Scalable Speculative Parallelization on Commodity Clusters

  • Authors:

  • Hanjun Kim;Arun Raman;Feng Liu;Jae W. Lee;David I. August

  • Affiliations:

  • -;-;-;-;-

  • Venue:
  • MICRO '43 Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture
  • Year:
  • 2010

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Abstract

While clusters of commodity servers and switches are the most popular form of large-scale parallel computers, many programs are not easily parallelized for execution upon them. In particular, high inter-node communication cost and lack of globally shared memory appear to make clusters suitable only for server applications with abundant task-level parallelism and scientific applications with regular and independent units of work. Clever use of pipeline parallelism (DSWP), thread-level speculation (TLS), and speculative pipeline parallelism (Spec-DSWP) can mitigate the costs of inter-thread communication on shared memory multicore machines. This paper presents Distributed Software Multi-threaded Transactional memory (DSMTX), a runtime system which makes these techniques applicable to non-shared memory clusters, allowing them to efficiently address inter-node communication costs. Initial results suggest that DSMTX enables efficient cluster execution of a wider set of application types. For 11 sequential C programs parallelized for a 4-core 32-node (128 total core) cluster without shared memory, DSMTX achieves a geomean speedup of 49x. This compares favorably to the 15x speedup achieved by our implementation of TLS-only support for clusters.