Software data-triggered threads

Authors:
Hung-Wei Tseng;Dean Michael Tullsen
Affiliations:
University of California, San Diego, La Jolla, CA, USA;University of California, San Diego, La Jolla, CA, USA
Venue:
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
Year:
2012

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Abstract

The data-triggered threads (DTT) programming and execution model can increase parallelism and eliminate redundant computation. However, the initial proposal requires significant architecture support, which impedes existing applications and architectures from taking advantage of this model. This work proposes a pure software solution that supports the DTT model without any hardware support. This research uses a prototype compiler and runtime libraries running on top of existing machines. Several enhancements to the initial software implementation are presented, which further improve the performance. The software runtime system improves the performance of serial C SPEC benchmarks by 15% on a Nehalem processor, but by over 7X over the full suite of single-thread applications. It is shown that the DTT model can work in conjunction with traditional parallelism. The DTT model provides up to 64X speedup over parallel applications exploiting traditional parallelism.