Porting CMS Heterogeneous Pixel Reconstruction to Kokkos

Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several por...

Full description

Bibliographic Details
Main Authors: Kortelainen Matti J., Kwok Martin, Childers Taylor, Strelchenko Alexei, Wang Yunsong
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:EPJ Web of Conferences
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03034.pdf
id doaj-e0d10e2985b543608d89e88e9b82bb1e
record_format Article
spelling doaj-e0d10e2985b543608d89e88e9b82bb1e2021-08-26T09:27:25ZengEDP SciencesEPJ Web of Conferences2100-014X2021-01-012510303410.1051/epjconf/202125103034epjconf_chep2021_03034Porting CMS Heterogeneous Pixel Reconstruction to KokkosKortelainen Matti J.0Kwok Martin1Childers Taylor2Strelchenko Alexei3Wang Yunsong4Fermi National Accelerator LaboratoryFermi National Accelerator LaboratoryArgonne National LaboratoryFermi National Accelerator LaboratoryLawrence Berkeley National LaboratoryProgramming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several portability technologies on the market such as Alpaka, Kokkos, and SYCL. These technologies aim to improve the developer’s productivity by making it possible to use the same source code for many different architectures. In this paper we use heterogeneous pixel reconstruction code from the CMS experiment at the CERNL LHC as a realistic use case of a GPU-targeting HEP reconstruction software, and report experience from prototyping a portable version of it using Kokkos. The development was done in a standalone program that attempts to model many of the complexities of a HEP data processing framework such as CMSSW. We also compare the achieved event processing throughput to the original CUDA code and a CPU version of it.https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03034.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Kortelainen Matti J.
Kwok Martin
Childers Taylor
Strelchenko Alexei
Wang Yunsong
spellingShingle Kortelainen Matti J.
Kwok Martin
Childers Taylor
Strelchenko Alexei
Wang Yunsong
Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
EPJ Web of Conferences
author_facet Kortelainen Matti J.
Kwok Martin
Childers Taylor
Strelchenko Alexei
Wang Yunsong
author_sort Kortelainen Matti J.
title Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
title_short Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
title_full Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
title_fullStr Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
title_full_unstemmed Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
title_sort porting cms heterogeneous pixel reconstruction to kokkos
publisher EDP Sciences
series EPJ Web of Conferences
issn 2100-014X
publishDate 2021-01-01
description Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several portability technologies on the market such as Alpaka, Kokkos, and SYCL. These technologies aim to improve the developer’s productivity by making it possible to use the same source code for many different architectures. In this paper we use heterogeneous pixel reconstruction code from the CMS experiment at the CERNL LHC as a realistic use case of a GPU-targeting HEP reconstruction software, and report experience from prototyping a portable version of it using Kokkos. The development was done in a standalone program that attempts to model many of the complexities of a HEP data processing framework such as CMSSW. We also compare the achieved event processing throughput to the original CUDA code and a CPU version of it.
url https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03034.pdf
work_keys_str_mv AT kortelainenmattij portingcmsheterogeneouspixelreconstructiontokokkos
AT kwokmartin portingcmsheterogeneouspixelreconstructiontokokkos
AT childerstaylor portingcmsheterogeneouspixelreconstructiontokokkos
AT strelchenkoalexei portingcmsheterogeneouspixelreconstructiontokokkos
AT wangyunsong portingcmsheterogeneouspixelreconstructiontokokkos
_version_ 1721195832039964672