Format abstraction for sparse tensor algebra compilers
Abstract
This paper shows how to build a sparse tensor algebra compiler that is agnostic to tensor formats (data layouts). We develop an interface that describes formats in terms of their capabilities and properties, and show how to build a modular code generator where new formats can be added as plugins. We then describe six implementations of the interface that compose to form the dense, CSR/CSF, COO, DIA, ELL, and HASH tensor formats and countless variants thereof. With these implementations at hand, our code generator can generate code to compute any tensor algebra expression on any combination of the aforementioned formats.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 24, 2018
- Source ID
- 10.1145/3276493
Entities
People
- Fredrik Kjølstad
- Saman Amarasinghe
- Stephen Chou
Organizations
- Defense Advanced Research Projects Agency
- Massachusetts Institute of Technology
- National Science Foundation
- Toyota Research Institute
- Wind Energy Technologies Office