AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

Agostini, N. B., Haris, J., Gibson, P. , Jayaweera, M., Rubin, N., Tumeo, A., Abellán, J. L., Cano Reyes, J. and Kaeli, D. (2024) AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. In: International Symposium on Code Generation and Optimization (CGO) 2024, Edinburgh, United Kingdom, 02-06 Mar 2024, pp. 143-157. ISBN 9798350395099 (doi: 10.1109/CGO57630.2024.10444801)

Abstract

This paper addresses the need for automatic and efficient generation of host driver code for arbitrary custom AXI-based accelerators targeting linear algebra algorithms, an important workload in various applications, including machine learning and scientific computing. While existing tools have focused on automating accelerator prototyping, little attention has been paid to the host-accelerator interaction. This paper introduces AXI4MLIR, an extension of the MLIR compiler framework designed to facilitate the automated generation of host-accelerator driver code. With new MLIR attributes and transformations, AXI4MLIR empowers users to specify accelerator features (including their instructions) and communication patterns and exploit the host memory hierarchy. We demonstrate AXI4MLIR's versatility across different types of accelerators and problems, showcasing significant CPU cache reference reductions (up to 56%) and up to a 1.65× speedup compared to manually optimized driver code implementations. AXI4MLIR implementation is open-source and available at: https:/7github.com/AXI4MLIR/axi4mlir.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cano Reyes, Dr Jose and Haris, Jude and Gibson, Mr Perry
• Authors: Agostini, N. B., Haris, J., Gibson, P., Jayaweera, M., Rubin, N., Tumeo, A., Abellán, J. L., Cano Reyes, J., and Kaeli, D.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 2643-2838
• ISBN: 9798350395099
• Copyright Holders: Copyright: © 2024 IEEE
• First Published: First published in International Symposium on Code Generation and Optimization (CGO) 2024: 143-157
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

Related URLs

• Pre-print
• Organisation