tutorial

Open access

Performance portable C++ programming with RAJA

Authors:

David Beckingsale,

Richard Hornung,

Tom Scogland,

Arturo VargasAuthors Info & Claims

PPoPP '19: Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming

Pages 455 - 456

https://doi.org/10.1145/3293883.3302577

Published: 16 February 2019 Publication History

PDF eReader

Abstract

With the rapid change of computing architectures, and variety of programming models; the ability to develop performance portable applications has become of great importance. This is particularly true in large production codes where developing and maintaining hardware specific versions is untenable.

To simplify the development of performance portable code, we introduce RAJA, our C++ library that allows developers to write single-source applications that can target multiple hardware and programming model back-ends. We provide a thorough introduction to all of RAJA features, and walk through some hands-on examples that will allow attendees to understand how RAJA might benefit their own applications. Attendees should bring a laptop computer to participate in the hands-on exercises.

This tutorial will introduce attendees to RAJA, a C++ library for developing performance portable applications. Attendees will learn how to write performance portable code that can execute on a range of programming models (OpenMP, CUDA, Intel TBB, and HCC) and hardware (CPU, GPU, Xeon Phi).

Specifically, attendees will learn how to convert existing C++ applications to use RAJA, and how to use RAJA's programming abstractions to expose existing parallelism in their applications without complex algorithm rewrites. We will also cover specific guidelines for using RAJA in a large application, including some common "gotchas" and how to handle memory management. Finally, attendees will learn how to categorize loops to allow for simple and systematic performance tuning on any architecture.

Cited By

View all

Heroux MValero-Lara PLee SGonzalez-Tallada MDenny JTeranishi KVetter J(2024)Enhancing Kokkos with OpenACCInternational Journal of High Performance Computing Applications10.1177/1094342024126198738:5(409-426)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1177/10943420241261987
Valero-Lara PLee SDenny JTeranishi KVetter JGonzalez-Tallada M(2024)sKokkos: Enabling Kokkos with Transparent Device Selection on Heterogeneous Systems using OpenACCProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3635035.3635043(23-34)Online publication date: 18-Jan-2024
https://dl.acm.org/doi/10.1145/3635035.3635043
Crisci LCarpentieri LCosenza BAccordi GGadioli DVitali EPalermo GBeccari A(2024)Enabling performance portability on the LiGen drug discovery pipelineFuture Generation Computer Systems10.1016/j.future.2024.03.045158:C(44-59)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.future.2024.03.045
Show More Cited By

Index Terms

Performance portable C++ programming with RAJA
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel programming languages
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages

Recommendations

On the Performance Portability of OpenACC, OpenMP, Kokkos and RAJA
HPCAsia '22: International Conference on High Performance Computing in Asia-Pacific Region

Performance Portability frameworks are becoming more central and essential in heterogeneous computing systems. However, the developer toolbox lacks the tools to assess the performance portability degree of these frameworks.

This article presents a new ...
Evaluation of directive-based performance portable programming models

We present an extended exploration of the performance portability of directives provided by OpenMP 4 and OpenACC to program various types of node architectures with attached accelerators. To do this, we use examples of algorithms with varying ...
Evaluation of a performance portable lattice Boltzmann code using OpenCL
IWOCL '14: Proceedings of the International Workshop on OpenCL 2013 & 2014

With the advent of many-core computer architectures such as GPGPUs from NVIDIA and AMD, and more recently Intel's Xeon Phi, ensuring performance portability of HPC codes is potentially becoming more complex. In this work we have focused on one important ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

PPoPP '19: Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming

February 2019

472 pages

ISBN:9781450362252

DOI:10.1145/3293883

General Chair:
Jeff Hollingsworth
University of Maryland
,
Program Chair:
Idit Keidar
Technion, Israel

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.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 February 2019

Check for updates

Author Tags

Qualifiers

Tutorial

Conference

PPoPP '19

Sponsor:

PPoPP '19: 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

February 16 - 20, 2019

District of Columbia, Washington

Acceptance Rates

PPoPP '19 Paper Acceptance Rate 29 of 152 submissions, 19%;

Overall Acceptance Rate 230 of 1,014 submissions, 23%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

21
Total Citations
View Citations
520
Total Downloads

Downloads (Last 12 months)88
Downloads (Last 6 weeks)3

Reflects downloads up to 19 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Heroux MValero-Lara PLee SGonzalez-Tallada MDenny JTeranishi KVetter J(2024)Enhancing Kokkos with OpenACCInternational Journal of High Performance Computing Applications10.1177/1094342024126198738:5(409-426)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1177/10943420241261987
Valero-Lara PLee SDenny JTeranishi KVetter JGonzalez-Tallada M(2024)sKokkos: Enabling Kokkos with Transparent Device Selection on Heterogeneous Systems using OpenACCProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3635035.3635043(23-34)Online publication date: 18-Jan-2024
https://dl.acm.org/doi/10.1145/3635035.3635043
Crisci LCarpentieri LCosenza BAccordi GGadioli DVitali EPalermo GBeccari A(2024)Enabling performance portability on the LiGen drug discovery pipelineFuture Generation Computer Systems10.1016/j.future.2024.03.045158:C(44-59)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.future.2024.03.045
Monil MMiniskar NTeranishi KVetter JValero-Lara P(2023)MatRIS: Multi-level Math Library Abstraction for Heterogeneity and Performance Portability using IRIS RuntimeProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624184(1081-1092)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624184
Valero-Lara PVetter JHenriksen TSinkarovs A(2023)A MultiGPU Performance-Portable Solution for Array Programming Based on KokkosProceedings of the 9th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3589246.3595369(1-12)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3589246.3595369
Moses WIvanov IDomke JEndo TDoerfert JZinenko ODehnavi MKulkarni MKrishnamoorthy S(2023)High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel ConstructsProceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3572848.3577475(119-134)Online publication date: 25-Feb-2023
https://dl.acm.org/doi/10.1145/3572848.3577475
Hayashi AAdams AYoung JMcCaskey ADumitrescu ESarkar VConte T(2023)Enabling Multi-threading in Heterogeneous Quantum-Classical Programming Models2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW59300.2023.00090(509-516)Online publication date: May-2023
https://doi.org/10.1109/IPDPSW59300.2023.00090
Miniskar NHaque Monil MValero-Lara PLiu FVetter J(2023)IRIS-DMEM: Efficient Memory Management for Heterogeneous Computing2023 IEEE High Performance Extreme Computing Conference (HPEC)10.1109/HPEC58863.2023.10363512(1-7)Online publication date: 25-Sep-2023
https://doi.org/10.1109/HPEC58863.2023.10363512
Valero-Lara PKim JVetter J(2023)A Portable and Heterogeneous LU Factorization on IRISEuro-Par 2022: Parallel Processing Workshops10.1007/978-3-031-31209-0_2(17-31)Online publication date: 2-May-2023
https://doi.org/10.1007/978-3-031-31209-0_2
Valero-Lara PLee SGonzalez-Tallada MDenny JVetter J(2022)KokkACC: Enhancing Kokkos with OpenACC2022 Workshop on Accelerator Programming Using Directives (WACCPD)10.1109/WACCPD56842.2022.00009(32-42)Online publication date: Nov-2022
https://doi.org/10.1109/WACCPD56842.2022.00009
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

On the Performance Portability of OpenACC, OpenMP, Kokkos and RAJA

Evaluation of directive-based performance portable programming models

Evaluation of a performance portable lattice Boltzmann code using OpenCL