Streamlining CXL Adoption for Hyperscale Efficiency (2404.03551v1)
Abstract: In our exploration of Composable Memory systems utilizing CXL, we focus on overcoming adoption barriers at Hyperscale, underscored by economic models demonstrating Total Cost of Ownership (TCO). While CXL addresses the pressing memory capacity needs of emerging Hyperscale applications, the escalating demands from evolving use cases such as AI outpace the capabilities of current CXL solutions. Hyperscalers resort to software-based memory (de)compression technology, alleviating memory capacity, storage, and network constraints but incurring a notable "Tax" on Compute CPU cycles. As a pivotal guide to the CXL community, Hyperscalers have formulated the groundbreaking Open Compute Project (OCP) Hyperscale CXL Tiered Memory Expander specification. If implemented, this specification lowers TCO adoption barriers, enabling diverse CXL deployments at both Hyperscaler and Enterprise levels. We present a CXL integrated solution, aligning with the aforementioned specification, introducing an energy-efficient, scalable, hardware-accelerated, Lossless Compressed Memory CXL Tier. This solution, slated for mid-2024 production and open for integration with Memory Expander controller manufacturers, offers 2-3X CXL memory compression in nanoseconds, delivering a 20-25% reduction in TCO for end customers without requiring additional physical slots. In our discussion, we pinpoint areas for collaborative innovation within the CXL Community to expedite software/hardware advancements for CXL Tiered Memory Expansion. Furthermore, we delve into unresolved challenges in Pooled deployment and explore potential solutions, collectively aiming to make CXL adoption a "No Brainer" at Hyperscale.
- George Apostol. 2022. Using Pools of Shared Resources to Lower Latency and Improve System Performance. https://drive.google.com/file/d/1cZGC64WFY491-Jrf7jAHy64xR-YyDIOD/view
- Design Tradeoffs in CXL-Based Memory Pools for Public Cloud Platforms. IEEE Micro 43, 2 (mar 2023), 30–38. https://doi.org/10.1109/MM.2023.3241586
- OCP Hyperscale CXL Tiered Memory Expander Specification,Revision 1 Version 1.0 Base Specification, Template v1.2, Effective October 27, 2023. https://www.opencompute.org/documents/hyperscale-cxl-tiered-memory-expander-for-ocp-base-specification-1-pdf
- Characterization of Data Compression in Datacenters. In 2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). 1–12. https://doi.org/10.1109/ISPASS57527.2023.00010
- CDPU: Co-designing Compression and Decompression Processing Units for Hyperscale Systems. In Proceedings of the 50th Annual International Symposium on Computer Architecture (Orlando, FL, USA) (ISCA ’23). Association for Computing Machinery, New York, NY, USA, Article 39, 17 pages. https://doi.org/10.1145/3579371.3589074
- A Case Against CXL Memory Pooling. In Proceedings of the 22nd ACM Workshop on Hot Topics in Networks (HotNets ’23). Association for Computing Machinery, New York, NY, USA, 18–24. https://doi.org/10.1145/3626111.3628195
- Brian Will. 2023. Intel® QuickAssist Technology Zstandard Plugin, an External Sequence Producer for Zstandard. https://community.intel.com/t5/Blogs/Tech-Innovation/Artificial-Intelligence-AI/Intel-QuickAssist-Technology-Zstandard-Plugin-an-External/post/1509818