Title :
Improving massively data parallel system performance with heterogeneity
Author :
Noh, Sam H. ; Dussa-Zieger, Klaudia
Author_Institution :
Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA
Abstract :
The authors introduce a new type of combined SIMD/MIMD (single-instruction multiple-data/multiple-instruction multiple-data) architecture called a hybrid system. The hybrid system consists of two components. The first component is massively parallel and consists of a large number of slow processors that are organized in an SIMD architecture. The second component consists of only a few fast processors (possibly only one) which are organized in an MIMD architecture. The authors contend that a hybrid system provides a means to adequately adjust to the characteristics of a parallel program, i.e., changing parallelism. They describe the machine and application model, and discuss the performance impact of such a system. Viewing the CM-2 with its front-end as a special case of a hybrid system, they substantiate the arguments and report measurements for a Gaussian elimination algorithm
Keywords :
parallel architectures; performance evaluation; CM-2; Gaussian elimination algorithm; SIMD/MIMD architecture; heterogeneity; hybrid system; massively data parallel system performance; parallel program; Computer architecture; Computer science; Concurrent computing; Distributed computing; Educational institutions; Parallel algorithms; Parallel processing; Performance analysis; System performance; Time measurement;
Conference_Titel :
Frontiers of Massively Parallel Computation, 1992., Fourth Symposium on the
Conference_Location :
McLean, VA
Print_ISBN :
0-8186-2772-7
DOI :
10.1109/FMPC.1992.234901