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Scalable and reliable communication for hardware transactional memory
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Proceedings of the 17th international conference on Parallel architectures and compilation techniques table of contents
Toronto, Ontario, Canada
SESSION: Multicore memory hierarchy design (part 1) table of contents
Pages 144-154  
Year of Publication: 2008
ISBN:978-1-60558-282-5
Authors
Seth H. Pugsley  University of Utah, Salt Lake City, UT, USA
Manu Awasthi  University of Utah, Salt Lake City, UT, USA
Niti Madan  University of Utah, Salt Lake City, UT, USA
Naveen Muralimanohar  University of Utah, Salt Lake City, UT, USA
Rajeev Balasubramonian  University of Utah, Salt Lake City, UT, USA
Sponsors
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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ABSTRACT

In a hardware transactional memory system with lazy versioning and lazy conflict detection, the process of transaction commit can emerge as a bottleneck. This is especially true for a large-scale distributed memory system where multiple transactions may attempt to commit simultaneously and coordination is required before allowing commits to proceed in parallel. In this paper, we propose novel algorithms to implement commit that are more scalable in terms of delay and are free of deadlocks/livelocks. We show that these algorithms have similarities with the token cache coherence concept and leverage these similarities to extend the algorithms to handle message loss and starvation scenarios. The proposed algorithms improve upon the state-of-the-art by yielding up to a 7X reduction in commit delay and up to a 48X reduction in network messages for commit. These translate into overall performance improvements of up to 66% (for synthetic workloads with average transaction length of 200 cycles), 35% (for average transaction length of 1000 cycles), and 8% (for average transaction length of 4000 cycles). For a small group of multi-threaded programs with frequent transaction commits, improvements of up to 8% were observed for a 32-node simulation.


REFERENCES

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Collaborative Colleagues:
Seth H. Pugsley: colleagues
Manu Awasthi: colleagues
Niti Madan: colleagues
Naveen Muralimanohar: colleagues
Rajeev Balasubramonian: colleagues