Errant Beam Detection Using the AMD Versal ACAP and Vitis AI

Anthony M. Cabrera; Yigit A. Yucesan; Frank Y. Liu; Willem Blokland; Jeffrey S. Vetter

doi:10.1109/HPEC58863.2023.10363622

Errant Beam Detection Using the AMD Versal ACAP and Vitis AI

Anthony M. Cabrera, Yigit A. Yucesan, Frank Y. Liu, Willem Blokland, Jeffrey S. Vetter

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The prevalence of ML and AI-powered solutions along with the slowing of Moore's Law has given rise to novel hardware platforms aimed at accelerating ML and AI. While programming these hardware platforms can be difficult, particularly for non-hardware experts, hardware vendors provide high-level tooling in an effort to address this difficulty. The Versal ACAP is an SoC designed by AMD that combines CPU cores, FPGA fabric, and a tiled, vector architecture called an AI engine all on the same socket. In an effort to more easily program this heterogeneous system, AMD has provided the Vitis AI development stack. In this work, we leverage Vitis AI to program a Versal ACAP to perform errant beam detection in the Spallation Neutron Source at Oak Ridge National Laboratory. Our initial work shows that after quantization and compilation of the model for the Versal ACAP, the classification accuracy, as measured by the AUC metric, is over 95% accurate while achieving this accuracy in 46 microseconds on average.

Original language	English
Title of host publication	2023 IEEE High Performance Extreme Computing Conference, HPEC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350308600
DOIs	https://doi.org/10.1109/HPEC58863.2023.10363622
State	Published - 2023
Event	2023 IEEE High Performance Extreme Computing Conference, HPEC 2023 - Virtual, Online, United States Duration: Sep 25 2023 → Sep 29 2023

Publication series

Name	2023 IEEE High Performance Extreme Computing Conference, HPEC 2023

Conference

Conference	2023 IEEE High Performance Extreme Computing Conference, HPEC 2023
Country/Territory	United States
City	Virtual, Online
Period	09/25/23 → 09/29/23

Funding

This research used resources of the Experimental Computing Laboratory (ExCL) 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 This research was supported by the Defense Advanced Research Projects Agency Microsystems Technology Office Domain-Specific System-on-Chip Program. This research used resources of the Experimental Comput- ing Laboratory (ExCL) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. De- partment of Energy under Contract No. DE-AC05-00OR22725 This research was supported by the Defense Advanced Research Projects Agency Microsystems Technology Office Domain-Specific System-on-Chip Program. The authors would like to thank Joseph Melber and Paul Hartke at AMD for helping to procure the VCK190 and connecting us with technical staff to troubleshoot issues.

Funders	Funder number
U.S. De- partment of Energy
U.S. Department of Energy	DE-AC05-00OR22725
Defense Advanced Research Projects Agency	VCK190
Office of Science

Keywords

Artificial Intelligence
Edge Computing
Heterogeneous Computing
Machine Learning
Versal ACAP
Vitis AI

Access to Document

10.1109/HPEC58863.2023.10363622

Cite this

Cabrera, A. M., Yucesan, Y. A., Liu, F. Y., Blokland, W., & Vetter, J. S. (2023). Errant Beam Detection Using the AMD Versal ACAP and Vitis AI. In 2023 IEEE High Performance Extreme Computing Conference, HPEC 2023 (2023 IEEE High Performance Extreme Computing Conference, HPEC 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPEC58863.2023.10363622

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abstract = "The prevalence of ML and AI-powered solutions along with the slowing of Moore's Law has given rise to novel hardware platforms aimed at accelerating ML and AI. While programming these hardware platforms can be difficult, particularly for non-hardware experts, hardware vendors provide high-level tooling in an effort to address this difficulty. The Versal ACAP is an SoC designed by AMD that combines CPU cores, FPGA fabric, and a tiled, vector architecture called an AI engine all on the same socket. In an effort to more easily program this heterogeneous system, AMD has provided the Vitis AI development stack. In this work, we leverage Vitis AI to program a Versal ACAP to perform errant beam detection in the Spallation Neutron Source at Oak Ridge National Laboratory. Our initial work shows that after quantization and compilation of the model for the Versal ACAP, the classification accuracy, as measured by the AUC metric, is over 95% accurate while achieving this accuracy in 46 microseconds on average.",

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Cabrera, AM, Yucesan, YA, Liu, FY, Blokland, W & Vetter, JS 2023, Errant Beam Detection Using the AMD Versal ACAP and Vitis AI. in 2023 IEEE High Performance Extreme Computing Conference, HPEC 2023. 2023 IEEE High Performance Extreme Computing Conference, HPEC 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE High Performance Extreme Computing Conference, HPEC 2023, Virtual, Online, United States, 09/25/23. https://doi.org/10.1109/HPEC58863.2023.10363622

Errant Beam Detection Using the AMD Versal ACAP and Vitis AI. / Cabrera, Anthony M.; Yucesan, Yigit A.; Liu, Frank Y. et al.
2023 IEEE High Performance Extreme Computing Conference, HPEC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE High Performance Extreme Computing Conference, HPEC 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Errant Beam Detection Using the AMD Versal ACAP and Vitis AI

Abstract

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Funding

Keywords

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