| Issue |
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|
|
|---|---|---|
| Article Number | 03035 | |
| Number of page(s) | 8 | |
| Section | Offline Computing | |
| DOI | https://doi.org/10.1051/epjconf/202125103035 | |
| Published online | 23 August 2021 | |
https://doi.org/10.1051/epjconf/202125103035
Performance of CUDA Unified Memory in CMS Heterogeneous Pixel Reconstruction
1 Fermi National Accelerator Laboratory, Batavia, IL, USA
* e-mail: matti@fnal.gov
** e-mail: kkwok@fnal.gov
Published online: 23 August 2021
The management of separate memory spaces of CPUs and GPUs brings an additional burden to the development of software for GPUs. To help with this, CUDA unified memory provides a single address space that can be accessed from both CPU and GPU. The automatic data transfer mechanism is based on page faults generated by the memory accesses. This mechanism has a performance cost, that can be with explicit memory prefetch requests. Various hints on the inteded usage of the memory regions can also be given to further improve the performance. The overall effect of unified memory compared to an explicit memory management can depend heavily on the application. In this paper we evaluate the performance impact of CUDA unified memory using the heterogeneous pixel reconstruction code from the CMS experiment as a realistic use case of a GPU-targeting HEP reconstruction software. We also compare the programming model using CUDA unified memory to the explicit management of separate CPU and GPU memory spaces.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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