A method for improving performance/watt of an embedded single-instruction multiple-data (SIMD) architecture using application-guided a priori scheduling of hardware resources is presented. A multi-core architectural simulator is adopted that accurately estimates power, performance, and utilization of various processor components (logic, interconnect and memory). A greedy search is then performed on each algorithm block of a signal processing chain in order to schedule each component's throughput and power. The proposed software-directed hardware rebalancing, applied to a typical electroencephalography (EEG) filtering chain, is analyzed for two different SIMD architectures. The first, representing a super V[subscript th] processor demonstrates a 51%-86% improvement in performance/watt at 1%-10% throughput reduction using block level or algorithm level a priori scheduling. The second architecture used is Synctium, a near V[subscript th] processor which demonstrates 50%-99% performance/watt improvement across the same throughput reduction range and optimization techniques. / Graduation date: 2012
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/29853 |
| Date | 20 April 2012 |
| Creators | Albright, Ryan K. |
| Contributors | Chiang, Patrick |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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