https://arxiv.org/abs/2405.00436 Skip to main content Cornell University We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate arxiv logo > cs > arXiv:2405.00436 [ ] Help | Advanced Search [All fields ] Search arXiv logo Cornell University Logo [ ] GO quick links * Login * Help Pages * About Computer Science > Distributed, Parallel, and Cluster Computing arXiv:2405.00436 (cs) [Submitted on 1 May 2024] Title:Porting HPC Applications to AMD Instinct$^\text{TM}$ MI300A Using Unified Memory and OpenMP Authors:Suyash Tandon, Leopold Grinberg, Gheorghe-Teodor Bercea, Carlo Bertolli, Mark Olesen, Simone Bna, Nicholas Malaya View a PDF of the paper titled Porting HPC Applications to AMD Instinct$^\text{TM}$ MI300A Using Unified Memory and OpenMP, by Suyash Tandon and 5 other authors View PDF Abstract:AMD Instinct$^\text{TM}$ MI300A is the world's first data center accelerated processing unit (APU) with memory shared between the AMD "Zen 4" EPYC$^\text{TM}$ cores and third generation CDNA$^\text{TM}$ compute units. A single memory space offers several advantages: i) it eliminates the need for data replication and costly data transfers, ii) it substantially simplifies application development and allows an incremental acceleration of applications, iii) is easy to maintain, and iv) its potential can be well realized via the abstractions in the OpenMP 5.2 standard, where the host and the device data environments can be unified in a more performant way. In this article, we provide a blueprint of the APU programming model leveraging unified memory and highlight key distinctions compared to the conventional approach with discrete GPUs. OpenFOAM, an open-source C++ library for computational fluid dynamics, is presented as a case study to emphasize the flexibility and ease of offloading a full-scale production-ready application on MI300 APUs using directive-based OpenMP programming. Comments: Accepted paper at ISC High Performance 2024 Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) Cite as: arXiv:2405.00436 [cs.DC] (or arXiv:2405.00436v1 [cs.DC] for this version) https://doi.org/10.48550/arXiv.2405.00436 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Suyash Tandon [view email] [v1] Wed, 1 May 2024 10:38:06 UTC (955 KB) Full-text links: Access Paper: View a PDF of the paper titled Porting HPC Applications to AMD Instinct$^\text{TM}$ MI300A Using Unified Memory and OpenMP, by Suyash Tandon and 5 other authors * View PDF * TeX Source * Other Formats license icon view license Current browse context: cs.DC < prev | next > new | recent | 2405 Change to browse by: cs References & Citations * NASA ADS * Google Scholar * Semantic Scholar a export BibTeX citation Loading... BibTeX formatted citation x [loading... ] Data provided by: Bookmark BibSonomy logo Reddit logo (*) Bibliographic Tools Bibliographic and Citation Tools [ ] Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) [ ] Litmaps Toggle Litmaps (What is Litmaps?) [ ] scite.ai Toggle scite Smart Citations (What are Smart Citations?) ( ) Code, Data, Media Code, Data and Media Associated with this Article [ ] Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) [ ] DagsHub Toggle DagsHub (What is DagsHub?) [ ] GotitPub Toggle Gotit.pub (What is GotitPub?) [ ] Links to Code Toggle Papers with Code (What is Papers with Code?) [ ] ScienceCast Toggle ScienceCast (What is ScienceCast?) ( ) Demos Demos [ ] Replicate Toggle Replicate (What is Replicate?) [ ] Spaces Toggle Hugging Face Spaces (What is Spaces?) [ ] Spaces Toggle TXYZ.AI (What is TXYZ.AI?) ( ) Related Papers Recommenders and Search Tools [ ] Link to Influence Flower Influence Flower (What are Influence Flowers?) [ ] Connected Papers Toggle Connected Papers (What is Connected Papers?) [ ] Core recommender toggle CORE Recommender (What is CORE?) * Author * Venue * Institution * Topic ( ) About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?) * About * Help * Click here to contact arXiv Contact * Click here to subscribe Subscribe * Copyright * Privacy Policy * Web Accessibility Assistance * arXiv Operational Status Get status notifications via email or slack