cs.DC · 2026-07-29 · No. 68

Distributed, Parallel, and Cluster Computing, 2026-07-29.

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

01 — The papers

5 entries
  1. 01

    Hermes: Low Tail-Latency Via Prefix Consensus

    Alejandro Ranchal-Pedrosa, Dakai Kang, Neil Giridharan, Dahlia Malkhi, Mohammad Sadoghi, Ben Marsh

    cs.DC · cs.CR

    Leader-based BFT protocols finalize through their leaders: a view whose leader is crashed or slow finalizes nothing, and the timeout that ends it admits no good setting. A conservative timeout turns every crashed leader into a long stall; an aggressive one voids the views of leaders that are merely slow. Either way the expired view is wasted, and this trade-off, not the good case, governs tail latency. Hermes makes expired views finalize....

    arxiv.org/abs/2607.25916 · PDF

  2. 02

    PowerScale: Energy-Efficient Geo-Distributed Model Training with Federated Datacenter Power

    Talha Mehboob, Zhe Xu, Michael Zink, David Irwin

    cs.DC

    The power demands of large-scale AI training increasingly exceed the capacity of any single data center, making geo-distributed training across power-constrained sites a practical necessity. Prior work optimizes such training mainly for time-to-accuracy using single-tier aggregation, where every site exchanges model updates directly with a central aggregator over the WAN each synchronization round, without accounting for the energy required...

    arxiv.org/abs/2607.25650 · PDF

  3. 03

    WASP: A Configurable Framework for Portable Stateful Serverless Applications

    Matteo Cenzato, Dario d'Abate, Arianna Dragoni, Giacomo Orsenigo, Luca Tosetti, Alessandro Margara

    cs.DC · cs.SE

    WebAssembly (WASM) is emerging as a lightweight alternative to containers for Function-as-a-Service (FaaS) across the edge-cloud continuum. However, existing WASM-based serverless platforms are tightly coupled to specific execution engines and predominantly designed for stateless workloads. This clashes with the heterogeneity of edge deployments, which demand support for stateful applications under diverse hardware and workload constraints....

    arxiv.org/abs/2607.25493 · PDF

  4. 04

    CW-Ghost: Search-Free Granularity Selection for Helper-Thread Prefetching via Capacity Windows

    Ya Zhang, Tong Lei, Yao Chen, Yonggang Che, Chuanfu Xu, Haozhong Qiu, Yusong Tan

    cs.DC

    Helper-thread prefetching hides the latency of irregular memory accesses by executing address dependency chains ahead of the main thread. However, its effectiveness depends on the range of future iterations covered by the helper thread. A fixed coverage range cannot consistently accommodate different workloads and processors, whereas exhaustively evaluating candidate configurations incurs substantial configuration cost. This paper presents...

    arxiv.org/abs/2607.25363 · PDF

  5. 05

    QCOEM: Quantum Cloud Orchestration with Evolutionary Multi-Objective Optimization

    Tam N. Pham, Hoa T. Nguyen, Quan Le-Trung

    cs.DC · cs.ET · quant-ph

    Quantum cloud platforms need to dynamically orchestrate workloads across heterogeneous quantum computation backends whose noise profiles, qubit topologies, and queues vary over time. Existing orchestrators use noise-agnostic heuristics that ignore backend-specific errors, causing reduced execution fidelity, load imbalance, and frequent rescheduling. To address these challenges, we propose QCOEM - a Quantum Cloud Orchestration framework that...

    arxiv.org/abs/2607.25358 · PDF

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