Acknowledgement
본 논문은 한국전자통신연구원 내부연구개발사업 대규모 데이터 처리 응용 성능 향상을 위한 새로운 메모리 연결망(CXL) 기술 기반 MPI 분산병렬처리 구조 연구 및 성능분석(23YS1700)의 지원을 받아 수행된 연구임.
References
- J. Hoffmann et al., "Training compute-optimal large language models," arXiv preprint, CoRR, 2022, arXiv: 2203.15556.
- J.A. Baktash and M. Dawodi, "Gpt-4: A review on advancements and opportunities in natural language processing," arXiv preprint, CoRR, 2023, arXiv: 2305.03195.
- C. Guo et al., "Exploring the benefits of resource disaggregation for service reliability in data centers," IEEE Trans. on Cloud Comput., vol. 11, no. 2, 2022, pp. 1651-1666. https://doi.org/10.1109/TCC.2022.3151923
- I.H. Chung, B. Abali, and P. Crumley, "Towards a composable computer system," in Proc. HPC Asia 2018, (Tokyo Japan), Jan. 2018, pp. 137-147.
- MemVerge: The Road to Endless Memory, https://www.youtube.com/watch?v=rO4PdTAwLTY&t=622s
- [CES 2023 Innovation Award] Publishing the Boundaries of Memory, https://semiconductor.samsung.com/emea/news-events/tech-blog/pushing-the-boundaries-of-memory-samsung-goes-beyond-hardware-to-become-total-solution-provider-with-cxl-memory-expander/
- SK hynix CXL Memory, https://news.skhynix.com/sk-hynix-develops-ddr5-dram-cxltm-memory-to-expand-the-cxl-memory-ecosystem/
- Enfabrica: Scaling CXL Memory Using High Speed Networking, https://www.youtube.com/watch?v=YdJWhqeT5DM&t=919s
- Xconn CXL Switches: Enablers of More Advanced HPC and AI/ML Cloud Computing, https://www.youtube.com/watch?v=VvKEHq3xjUw&list=PLsf8NUp2sz_iF3X4s_qazc8c_vYnlAVXv&index=4
- J. Sim et al., "Computational CXL-memory solution for accelerating memory-intensive applications," IEEE Comput. Archit. Lett., vol. 22, no. 1, 2022, pp. 5-8. https://doi.org/10.1109/LCA.2022.3226482
- Y. Fridman et al., "CXL Memory as Persistent Memory for disaggregated HPC: A practical approach," arXiv preprint, CoRR, 2023, arXiv: 2308.10714.
- D. Lee et al., "Elastic use of far memory for In-memory database management systems," in Proc. DaMoN 2023, (Seattle, WA, USA), June 2023, pp. 35-43.
- Y. Sun et al., "Demystifying CXL memory with genuine CXL-ready systems and devices," in Proc. MICRO 2023, (Toronto, Canada), Oct. 2023, pp. 105-121.
- K. Kim et al., "SMT: Software-defined memory tiering for heterogeneous computing systems with CXL memory expander," IEEE Micro, vol. 43, no. 2, 2023, pp. 20-29.
- H. Li et al., "Pond: CXL-based memory pooling systems for cloud platforms," in Proc. ASPLOS 2023, vol. 2, (Vancouver, Canada), Mar. 2023, pp. 574-587.
- D. Gouk et al., "Memory pooling with cxl," IEEE Micro, vol. 43, no. 2, 2023, pp. 48-57.
- M. Kwon et al., "Failure tolerant training with persistent memory disaggregation over CXL," IEEE Micro, vol. 43, no. 2, 2023, pp. 66-75.
- Flight Simulator, https://memverge.com/memverge-and-sk-hynix-accelerate-memory-pooling-and-sharing-software-development-with-cxl-flight-simulator/
- M. Ha et al., "Dynamic capacity service for improving CXL pooled memory efficiency," IEEE Micro, vol. 43, no. 2, 2023, pp. 39-47. https://doi.org/10.1109/MM.2023.3237756
- Jonathan Cameron's QEMU Working Fork, https://gitlab.com/jic23/qemu
- Y. Yang et al., "CXLMemSim: A pure software simulated CXL. mem for performance characterization," arXiv preprint, CoRR, 2023, arXiv: 2303.06153.
- Scalable Memory Development Kit(SMDK) v1.5, https://github.com/OpenMPDK/SMDK
- HMSDK, https://github.com/skhynix/hmsdk
- MemVerge Project Gismo: Global IO-free Shared Memory Objects, https://www.youtube.com/watch?v=D66W7eqFbhc
- Ray, https://www.ray.io/ray-sgd
- Timeplus, https://www.timeplus.com/
- MemVerge Memory Viewer CXL and Memory Machine CXL, https://www.youtube.com/watch?v=cwZCORGjCsM
- GII Korea, "세계의 CXL 컨트롤러 IP 시장 분석," 2023, https://www.giikorea.co.kr/report/qyr1215847-global-cxl-controller-ip-market-research-report.html