Convolution engine
Abstract
This paper focuses on the trade-off between flexibility and efficiency in specialized computing. We observe that specialized units achieve most of their efficiency gains by tuning data storage and compute structures and their connectivity to the data-flow and data-locality patterns in the kernels. Hence, by identifying 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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 23, 2013
- Source ID
- 10.1145/2508148.2485925
Entities
People
- Christos Kozyrakis
- Mark A. Horowitz
- Ofer Shacham
- Preethi Venkatesan
- Rehan Hameed
- Wajahat Qadeer
Organizations
- Defense Advanced Research Projects Agency
- Stanford University