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Published November 1998 | Published
Book Section - Chapter Open

An Initial Evaluation of the Tera Multithreaded Architecture and Programming System Using the C3I Parallel Benchmark Suite

Abstract

The Tera Multithreaded Architecture (MTA) is a radical new architecture intended to revolutionize high-performance computing in both the scientific and commercial marketplaces. Each processor supports 128 threads in hardware. Extremely fast thread switching is used to mask latency in a uniform-access memory system without caching. It is claimed that these hardware characteristics allow compilers to easily transform sequential programs into efficient multithreaded programs for the Tera MTA. In this paper, we attempt to provide an objective initial evaluation of the performance of the Tera multithreaded architecture and programming system for general-purpose applications. The basis of our investigation is two programs from the C3I Parallel Benchmark Suite (C3IPBS). Both these programs have previously been shown to have the potential for large-scale parallelization. We compare the performance of these programs on (i) a fast uniprocessor, (ii) two conventional shared-memory multiprocessors, and (iii) the first installed Tera MTA (at the San Diego Supercomputer Center). On these platforms, we compare the effectiveness of both automatic and manual parallelization.

Additional Information

© 1998 IEEE. Thanks to Gail Alverson, John Feo, Kristi Maschhoff, and Allan Porterfield at Tera Computer Company and Wayne Pfeiffer at San Diego Supercomputer Center for their help developing these programs and their comments on this paper. Particular thanks to John Feo for developing the fine-grained solution to the Terrain Masking problem for the Tera MTA. Thanks to Sean Suchter in the Computer Science Department at Caltech for investigating and explaining the Tera MTA to us in the early stages of this work. Thanks to Eric Bogs and Jason Roth in the Computer Science Department at Caltech for developing the Sthreads solutions to the Threat Analysis and Terrain Masking problems on the Pentium Pro platform. Thanks also to our other colleagues in the Computer Science Department and Center for Advanced Computing Research at Caltech for their support of this work. This research was supported by DARPA grant DABT63-97-C-0028, Air Force Office of Scientific Research grant AFOSR-91-0070, and the NSF Center for Research on Parallel Computation (CRPC) under Cooperative Agreement No. CCR-912008.

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