abstract: Performance improvements have largely followed Moore's Law due to the help from technology scaling. In order to continue improving performance, power-efficiency must be reduced. Better technology has improved power-efficiency, but this has a limit. Multi-core architectures have been shown to be an additional aid to this crusade of increased power-efficiency. Accelerators are growing in popularity as the next means of achieving power-efficient performance. Accelerators such as Intel SSE are ideal, but prove difficult to program. FPGAs, on the other hand, are less efficient due to their fine-grained reconfigurability. A middle ground is found in CGRAs, which are highly power-efficient, but largely programmable accelerators. Power-efficiencies of 100s of GOPs/W have been estimated, more than 2 orders of magnitude greater than current processors. Currently, CGRAs are limited in their applicability due to their ability to only accelerate a single thread at a time. This limitation becomes especially apparent as multi-core/multi-threaded processors have moved into the mainstream. This limitation is removed by enabling multi-threading on CGRAs through a software-oriented approach. The key capability in this solution is enabling quick run-time transformation of schedules to execute on targeted portions of the CGRA. This allows the CGRA to be shared among multiple threads simultaneously. Analysis shows that enabling multi-threading has very small costs but provides very large benefits (less than 1% single-threaded performance loss but nearly 300% CGRA throughput increase). By increasing dynamism of CGRA scheduling, system performance is shown to increase overall system performance of an optimized system by almost 350% over that of a single-threaded CGRA and nearly 20x faster than the same system with no CGRA in a highly threaded environment. / Dissertation/Thesis / M.S. Computer Science 2011
| Identifer | oai:union.ndltd.org:asu.edu/item:14483 |
| Date | January 2011 |
| Contributors | Pager, Jared (Author), Shrivastava, Aviral (Advisor), Gupta, Sandeep (Committee member), Speyer, Gil (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 82 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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