An Empirical Evaluation of the Convex SPP-1000 Hierarchical Shared Memory System

Abstract

Cache coherency in a scalable parallel computer architecture requires mechanisms beyond the conventional common bus based snooping approaches which are limited to about 16 processors. The new Convex SPP-1000 achieves cache coherency across 128 processors through a two-level shared memory NUMA structure employing directory based and SCI protocol mechanisms. While hardware support for managing a common global name space minimizes overhead costs and simplifies programming, latency considerations for remote accesses may still dominate and can under unfavorable conditions constrain scalability. This paper provides the first published evaluation of the SP-1000 hierarchical cache coherency mechanisms from the perspective of measured latency and its impact on basic global How control mechanisms, scaling of a parallel science code, and sensitivity of cache miss rates to system scale. It is shown that global remote access latency is only a factor of seven greater than that of local cache miss penalty and that scaling of a challenging scientific application is not severely degraded by the hierarchical structure for achieving consistency across the system processor caches.