Performance Analysis of GEMM Workloads on the AMD Versal Platform
Kaustubh Manohar Mhatre, Venkata Guru Prasanth Mulleti, Curt John Bansil, Endri Taka, Aman Arora · 2025
AMD Versal is a new heterogeneous computing hardware architecture comprised of adaptive intelligence (AI) engines, programmable logic, and a processing system. General Matrix Multiplication (GEMM) is the fundamental building block of modern deep learning (DL) applications such as ChatGPT, and GEMM workloads can be mapped onto Versal in different ways, each with distinct trade-offs. This paper presents a thorough analysis of GEMM workloads of different shapes and sizes, showcasing performance artifacts associated with the AMD Versal architecture. Focusing on the unique aspects of the Versal architecture, multiple research questions related to performance scaling, sensitivity, and efficiency are explored. This paper aims to assist FPGA developers looking to implement GEMM on AMD Versal by providing insights for enhancing performance.