An empirical comparison of the Kendall Square Research KSR-1 and Stanford DASH multiprocessors

• Published in: Proceedings of the 1993 ACM/IEEE conference on Supercomputing pp. 214 - 225
• Main Authors: Singh, J. P., Joe, T., Hennessy, J. L., Gupta, A.
• Format: Conference Proceeding
• Language: English
• Published: New York, NY, USA ACM 01.12.1993; IEEE
• Series: ACM Conferences
• Subjects: Applied computing > Physical sciences and engineering > Earth and atmospheric sciences; Computer architecture; Computer science; Computer systems organization > Architectures > Distributed architectures > Grid computing; Computer systems organization > Architectures > Parallel architectures; Computer systems organization > Architectures > Parallel architectures > Multicore architectures; Computer systems organization > Architectures > Serial architectures > Superscalar architectures; Computing methodologies > Modeling and simulation > Simulation types and techniques > Massively parallel and high-performance simulations; Computing methodologies > Symbolic and algebraic manipulation > Symbolic and algebraic algorithms > Algebraic algorithms; Distributed decision making; General and reference > Cross-computing tools and techniques > Performance; Hardware; Kernel; Laboratories; Large-scale systems; Mathematics of computing > Mathematical analysis > Numerical analysis > Computation of transforms; Memory architecture; Memory management; Software and its engineering > Software organization and properties > Software system structures > Distributed systems organizing principles > Grid computing; US Department of Transportation
• ISBN: 0818643404; 9780818643408
• ISSN: 1063-9535
• DOI: 10.1145/169627.169699

Two interesting variants of large-scale shared-address-space parallel architectures are cache-coherent non-uniform-memory-access machines (CC-NUMA) and cache-only memory architectures (COMA). Both have distributed main memory and use directory-based cache coherence. While both architectures migrate and replicate data at the cache level automatically under hardware control, COMA machines do this at the main memory level as well. The authors compare the parallel performance of a recent realization of each type of architecture, the Stanford DASH multiprocessor (CC-NUMA) and the Kendall Square Research KSR-1 (COMA). Using a suite of important computational kernels and complete scientific applications, they examine performance differences resulting both from the CC-NUMA/COMA nature of the machines as well as from specific differences in system implementation.