Abstract
In the landscape of High-Performance Computing (HPC), the quest for efficient and scalable memory solutions remains paramount. The advent of Compute Express Link (CXL) introduces a promising avenue with its potential to function as a Persistent Memory (PMem) solution in the context of disaggregated HPC systems. This paper presents a comprehensive exploration of CXL memory's viability as a candidate for PMem, supported by physical experiments conducted on cutting-edge multi-NUMA nodes equipped with CXL-attached memory prototypes. Our study not only benchmarks the performance of CXL memory but also illustrates the seamless transition from traditional PMem programming models to CXL, reinforcing its practicality. To substantiate our claims, we establish a tangible CXL prototype using an FPGA card embodying CXL 1.1/2.0 compliant endpoint designs (Intel FPGA CXL IP). Performance evaluations, executed through the STREAM and STREAM-PMem benchmarks, showcase CXL memory's ability to mirror PMem characteristics in App-Direct and Memory Mode while achieving impressive bandwidth metrics with Intel 4th generation Xeon (Sapphire Rapids) processors. The results elucidate the feasibility of CXL memory as a persistent memory solution, outperforming previously established benchmarks. In contrast to published DCPMM results, our CXL-DDR4 memory module offers comparable bandwidth to local DDR4 memory configurations, albeit with a moderate decrease in performance. The modified STREAM-PMem application underscores the ease of transitioning programming models from PMem to CXL, thus underscoring the practicality of adopting CXL memory. The sources of this work are available at: https://github.com/Scientific-Computing-Lab-NRCN/STREAMer.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 |
| Publisher | Association for Computing Machinery |
| Pages | 983-994 |
| Number of pages | 12 |
| ISBN (Electronic) | 9798400707858 |
| DOIs | |
| State | Published - 12 Nov 2023 |
| Externally published | Yes |
| Event | 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 - Denver, United States Duration: 12 Nov 2023 → 17 Nov 2023 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 12/11/23 → 17/11/23 |
Bibliographical note
Publisher Copyright:© 2023 ACM.
Funding
This work was supported by Pazy grant 226/20, Israel Science Foundation grant 22/1425, the Lynn and William Frankel Center for Computer Science, and Intel Corporation (oneAPI Center of Excellence program). Computational support was provided by the NegevHPC project [54] and Intel Developer Cloud [23]. The authors would like to thank Gabi Dadush, Israel Hen, and Emil Malka for their hardware support on NegevHPC. The authors also want to thank Jay Mahalingam and Guy Tamir of Intel for their great help in forming this collaboration.
| Funders | Funder number |
|---|---|
| Lynn and William Frankel Center for Computer Science | |
| Intel Corporation | |
| Israel Science Foundation | 22/1425 |
Keywords
- CXL
- HPC
- Intel Optane DCPMM
- Memory disaggregation
- Persistent Memory (PMem)
- STREAM
- STREAM-PMem
- STREAMer