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Emerging Compute Express Link (CXL) enables cost-efficient memory expansion beyond the local DRAM of processors. While its CXL$.$mem protocol provides minimal latency overhead through an optimized protocol stack, frequent CXL memory…

The substantial memory requirements of Large Language Models (LLMs), particularly for long-context fine-tuning, have renewed interest in CPU offloading to augment limited GPU memory. However, as context lengths grow, relying on CPU memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-31 Yong-Cheng Liaw , Shuo-Han Chen

CXL has been the emerging technology for expanding memory for both the host CPU and device accelerators with load/store interface. Extending memory coherency to the PCIe root complex makes the codesign more flexible in that you can access…

Hardware Architecture · Computer Science 2023-09-11 Yiwei Yang

Conventional heterogeneous computing systems built on PCIe interconnects suffer from inefficient fine-grained host-device interactions and complex programming models. In recent years, many proprietary and open cache-coherent interconnect…

Hardware Architecture · Computer Science 2026-01-13 Yanjing Wang , Lizhou Wu , Sunfeng Gao , Yibo Tang , Junhui Luo , Zicong Wang , Yang Ou , Dezun Dong , Nong Xiao , Mingche Lai

In GPU graph analytics, the use of external memory such as the host DRAM and solid-state drives is a cost-effective approach to processing large graphs beyond the capacity of the GPU onboard memory. This paper studies the use of Compute…

Heterogeneous memory technologies are increasingly important instruments in addressing the memory wall in HPC systems. While most are deployed in single node setups, CXL.mem is a technology that implements memories that can be attached to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-10 Stepan Vanecek , Matthew Turner , Manisha Gajbe , Matthew Wolf , Martin Schulz

The rise of serverless computing introduced a new class of scalable, elastic and widely available parallel workers in the cloud. Many systems and applications benefit from offloading computations and parallel tasks to dynamically allocated…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-23 Marcin Copik , Lukas Möller , Alexandru Calotoiu , Torsten Hoefler

Modern distributed file systems rely on uncoordinated, per node page caches that replicate hot data locally across the cluster. While ensuring fast local access, this architecture underutilizes aggregate cluster DRAM capacity through…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-22 Shai Bergman , Zhe Yang , Julien Eudine , Giorgio Negro , Onur Mutlu , Arash Tavakkol , Ji Zhang

Data lakes hold a growing amount of cold data that is infrequently accessed, yet require interactive response times. Serverless functions are seen as a way to address this use case since they offer an appealing alternative to maintaining…

Databases · Computer Science 2022-08-23 Simon Kassing , Ingo Müller , Gustavo Alonso

This paper proposes ScalePool, a novel cluster architecture designed to interconnect numerous accelerators using unified hardware interconnects rather than traditional long-distance networking. ScalePool integrates Accelerator-Centric Links…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-17 Hyein Woo , Miryeong Kwon , Jiseon Kim , Eunjee Na , Hanjin Choi , Seonghyeon Jang , Myoungsoo Jung

Compute eXpress Link (CXL) has emerged as a key enabler of memory disaggregation for future heterogeneous computing systems to expand memory on-demand and improve resource utilization. However, CXL is still in its infancy stage and lacks…

Emerging Technologies · Computer Science 2026-01-13 Yanjing Wang , Lizhou Wu , Wentao Hong , Yang Ou , Zicong Wang , Sunfeng Gao , Jie Zhang , Sheng Ma , Dezun Dong , Xingyun Qi , Mingche Lai , Nong Xiao

Modern AI workloads such as large language models (LLMs) and retrieval-augmented generation (RAG) impose severe demands on memory, communication bandwidth, and resource flexibility. Traditional GPU-centric architectures struggle to scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-15 Myoungsoo Jung

The continual increase of cores on server-grade CPUs raises demands on memory systems, which are constrained by limited off-chip pin and data transfer rate scalability. As a result, high-end processors typically feature lower memory…

Hardware Architecture · Computer Science 2025-11-18 Divya Kiran Kadiyala , Alexandros Daglis

Large-scale AI training and inference require hundreds of gigabytes to terabytes of DRAM with high peak to average utilization ratios, resulting in overprovisioning. In cloud computing, DRAM constitutes a significant share of the cost. Yet,…

Hardware Architecture · Computer Science 2026-05-28 Kaustav Goswami , Maryam Babaie , Hoa Nguyen , Venkatesh Akella , Jason Lowe-Power

The widening gap between processor speed and storage latency has made data movement a dominant bottleneck in modern systems. Two lines of storage-layer innovation attempted to close this gap: persistent memory shortened the latency…

Operating Systems · Computer Science 2026-04-06 Yiwei Yang , Yanpeng Hu , Yusheng Zheng , Estabon Ramos , Jianchang Su , Andi Quinn , Wei Zhang

CXL (Compute Express Link) enables multiple hosts to share byte-addressable memory with hardware cache coherence, but no existing filesystem exploits this for lock-free multi-host coordination. We present DaxFS, a Linux filesystem for CXL…

Operating Systems · Computer Science 2026-04-03 Cong Wang , Yiwei Yang , Yusheng Zheng

This review report discusses the cold start latency in serverless inference and existing solutions. It particularly reviews the ServerlessLLM method, a system designed to address the cold start problem in serverless inference for large…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-26 Himel Ghosh

Compute Express Link (CXL) emerges as a solution for wide gap between computational speed and data communication rates among host and multiple devices. It fosters a unified and coherent memory space between host and CXL storage devices such…

Public cloud providers seek to meet stringent performance requirements and low hardware cost. A key driver of performance and cost is main memory. Memory pooling promises to improve DRAM utilization and thereby reduce costs. However,…

This work introduces a GPU storage expansion solution utilizing CXL, featuring a novel GPU system design with multiple CXL root ports for integrating diverse storage media (DRAMs and/or SSDs). We developed and siliconized a custom CXL…