@inproceedings{c13bd55810db4f63a8f4d088ad4f5d3b,
title = "The Support of MLIR HLS Adaptor for LLVM IR",
abstract = "Since the emergence of MLIR, High-level Synthesis (HLS) tools started to design in multi-level abstractions. Unlike the traditional HLS tools that are based on a single abstraction (e.g. LLVM), optimizations in different levels of abstraction could benefit from cross-layer optimizations to get better results. Although current HLS tools with MLIR can generate HLS C/C++ to do synthesis, we believe that a direct IR transformation from MLIR to LLVM will keep more expression details. In this paper, we propose an adaptor for LLVM IR, which can optimize the IR, generated from MLIR, into HLS readable IR. Without the gap of unsupported syntax between different versions, developers could focus on their specialization. Our preliminary results show that the MLIR flow via our adaptor can generate comparable performance results with the version by MLIR HLS tools generating HLS C++ codes. The experiment is performed with Xilinx Vitis and HLS tools.",
keywords = "HLS, LLVM, MLIR",
author = "Liang, {Geng Ming} and Yuan, {Chuan Yue} and Yuan, {Meng Shiun} and Chen, {Tai Liang} and Chen, {Kuan Hsun} and Lee, {Jenq Kuen}",
note = "Funding Information: This work is supported in part by Taiwan MOST and Mediatek. Publisher Copyright: {\textcopyright} 2022 ACM.; 51st International Conference on Parallel Processing, ICPP 2022 ; Conference date: 29-08-2022 Through 01-09-2022",
year = "2023",
month = jan,
day = "13",
doi = "10.1145/3547276.3548515",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "1--8",
booktitle = "ICPP Workshops '22: Workshop Proceedings of the 51st International Conference on Parallel Processing",
address = "United States",
}