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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ro, W.W. Gaudiot, J.-L. |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Electr. Eng., Univ. of Southern California, CA, USA (Ro, W.W.) |
| Abstract | Summary form only given. Speculative preexecution achieves efficient data prefetching by running additional prefetching threads on spare hardware contexts. Various implementations for speculative preexecution have been proposed, including compiler-based static approaches and hardware-based dynamic approaches. A static approach defines the p-thread at compile time and executes it as a stand-alone running thread. Therefore, it cannot efficiently take the dynamic events into account and requires a higher fetch bandwidth. Conversely, a hardware approach is, by essence, able to dynamically use the runtime information. However, it requires more complex hardware and also lacks global program information on data and control flow. We propose SPEAR (Speculative Preexecution Assisted by CompileR), a preexecution model which is a hybrid of the two approaches. It relies on a post-compiler to extract the p-thread code from program binaries and uses specially designed hardware to trigger the execution of the p-thread. For this purpose, an automated software tool for p-thread identification has been developed and a modified SMT model with the specially designed front-end is proposed. |
| Sponsorship | IEEE Comput. Soc. Tech. Committee on Parallel Processing |
| File Size | 1471038 |
| File Format | |
| ISBN | 0769521320 |
| DOI | 10.1109/IPDPS.2004.1303008 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-04-26 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Prefetching Yarn Hardware Delay Bandwidth Runtime Data mining Software tools Surface-mount technology Microprocessors |
| Content Type | Text |
| Resource Type | Article |
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