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Loop parallelism on Tera MTA using SISAL

Conference ·
OSTI ID:224967

The difficulty of programming parallel computers has impeded their wide-spread use. The problems are caused by existing hardware and software tools. The software problems on shared-memory and vector computers can be solved by using deterministic high-performance functional languages like SISAL. Distributed-memory computers have even more obstacles than shared-memory parallel machines. Research indicates that multithreaded architectures can hide long latency of distributed memories and that they can solve the problems of locality. Tera`s MTA multiprocessor is based on the concept of multithreading and provides the programmer with a real shared-memory model. This paper investigates the performance of parallel loops written in SISAL and executed on the Tera MTA using the Livermore Loops benchmarks.

Research Organization:
Lawrence Livermore National Lab., CA (United States)
Sponsoring Organization:
USDOE, Washington, DC (United States)
DOE Contract Number:
W-7405-ENG-48
OSTI ID:
224967
Report Number(s):
UCRL-JC--122696; CONF-9511199--1; ON: DE96006767
Country of Publication:
United States
Language:
English

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