Distributed shared abstractions (DSA) on multiprocessors

Clémençon, Christian; Mukherjee, Bodhisattwa; Schwan, Karsten

doi:10.1109/32.485223

Cited by 11 publications

(3 citation statements)

References 31 publications

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“…As a result, the performance of mutex locks differs across both machines, but the interface and functionality provided to application programmers does not change. The portability of Cthreads programs to non-shared memory machines is outside the scope of this paper (see [24,25,21] for our own contributions to this topic). However, to take advantage of distributed memory machines available at Georgia Tech, our group has performed an explicit port of TRANS to the IBM SP-2 parallel supercomputer.…”

Section: Implementation Characteristicsmentioning

confidence: 99%

A parallel spectral model for atmospheric transport processes

Kindler

Schwan

Silva

et al. 1996

Concurrency: Pract. Exper.

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The paper describes a parallel implementation of a grand challenge problem: global atmospheric modeling. The novel contributions of our work include (1) a detailed investigation of opportunities for parallelism in atmospheric global modeling based on spectral solution methods, (2) the experimental evaluation of overheads arising from load imbalances and data movement for alternative parallelization methods, and (3) the development of a parallel code that can be monitored and steered interactively based on output data visualizations and animations of program functionality or performance. Code parallelization takes advantage of the relative independence of computations at different levels in the earth's atmosphere, resulting in parallelism of up to 40 processors, each independently performing computations for different atmospheric levels and requiring few communications between different levels across model time steps. Next, additional parallelism is attained within each level by taking advantage of the natural parallelism offered by the spectral computations being performed (e.g. taking advantage of independently computable terms in equations). Performance measurements are performed on a 64‐node KSR2 supercomputer. However, the parallel code has been ported to several shared memory parallel machines, including SGI multiprocessors, and has also been ported to distributed memory platforms like the IBM SP‐2.

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Section: Implementation Characteristicsmentioning

confidence: 99%

A parallel spectral model for atmospheric transport processes

Kindler

Schwan

Silva

et al. 1996

Concurrency: Pract. Exper.

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“…Distributed Shared Abstractions (DSAs) [1] demonstrate the scalable and high performance on shared memory multiprocessors, using weak data consistency. Parallel Abstract Data Types [2] describe commonly used computational patterns in science and engineering applications.…”

Section: Shared Abstract Data Typesmentioning

confidence: 99%

“…A key characteristic for scalable performance was to use weakened data consistency [1]. Sequential consistency can provide a global priority ordering on the PriQueue elements, but typically through the use of a serialising lock.…”

Section: A Performance Analysis Of the Travelling Salesman Problemmentioning

confidence: 99%

Using SADTs to support irregular computational problems

Nash

Dew

Berzins

Proceedings Fourth International Symposium on Parallel Architectures, Algorithms, and Networks (I-Span'99)

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There are well defined methods for supporting regular problems with scalable performance, typified by the HPF language and the BSP model. Less well understood is the solution of more irregular problems, supporting complex shared data structures and task dependencies, and typically requiring dynamic load balancing to sustain high performance. It is demonstrated how the use of Shared Abstract Data Types (SADTs), together with an extended BSP cost model, can support irregular problems in a structured manner. An SADT is an extension of a serial ADT which allows the concurrent invocation of its methods. A number of SADTs are used to implement a solution of the travelling salesman problem on the Cray T3D machine, and a description of the restructuring of a parallel CFD code using SADTs is provided, with initial results given for the Cray T3E.

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