-Earth Explorer 1 (ISEE 1) spacecraft. Data from the first traversal of the spacecraft through the entire dayside magnetosphere have been examined to determine the spatial distribution of wave occurrence. Successive 20-min segments of data were transformed to a field-aligned coordinate system. The parallel component was detrended and all three components of the field spectrally analyzed. Wave occurrence was defined by the presence of significant peaks in the power spectra. Wave events were categorized by three wave frequency bands: Pc 3 with T approximately 10-45 s; Pc 4 with T approximately 45-150 s; the short-period part of the Pc 5 wave band with T approximately 150-324 s. Properties of the spectral peaks were then entered into a data base. The data base was next sorted to determine the spatial occurrence pattern for the waves. Our results show that Pc 3 waves most frequently occur just outside synchronous orbit and are approximately centered on local noon. Pc 4 waves have a similar distribution with its peak further out. Pc 5 waves have high occurrence rate at the two flanks of the magnetosphere. Peaks in spectra obtained near the magnetopause are less clearly defined than those deeper in the magnetosphere.

Cao, M.↗

NASA NTRS1975

Operational performance of a low cost, air mass 2 solar simulator

The present work describes briefly the design, construction, and operation of a low cost air mass 2 solar simulator, and then presents the performance characteristics of a modified version in terms of total irradiance, uniformity of irradiance, spectral distribution, and beam subtense angle. The simulator consists of an array of 143 tungsten halogen lamps and a corresponding array of 143 Fresnel lenses parallel and in front of the lenses, so that a 1.2 m by 1.2 m area is irradiated with uniform collimated irradiance. The performance of this 143-lamp version is compared with that of the 12-lamp prototype. It was found that the larger design required a lower lamp voltage for an equivalent average total irradiance in the test plane. However, distribution of total irradiance was not as good for the large simulator.

Yass, K.↗

DOE OSTI2022

Real-time and post-hoc compression for data from Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) is an emerging sensing technology that records the strain-rate along fiber optic cables at high spatial and temporal resolution. This technique is becoming a popular tool in seismology, hydrology, and other subsurface monitoring applications. However, due to the large coverage (10’s of km) and high density of measurements (1m spacing at 100’s of Hz), a DAS installation could produce terabytes of data records per day. Because many DAS instruments are deployed in remote locations, this large data size poses significant challenges to its transfer and storage. In this paper, we explore lossless compression methods to reduce the storage requirement in both real-time and post-hoc scenarios. Here we propose a two-stage compression method to improve the compression ratio and compression speed. This two-stage compression method could reduce the storage requirement by 40%, which is 20% more than other lossless methods, such as ZSTD. We demonstrate that the compression method could complete its operation well before the DAS instrument needs to output the next file, making it suitable for real-time DAS acquisition. We also implement a parallel compression method for a post-hoc scenario and demonstrate that our method could effectively utilize a parallel computer. With 256 CPU cores, our parallel compression method achieves the speed of 26GB/second.

58 GEOSCIENCES↗

DOE OSTI2024

FuseIM: Fusing Probabilistic Traversals for Influence Maximization on Exascale Systems

Probabilistic breadth-first traversals (BPTs) are used in many network science and graph machine learning applications. In this paper, we are motivated by the application of BPTs in stochastic diffusion-based graph problems such as influence maximization. These applications heavily rely on BPTs to implement a Monte-Carlo sampling step for their approximations. Given the large sampling complexity, stochasticity of the diffusion process, and the inherent irregularity in real-world graph topologies, efficiently parallelizing these BPTs remains significantly challenging. In this paper, we present a new algorithm to fuse massive number of concurrently executing BPTs with random starts on the input graph. Our algorithm is designed to fuse BPTs by combining separate traversals into a unified frontier on distributed multi-GPU systems. To show the general applicability of the fused BPT technique, we have incorporated it into two state-of-the-art influence maximization parallel implementations (gIM and Ripples). Our experiments on up to 4K nodes of the OLCF Frontier supercomputer (32,768 GPUs and 196K CPU cores) show strong scaling behavior, and that fused BPTs can improve the performance of these implementations up to 34x (for gIM) and ~360x (for Ripples).

Neff, Reece W.↗

NASA NTRS1993

Particle simulation on heterogeneous distributed supercomputers

We describe the implementation and performance of a three dimensional particle simulation distributed between a Thinking Machines CM-2 and a Cray Y-MP. These are connected by a combination of two high-speed networks: a high-performance parallel interface (HIPPI) and an optical network (UltraNet). This is the first application to use this configuration at NASA Ames Research Center. We describe our experience implementing and using the application and report the results of several timing measurements. We show that the distribution of applications across disparate supercomputing platforms is feasible and has reasonable performance. In addition, several practical aspects of the computing environment are discussed.

Becker, Jeffrey C.↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

Edge computing↗

DOE OSTI2022

Toward designing effective exascale scientific computing workflows: experiences and best practices

Many fields within scientific computing have embraced advances in big-data analysis and machine learning, which often requires the deployment of large, distributed and complicated workflows that may combine training neural networks, performing simulations, running inference, and performing database queries and data analysis in asynchronous, parallel and pipelined execution frameworks. Such a shift has brought into focus the need for scalable, efficient workflow management solutions with reproducibility, error and provenance handling, traceability, and checkpoint-restart capabilities, among other needs. Here, we discuss challenges and best-practices for deploying exascale-generation computational science workflows on resources at the Oak Ridge Leadership Computing Facility (OLCF). We present our experiences with large-scale deployment of distributed workflows on the Summit supercomputer, including for bioinformatics and computational biophysics, materials science, and deep learning model optimization. We also present problems and solutions created by working within a Python-centric software base on traditional HPC systems, and discuss steps that will be required before the convergence of HPC, AI, and data science can be fully realized. Our results point to a wealth of exciting new possibilities for harnessing this convergence to tackle new scientific challenges.

Coletti, Mark↗

NASA NTRS1994

Effect of hexylene glycol-altered microtubule distributions on cytokinesis and polar lobe formation in fertilized eggs of Ilyanassa obsoleta

Some effects of gravity on early morphogenesis are correlated with microtubule locations within cells. During first cleavage in Ilyanassa obsoleta embryos, a transitory polar lobe constriction forms and then relaxes, allowing the polar lobe to merge with one daughter cell. If the polar lobe is equally divided or removed, morphogenesis is severely disrupted. To examine microtuble locations during early Ilyanassa development, eggs were fixed and stained for polymerized alpha-tubulin during first cleavage. The mitotic apparatus assembles at the animal pole. The cleavage furrow forms between the asters, constricting to a stabilized intercellular bridge encircling midbody-bound microtubules, whereas the polar lobe constriction forms below and parallel to the spindle, constricting to a transitory intercellular bridge encircling no detectable microtubules. At metaphase an alpha-tubulin epitope is distributed throughout the spindle, whereas a beta-tubulin epitope is present predominantly in the asters. Incubation in hexylene glycol, a drug that increases microtubule polymerization, during mitosis causes the polar lobe constriction to tighten around polymerized alpha-tubulin and remain stably constricted. If hexylene glycol is removed, alpha-tubulin staining disappears from the polar lobe constriction, which relaxes, whereas microtubules remain in the cleavage furrow, which remains constricted. These observations suggest that asymmetric distribution of microtubules affects early Ilyanassa cleavage patterns, and that continued presence of microtubules extending through an intercellular bridge is important for stabilization of the bridge constriction prior to completion of cytokinesis. These data provide the basis for further analysis of the role of microtubules in possible microgravity disruptions of Ilyanassa development.

NASA Discipline Cell Biology↗

NASA NTRS1985

Moving target, distributed, real-time simulation using Ada

Research on a precompiler solution is described for the moving target compiler problem encountered when trying to run parallel simulation algorithms on several microcomputers. The precompiler is under development at NASA-Lewis for simulating jet engines. Since the behavior of any component of a jet engine, e.g., the fan inlet, rear duct, forward sensor, etc., depends on the previous behaviors and not the current behaviors of other components, the behaviors can be modeled on different processors provided the outputs of the processors reach other processors in appropriate time intervals. The simulator works in compute and transfer modes. The Ada procedure sets for the behaviors of different components are divided up and routed by the precompiler, which essentially receives a multitasking program. The subroutines are synchronized after each computation cycle.

Collins, W. R.↗

NASA NTRS1990

Highly parallel sparse Cholesky factorization

Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms.

Gilbert, John R.↗