cs.DC · 2026-07-20 · No. 59

Distributed, Parallel, and Cluster Computing, 2026-07-20.

4 new papers in cs.DC. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

4 entries
  1. 01

    Every Microsecond Matters: Achieving Near Speed-of-Light Latency in GPU Collectives

    Siyuan Shen, Anton Korzh, John Bachan, Tiancheng Chen, Arnav Goel, Ludwig Schneider, Pouya Kousha, Zhenhao He,...

    cs.DC

    GPU collective communication is typically optimized for bandwidth, yet many emerging workloads are increasingly limited by latency. Long-context decode-heavy large language model (LLM) inference is a prime example, where serving large models requires multiple GPUs, and many small collectives lie directly on the critical path of token generation. Therefore, even microsecond of overhead can impact performance and cost. In this work, we study...

    arxiv.org/abs/2607.16100 · PDF

  2. 02

    JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models

    Haoran Sun, Wentao Zhang, Junyang Hua, Hedan Yang, Yongjian Guo, Yifei Zhang, Xiaolong Xiang, Mingxi Luo, Jing Long,...

    cs.DC · cs.AI · cs.SE

    The post-training of Vision-Language-Action (VLA) models is essential due to the diversity of simulators, robot embodiments, and task objectives. Existing compute services, whether offered as direct accelerator rental or batch-workload submission, typically allocate an exclusive set of GPU and CPU resources to a single tenant. While this paradigm maximizes client flexibility, it burdens users with infrastructure adaptation, and the fixed...

    arxiv.org/abs/2607.16074 · PDF

  3. 03

    Scalable LLM Agent Tool Access in the Cloud

    Mingxin Li, Enge Song, Yueshang Zuo, Xiaodong Liu, Rong Wen, Qiang Fu, Gianni Antichi, Jian He, Jing Tie, Zhou Shao,...

    cs.DC · cs.AI · cs.NI

    LLM agents increasingly rely on tool calling to act on external systems, and the Model Context Protocol (MCP) has quickly become its de facto interface. Operating MCP at cloud scale, however, becomes difficult. On the tool provider side, legacy services are not directly callable through MCP; the rapid protocol development also creates ongoing compatibility cost. On the agent side, the number of accessible tool is limited by the LLM context...

    arxiv.org/abs/2607.15593 · PDF

  4. 04

    FSZ: Breaking the Prediction-Throughput Trade-off in GPU Lossy Compression

    Jiajun Huang

    cs.DC · cs.PF

    Existing fast GPU error-bounded lossy compressors have achieved high throughput through pure-GPU single-kernel designs, but their compression ratios remain limited because they typically apply a fixed first-order predictor on independent blocks. We propose FSZ, a GPU error-bounded lossy compressor that redesigns the prediction stage with three mutually reinforcing algorithmic innovations to achieve both higher compression ratios and higher...

    arxiv.org/abs/2607.15413 · PDF

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