Abstract
As opposed to the Open Computing Language (OpenCL) programming model in which host and device codes are generally written in different languages, the SYCL programming model can combine host and device codes for an application in a type-safe way to improve development productivity. In this paper, we chose the HACCmk routine, a representative compute-bound kernel, as a case study on the performance of the SYCL programming model targeting a heterogeneous computing device. More specifically, we introduced the SYCL programming model, presented the OpenCL and SYCL implementations of the routine, and compared the performance of the two implementations using the offline and online compilation on Intelo Iri sT\M Pro integrated GPUs. We found that the overhead of online compilation may become significant compared to the execution time of a kernel. Compared to the performance of OpenCL implementations, the SYCL implementation can maintain the performance using the offline compilation. The number of execution units in a GPU are critical to improving the raw performance of a compute-bound kernel.
| Original language | English |
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| Title of host publication | Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 368-374 |
| Number of pages | 7 |
| ISBN (Electronic) | 9781728174457 |
| DOIs | |
| State | Published - May 2020 |
| Externally published | Yes |
| Event | 34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 - New Orleans, United States Duration: May 18 2020 → May 22 2020 |
Publication series
| Name | Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 |
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Conference
| Conference | 34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 |
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| Country/Territory | United States |
| City | New Orleans |
| Period | 05/18/20 → 05/22/20 |
Funding
We appreciate the reviewers for their constructive criticism. The research was supported by the U.S. Department of Energy, Office of Science, under contract DE AC02 06CH11357 and made use of the Argonne Leadership Computing Facility, a DOE Office of Science User Facility.
Keywords
- Compilation modes
- Compute-bound kernel
- GPU
- Programming model