Abstract
The SLATE (Software for Linear Algebra Targeting Exascale) library is being developed to provide fundamental dense linear algebra capabilities for current and upcoming distributed high-performance systems, both accelerated CPU-GPU based and CPU based. SLATE will provide coverage of existing ScaLAPACK functionality, including the parallel BLAS; linear systems using LU and Cholesky; least squares problems using QR; and eigenvalue and singular value problems. In this respect, it will serve as a replacement for ScaLAPACK, which after two decades of operation, cannot adequately be retrofitted for modern accelerated architectures. SLATE uses modern techniques such as communication-avoiding algorithms, lookahead panels to overlap communication and computation, and task-based scheduling, along with a modern C++ framework. Here we present the design of SLATE and initial reports of several of its components.
| Original language | English |
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| Title of host publication | Proceedings of SC 2019 |
| Subtitle of host publication | The International Conference for High Performance Computing, Networking, Storage and Analysis |
| Publisher | IEEE Computer Society |
| ISBN (Electronic) | 9781450362290 |
| DOIs | |
| State | Published - Nov 17 2019 |
| Externally published | Yes |
| Event | 2019 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019 - Denver, United States Duration: Nov 17 2019 → Nov 22 2019 |
Publication series
| Name | International Conference for High Performance Computing, Networking, Storage and Analysis, SC |
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| ISSN (Print) | 2167-4329 |
| ISSN (Electronic) | 2167-4337 |
Conference
| Conference | 2019 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 11/17/19 → 11/22/19 |
Funding
This research was supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S. Department of Energy’s Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation’s exascale computing imperative. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
Keywords
- Dense linear algebra
- Distributed computing
- GPU computing