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HIPCL: Tool for Porting CUDA Applications to Advanced OpenCL Platforms Through HIP

Authors:

Michal Babej,

Pekka JääskeläinenAuthors Info & Claims

IWOCL '20: Proceedings of the International Workshop on OpenCL

Article No.: 18, Pages 1 - 3

https://doi.org/10.1145/3388333.3388641

Published: 27 April 2020 Publication History

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Abstract

Heterogeneous-compute Interface for Portability (HIP), is an open-source C++ runtime API and a kernel language. It is designed to be compatible with CUDA and to deliver close to native performance on CUDA platforms while exposing additional low-level hardware features. A key use case of HIP is in providing a portability route out from the NVIDIA CUDA platform, which is highlighted with an automated tool that can convert CUDA applications to HIP programs.

In this work we describe HIPCL, a new tool which allows running HIP programs on OpenCL platforms with sufficient capabilities. HIPCL thus expands the scope of the CUDA portability route from AMD ROCm platform supported targets to platforms with advanced OpenCL support. We highlight the implementation challenges of HIPCL related to the feature mismatches between CUDA and OpenCL and exemplify its runtime overheads in comparison to directly executing OpenCL applications.

Reference

[1]

Pekka Jääskeläinen, Carlos Sánchez de La Lama, Erik Schnetter, Kalle Raiskila, Jarmo Takala, and Heikki Berg. 2015. pocl: A Performance-Portable OpenCL Implementation. International Journal of Parallel Programming 43, 5 (2015), 752--785.

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Rangel EPennycook SPope AFrontiere NMa ZMadananth V(2023)A Performance-Portable SYCL Implementation of CRK-HACC for ExascaleProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624187(1114-1125)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624187
Fumero JRethy GStratikopoulos AFoutris NKotselidis CRosà AHenz M(2023)Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code GenerationProceedings of the 15th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages10.1145/3623507.3623555(61-72)Online publication date: 18-Oct-2023
https://dl.acm.org/doi/10.1145/3623507.3623555
Zhao JBertoni CYoung JHarms KSarkar VVideau B(2023)HIPLZ: Enabling Performance Portability for Exascale SystemsEuro-Par 2022: Parallel Processing Workshops10.1007/978-3-031-31209-0_15(197-210)Online publication date: 2-May-2023
https://doi.org/10.1007/978-3-031-31209-0_15
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Index Terms

HIPCL: Tool for Porting CUDA Applications to Advanced OpenCL Platforms Through HIP
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel programming languages
2. Software and its engineering
  1. Software notations and tools
    1. Compilers

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Information & Contributors

Information

Published In

IWOCL '20: Proceedings of the International Workshop on OpenCL

April 2020

104 pages

ISBN:9781450375313

DOI:10.1145/3388333

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

In-Cooperation

Khronos: Khronos Group
Codeplay: Codeplay Software Ltd.
Intel: Intel
The University of Bristol: The University of Bristol
Tech Univ of Munich: Technical University of Munich

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 April 2020

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Poster
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Refereed limited

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Electronic Components and Systems for European Leadership

Conference

IWOCL '20

IWOCL '20: International Workshop on OpenCL

April 27 - 29, 2020

Munich, Germany

Acceptance Rates

IWOCL '20 Paper Acceptance Rate 21 of 30 submissions, 70%;

Overall Acceptance Rate 84 of 152 submissions, 55%

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Cited By

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Rangel EPennycook SPope AFrontiere NMa ZMadananth V(2023)A Performance-Portable SYCL Implementation of CRK-HACC for ExascaleProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624187(1114-1125)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624187
Fumero JRethy GStratikopoulos AFoutris NKotselidis CRosà AHenz M(2023)Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code GenerationProceedings of the 15th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages10.1145/3623507.3623555(61-72)Online publication date: 18-Oct-2023
https://dl.acm.org/doi/10.1145/3623507.3623555
Zhao JBertoni CYoung JHarms KSarkar VVideau B(2023)HIPLZ: Enabling Performance Portability for Exascale SystemsEuro-Par 2022: Parallel Processing Workshops10.1007/978-3-031-31209-0_15(197-210)Online publication date: 2-May-2023
https://doi.org/10.1007/978-3-031-31209-0_15
Zhao JBertoni CYoung JHarms KSarkar VVideau B(2023)HIPLZ: Enabling performance portability for exascale systemsConcurrency and Computation: Practice and Experience10.1002/cpe.786635:25Online publication date: 17-Jul-2023
https://doi.org/10.1002/cpe.7866
Nair AJoshi A(2022)Parallelizing CPU-GPU Network Processing Flows2022 International Conference on Innovative Trends in Information Technology (ICITIIT)10.1109/ICITIIT54346.2022.9744209(1-5)Online publication date: 12-Feb-2022
https://doi.org/10.1109/ICITIIT54346.2022.9744209
Schutte HPhelps CMarathe AIslam T(2022)LIBNVCD: An Extendable and User-friendly Multi-GPU Performance Measurement Tool2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC54236.2022.00019(73-82)Online publication date: Jun-2022
https://doi.org/10.1109/COMPSAC54236.2022.00019
Thoman PGogl DFahringer T(2021)Sylkan: Towards a Vulkan Compute Target Platform for SYCLProceedings of the 9th International Workshop on OpenCL10.1145/3456669.3456683(1-12)Online publication date: 27-Apr-2021
https://dl.acm.org/doi/10.1145/3456669.3456683
Jin ZVetter J(2021)Evaluating CUDA Portability with HIPCL and DPCT2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW52791.2021.00065(371-376)Online publication date: Jun-2021
https://doi.org/10.1109/IPDPSW52791.2021.00065
Ai XMania GGray HKuhn MStyles N(2021)A GPU-Based Kalman Filter for Track FittingComputing and Software for Big Science10.1007/s41781-021-00065-z5:1Online publication date: 5-Oct-2021
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