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| Content Provider | ACM Digital Library |
|---|---|
| Author | Li, Zheng Joubert, Antoine Belhadj, Bilel Héliot, Rodolphe Temam, Olivier |
| Abstract | Motivated by energy constraints, future heterogeneous multi-cores may contain a variety of accelerators, each targeting a subset of the application spectrum. Beyond energy, the growing number of faults steers accelerator research towards fault-tolerant accelerators. In this article, we investigate a fault-tolerant and energy-efficient accelerator for signal processing applications. We depart from traditional designs by introducing an accelerator which relies on unary coding, a concept which is well adapted to the continuous real-world inputs of signal processing applications. Unary coding enables a number of atypical micro-architecture choices which bring down area cost and energy; moreover, unary coding provides graceful output degradation as the amount of transient faults increases. We introduce a configurable hybrid digital/analog micro-architecture capable of implementing a broad set of signal processing applications based on these concepts, together with a back-end optimizer which takes advantage of the special nature of these applications. For a set of five signal applications, we explore the different design tradeoffs and obtain an accelerator with an area cost of $1.63mm^{2}.$ On average, this accelerator requires only 2.3% of the energy of an Atom-like core to implement similar tasks. We then evaluate the accelerator resilience to transient faults, and its ability to trade accuracy for energy savings. |
| Starting Page | 1 |
| Ending Page | 12 |
| Page Count | 12 |
| File Format | |
| ISSN | 01635964 |
| DOI | 10.1145/2508148.2485923 |
| Journal | ACM SIGARCH Computer Architecture News (CARN) |
| Volume Number | 41 |
| Issue Number | 3 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1981-04-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
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