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Content Provider | ACM Digital Library |
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Author | Lee, Jae W. Kim, Hanjun August, David I. Liu, Feng Raman, Arun |
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. |
Starting Page | 3 |
Ending Page | 14 |
Page Count | 12 |
File Format | |
ISBN | 9780769542997 |
ISSN | 10724451 |
DOI | 10.1109/MICRO.2010.19 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2010-12-04 |
Access Restriction | Subscribed |
Subject Keyword | Loop-level parallelism multi-threaded transactions pipelined parallelism software transactional memory thread-level speculation distributed systems |
Content Type | Text |
Resource Type | Article |
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