Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 10 of 10
Full-Text Articles in Physical Sciences and Mathematics
Benchmarks And Standards For The Evaluation Of Parallel Job Schedulers, Steve J. Chapin, Walfredo Cirne, Dror G. Feitelson, James Patton Jones
Benchmarks And Standards For The Evaluation Of Parallel Job Schedulers, Steve J. Chapin, Walfredo Cirne, Dror G. Feitelson, James Patton Jones
Electrical Engineering and Computer Science - All Scholarship
The evaluation of parallel job schedulers hinges on the workloads used. It is suggested that this be standardized, in terms of both format and content, so as to ease the evaluation and comparison of different systems. The question remains whether this can encompass both traditional parallel systems and metacomputing systems. This paper is based on a panel on this subject that was held at the workshop, and the ensuing discussion; its authors are both the panel members and participants from the audience. Naturally, not all of us agree with all the opinions expressed here...
A Matrix-Based Approach To Global Locality Optimization, Mahmut Kandemir, Alok Choudhary, J. Ramanujam, Prith Banerjee
A Matrix-Based Approach To Global Locality Optimization, Mahmut Kandemir, Alok Choudhary, J. Ramanujam, Prith Banerjee
Electrical Engineering and Computer Science - All Scholarship
Global locality optimization is a technique for improving the cache performance of a sequence of loop nests through a combination of loop and data layout transformations. Pure loop transformations are restricted by data dependences and may not be very successful in optimizing imperfectly nested loops and explicitly parallelized programs. Although pure data transformations are not constrained by data dependences, the impact of a data transformation on an array might be program-wide; that is, it can affect all the references to that array in all the loop nests. Therefore, in this paper we argue for an integrated approach that employs both …
Random Number Generators For Parallel Computers, Paul D. Coddington
Random Number Generators For Parallel Computers, Paul D. Coddington
Northeast Parallel Architecture Center
Random number generators are used in many applications, from slot machines to simulations of nuclear reactors. For many computational science applications, such as Monte Carlo simulation, it is crucial that the generators have good randomness properties. This is particularly true for large-scale simulations done on high-performance parallel computers. Good random number generators are hard to find, and many widely-used techniques have been shown to be inadequate. Finding high-quality, efficient algorithms for random number generation on parallel computers is even more difficult. Here we present a review of the most commonly-used random number generators for parallel computers, and evaluate each generator …
Array Decompositions For Nonuniform Computational Environments, Maher Kaddoura, Sanjay Ranka, Albert Wang
Array Decompositions For Nonuniform Computational Environments, Maher Kaddoura, Sanjay Ranka, Albert Wang
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
Two-dimensional arrays are useful in a large variety of scientific and engineering applications. Parallelization of these applications requires the decomposition of array elements among different machines. Several data-decomposition techniques have been studied in the literature for machines with uniform computational power. In this paper we develop new methods for decomposing arrays into a cluster of machines with nonuniform computational power. Simulation results show that our methods provide superior decomposition over naive schemes.
Parallel Remapping Algorithms For Adaptive Problems, Chao Wei Ou, Sanjay Ranka
Parallel Remapping Algorithms For Adaptive Problems, Chao Wei Ou, Sanjay Ranka
Northeast Parallel Architecture Center
In this paper we present fast parallel algorithms for remapping a class of irregular and adaptive problems on coarse-grained distributed memory machines. We show that the remapping of these applications, using simple index-based mapping algorithm, can be reduced to sorting a nearly sorted list of integers or merging an unsorted list of integers with a sorted list of integers. By using the algorithms we have developed, the remapping of these problems can be achieved at a fraction of the cost of mapping from scratch. Experimental results are presented on the CM-5.
Parallel Incremental Graph Partitioning Using Linear Programming, Chao Wei Ou, Sanjay Ranka
Parallel Incremental Graph Partitioning Using Linear Programming, Chao Wei Ou, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
Partitioning graphs into equally large groups of nodes while minimizing the number of edges between different groups is an extremely important problem in parallel computing. For instance, efficiently parallelizing several scientific and engineering applications requires the partitioning of data or tasks among processors such that the computational load on each node is roughly the same, while communication is minimized. Obtaining exact solutions is computationally intractable, since graph-partitioning is an NP-complete. For a large class of irregular and adaptive data parallel applications (such as adaptive meshes), the computational structure changes from one phase to another in an incremental fashion. In incremental …
A Compilation Approach For Fortran 90d/Hpf Compilers On Distributed Memory Mimd Computers, Zeki Bozkus, Alok Choudhary, Geoffrey C. Fox, Tomasz Haupt
A Compilation Approach For Fortran 90d/Hpf Compilers On Distributed Memory Mimd Computers, Zeki Bozkus, Alok Choudhary, Geoffrey C. Fox, Tomasz Haupt
Northeast Parallel Architecture Center
This paper describes a compilation approach for a Fortran 90D/HPF compiler, a source-to-source parallel compiler for distributed memory systems. Different from Fortran 77 parallelizing compilers, a Fortran90D/HPF compiler does not parallelize sequential constructs. Only parallelism expressed by Fortran 90D/HPF parallel constructs is exploited. The methodology of parallelizing Fortran programs such as computation partitioning, communication detection and generation, and the run-time support for the compiler are discussed. An example of Gaussian Elimination is used to illustrate the compilation techniques with performance results.
Integrating Multiple Programming Paradigms On Connection Machine Cm5 In A Dataflow-Based Software Environment, Gang Cheng, Geoffrey C. Fox, Kim Mills
Integrating Multiple Programming Paradigms On Connection Machine Cm5 In A Dataflow-Based Software Environment, Gang Cheng, Geoffrey C. Fox, Kim Mills
Northeast Parallel Architecture Center
By viewing different parallel programming paradigms as essential heterogeneous approaches in mapping "real-world" problems to parallel systems, we discuss methodologies in integrating multiple programming models on a Connection Machine CM5. In a data flow based integration model built in a visualization software AVS, we demonstrate a simple, effective and modular way to couple sequential, data-parallel and explicit message-passing modules into an integrated programming environment on the CM5.
Parti Primitives For Unstructured And Block Structured Problems, Alan Sussman, Joel Saltz, Raja Das, S. Gupta, Dimitri Mavriplis, Ravi Ponnusamy
Parti Primitives For Unstructured And Block Structured Problems, Alan Sussman, Joel Saltz, Raja Das, S. Gupta, Dimitri Mavriplis, Ravi Ponnusamy
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
This paper describes a set of primitives (PARTI) developed to efficiently execute unstructured and block structured problems on distributed memory parallel machines. We present experimental data from a 3-D unstructured Euler solver run on the Intel Touchstone Delta to demonstrate the usefulness of our methods.
Which Applications Can Use High Performance Fortran And Fortran-D: Industry Standard Data Parallel Languages?, Alok Choudhary, Geoffrey C. Fox, Tomasz Haupt, S. Ranka
Which Applications Can Use High Performance Fortran And Fortran-D: Industry Standard Data Parallel Languages?, Alok Choudhary, Geoffrey C. Fox, Tomasz Haupt, S. Ranka
Northeast Parallel Architecture Center
In this paper, we present the first, preliminary results of HPF/Fortran-D language analysis based on compiling and running benchmark applications using a prototype implementation of HPF/Fortran-D compiler. The analysis indicate that the HPF is a very convenient tool for programming many applications on massively parallel and/or distributed systems. In addition, we cumulate experience on how to parallelize irregular problems to extend the scope of Fortran-D beyond HPF and suggest future extensions to the Fortran standard.