Name
Abstract | ||
|---|---|---|
Finding the optimal tradeoff in terms of area, delay and energy consumption which satisfies a given DSP functionality is the main objective of hardware and embedded software designers. Signal bit-widths importantly impact these metrics. Signals with less bits also require operators with smaller area, shorter critical path and lower energy consumption. In some applications, these minimal signal bit-widths can vary significantly depending on the quantization mode. As a result, a rounding-based implementation may require smaller minimal bit-widths than a truncation-based one and potentially lead to cheaper system implementations. The optimal quantization mode combination (QMC) can reduce significantly the implementation cost compared to a traditional implementation based on the truncation mode. This has been demonstrated on different representative kernels. For example, in the case of a LMS filter, the optimal QMC can reduce up to 46% of the area of an implementation based on truncation. |
Year | Venue | Field |
|---|---|---|
2010 | European Signal Processing Conference | Least mean squares filter,Truncation,Digital signal processing,Embedded software,Computer science,Real-time computing,Rounding,Critical path method,Quantization (signal processing),Computer engineering,Energy consumption |
DocType | ISSN | Citations |
Conference | 2219-5491 | 3 |
PageRank | References | Authors |
0.57 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Menard | 1 | 207 | 19.00 |
| David Novo | 2 | 110 | 12.88 |
| Romuald Rocher | 3 | 94 | 8.38 |
| Francky Catthoor | 4 | 3932 | 423.30 |
| Olivier Sentieys | 5 | 597 | 73.35 |