No Atomics, No Problem. Developing a RAG Pipeline for Shared CXL Memory

IF 4.9 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
IEEE Transactions on Computers Pub Date : 2026-04-01 Epub Date: 2026-02-24 DOI:10.1109/TC.2026.3667821
Alfred Bratterud;Gisle Dankel;Amin Farajianzadeh;John Groves;Chengyi Juan;Joshua Suetterlein;Andrés Márquez;Petter Gustad;Arnt Emil Ingulstad
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引用次数: 0

Abstract

We share early experiments with software development for shared CXL memory on the H3 Falcon C5022 CXL switch. We describe how the different stages in the development of a commercial RAG pipeline were impacted by the presence of CXL memory. All of Wikipedia is split into 46 million text passages which are embedded into a high-dimensional embedding space and subjected to heavy load in single- and multi-host experiments. We observe significant performance advantages available to DuckDB and Faiss without changing the software; we measure up to 12x latency reduction with real workloads and 40x reduction with synthetic workloads on CXL, compared to the same queries run with demand paging on NVMe. We explain the current challenges of working with two disjoint cache coherency domains and explain how the Fabric-Attached Memory File System (famfs) and famfs producer-consumer queues provide synchronization patterns without atomic operations on current x86 CPUs. We then discuss open challenges remaining for high performance atomics and locking mechanisms in shared memory. Lastly we show how famfs page-level interleaving enables near-linear throughput scaling when a second host serves queries from the same Faiss index on shared fabric-attached memory and how shared memory allocations can be orchestrated by Kubernetes in a full vertical RAG deployment.
没有原子,就没有问题。面向共享CXL内存的RAG管道开发
我们分享了在H3 Falcon C5022 CXL交换机上共享CXL内存的软件开发的早期实验。我们描述了商业RAG管道开发的不同阶段如何受到CXL内存的影响。所有维基百科被分成4600万个文本段落,嵌入到高维嵌入空间中,并在单主机和多主机实验中承受沉重的负载。我们观察到DuckDB和Faiss在不更改软件的情况下具有显著的性能优势;与在NVMe上使用需求分页运行相同的查询相比,我们测量到在CXL上使用真实工作负载减少了12倍的延迟,在合成工作负载上减少了40倍的延迟。我们解释了当前使用两个不相连的缓存一致性域所面临的挑战,并解释了Fabric-Attached Memory File System (famfs)和famfs生产者-消费者队列如何在当前x86 cpu上提供不需要原子操作的同步模式。然后讨论共享内存中的高性能原子和锁定机制仍然存在的挑战。最后,我们展示了当第二台主机在共享fabric附加内存上提供来自相同Faiss索引的查询时,fams页面级交错如何实现近线性吞吐量扩展,以及Kubernetes如何在完全垂直RAG部署中协调共享内存分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Computers
IEEE Transactions on Computers 工程技术-工程:电子与电气
CiteScore
6.60
自引率
5.40%
发文量
199
审稿时长
6.0 months
期刊介绍: The IEEE Transactions on Computers is a monthly publication with a wide distribution to researchers, developers, technical managers, and educators in the computer field. It publishes papers on research in areas of current interest to the readers. These areas include, but are not limited to, the following: a) computer organizations and architectures; b) operating systems, software systems, and communication protocols; c) real-time systems and embedded systems; d) digital devices, computer components, and interconnection networks; e) specification, design, prototyping, and testing methods and tools; f) performance, fault tolerance, reliability, security, and testability; g) case studies and experimental and theoretical evaluations; and h) new and important applications and trends.
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