Name
Abstract | ||
|---|---|---|
Domain-specific systems-on-chip, a class of heterogeneous many-core systems, is recognized as a key approach to narrow down the performance and energy-efficiency gap between custom hardware accelerators and programmable processors. Reaching the full potential of these architectures depends critically on optimally scheduling the applications to available resources at runtime. Existing optimization-based techniques cannot achieve this objective at runtime due to the combinatorial nature of the task scheduling problem. As the main theoretical contribution, this article poses scheduling as a classification problem and proposes a hierarchical imitation learning (IL)-based scheduler that learns from an Oracle to maximize the performance of multiple domain-specific applications. Extensive evaluations with six streaming applications from wireless communications and radar domains show that the proposed IL-based scheduler approximates an offline Oracle policy with more than 99% accuracy for performance- and energy-based optimization objectives. Furthermore, it achieves almost identical performance to the Oracle with a low runtime overhead and successfully adapts to new applications, many-core system configurations, and runtime variations in application characteristics. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCAD.2020.3012861 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
Domain-specific SoC (DSSoC),heterogeneous computing,imitation learning (IL),many-core architectures,scheduling | Journal | 39 |
Issue | ISSN | Citations |
11 | 0278-0070 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anish Krishnakumar | 1 | 0 | 0.68 |
| Samet E. Arda | 2 | 1 | 1.39 |
| A. Alper Goksoy | 3 | 0 | 0.68 |
| Sumit K. Mandal | 4 | 12 | 1.92 |
| Umit Y. Ogras | 5 | 1120 | 54.67 |
| Anderson Luiz Sartor | 6 | 31 | 7.67 |
| Radu Marculescu | 7 | 4366 | 267.69 |