Back to Search
Start Over
Convolution Engine: Balancing Efficiency and Flexibility in Specialized Computing.
- Source :
-
Communications of the ACM . Apr2015, Vol. 58 Issue 4, p85-93. 9p. 5 Diagrams, 5 Charts, 4 Graphs. - Publication Year :
- 2015
-
Abstract
- General-purpose processors, while tremendously versatile, pay a huge cost for their flexibility by wasting over 99% of the energy in programmability overheads. We observe that reducing this waste requires tuning data storage and compute structures and their connectivity to the data-flow and data-locality patterns in the algorithms. Hence, by backing off from full programmability and instead targeting key data-flow patterns used in a domain, we can create efficient engines that can be programmed and reused across a wide range of applications within that domain. We present the Convolution Engine (CE)--a programmable processor specialized for the convolution-like data-flow prevalent in computational photography, computer vision, and video processing. The CE achieves energy efficiency by capturing data-reuse patterns, eliminating data transfer overheads, and enabling a large number of operations per memory access. We demonstrate that the CE is within a factor of 2–3× of the energy and area efficiency of custom units optimized for a single kernel. The CE improves energy and area efficiency by 8–15× over data-parallel Single Instruction Multiple Data (SIMD) engines for most image processing applications. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00010782
- Volume :
- 58
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Communications of the ACM
- Publication Type :
- Periodical
- Accession number :
- 101826068
- Full Text :
- https://doi.org/10.1145/2735841