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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kai Du Varman, P. Mohanram, K. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, University of Pittsburgh, USA (Mohanram, K.) || Department of Electrical and Computer Engineering, Rice University, Houston, USA (Kai Du; Varman, P.) |
| Abstract | Speculative adders have attracted strong interest for reducing critical path delays to sub-logarithmic delays by exploiting the tradeoffs between reliability and performance. Speculative adders also find use in the design of reliable variable latency adders, which combine speculation with error correction to achieve high performance for low area overhead over traditional adders. This paper describes speculative carry select addition (SCSA), a novel function speculation technique for the design of low error-rate speculative adders and low overhead, high performance, reliable variable latency adders. We develop an analytical model for the error rate of SCSA to facilitate both design exploration and convergence. We show that for an error rate of 0.01% (0.25%), SCSA-based speculative addition is 10% faster than the DesignWare adder with up to 43% (56%) area reduction. Further, on average, variable latency addition using SCSA-based speculative adders is 10% faster than the DesignWare adder with area requirements of −19% to 16% (−17% to 29%) for unsigned random (signed Gaussian) inputs. |
| Starting Page | 1257 |
| Ending Page | 1262 |
| File Size | 277713 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781457721458 |
| ISSN | 15301591 |
| DOI | 10.1109/DATE.2012.6176685 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-03-12 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | European Design Automation Association (EDAA) |
| Subject Keyword | Adders Error analysis Delay Analytical models Complexity theory Reliability engineering |
| Content Type | Text |
| Resource Type | Article |
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