cs.DC · 2026-09-10 · No. 111

Distributed, Parallel, and Cluster Computing, 2026-09-10.

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

01 — The papers

6 entries
  1. 01

    Avatar: Toward Autonomous End-to-End Orchestration of Scientific Workflows using LLMs

    Suman Raj, Hai Duc Nguyen, Haochen Pan, Ryan Chard, Kyle Chard, Ian Foster

    cs.DC · cs.MA

    Scientific workflow management (WMSs) systems automate execution, yet orchestrate using fixed, hand-tuned rules. LLM agents promise more autonomous orchestration, but it remains unclear where to introduce agentic reasoning, how to bound its risk, and when it actually helps. We present Avatar, an actor-based architecture comprising an orchestrator, an executor, and a provenance monitor. Each actor's decision policy is pluggable (rule-based or...

    arxiv.org/abs/2609.10509 · PDF

  2. 02

    Stencil Computation at the Intersection of AI and HPC

    Timothee Ewart, Mauricio Araya-Polo

    cs.DC

    Tensor compilers such as TinyTC and OpenAI Triton were originally developed for AI workloads, but the same tiling and memory abstractions can be applied to implement efficient high-order stencils for scientific and industrial applications. We demonstrate this for an 8th-order, 25-point acoustic stencil with boundary conditions over an a demanding-sized grid, targeting GPGPUs, where we compare the hardware-specialized TinyTC implementation...

    arxiv.org/abs/2609.10368 · PDF

  3. 03

    CEDD-optimizer: Enabling Cost-Efficient Dataset Distillation on Geographically Distributed Edge Systems

    Dai Liu, Eishi Arima, Martin Schulz

    cs.DC

    Centralized learning is a fundamental paradigm in modern AI, in which data are collected from distributed edge devices and aggregated at a central host for model training. However, this pipeline is often bottlenecked by the substantial communication overhead of data collection. Dataset Distillation (DD), with its high compression ratio, is therefore attractive for centralized learning on distributed data. Yet, the cost efficiency of DD in...

    arxiv.org/abs/2609.10151 · PDF

  4. 04

    Introvert Clustering for Distributed Graph Algorithms

    Yi-Jun Chang, Nima Dolatabadi

    cs.DC · cs.DS

    We introduce a graph decomposition primitive called introvert clustering, which strengthens standard low-diameter clustering by guaranteeing that every clustered vertex keeps at least a $\left(\frac12-\varepsilon\right)$-fraction of its relevant neighbors in its own cluster. Repeatedly applying this primitive yields a layered introvert network decomposition with $O(\log n)$ layers and weak diameter $O(\log n)$. We give two applications in the...

    arxiv.org/abs/2609.10044 · PDF

  5. 05

    Epoch: Compiling Diffusion Blocks for Sparse MoE Serving

    Jianian Zhu, Hang Wu, Yinghui Li, Haojie Wang, Ruixuan Li, Jidong Zhai

    cs.DC

    Diffusion language models generate text by refining a fixed-size block of token positions through many forward passes, a loop that does not match the per-forward execution unit used by most LLM serving systems. A dense MoE runtime binds all work to the refinement-iteration clock: it rebuilds similar routing structure on every forward, recomputes expert outputs for positions whose logits are already dead, and sends those positions through...

    arxiv.org/abs/2609.09748 · PDF

  6. 06

    Breaking Fault Lines: Unifying TEE-Assisted BFT Consensus in Partially Trusted Worlds

    Xiaoqing Wen, Tong Liu, Jianyu Niu, Jialin Li, Cong Wang, Yinqian Zhang, Chen Feng

    cs.DC

    This paper revisits TEE-assisted BFT under a universal partial-TEE model, where an arbitrary subset of replicas execute inside TEEs while the remaining replicas operate without hardware trust guarantees. We show that heterogeneous trust changes the structure of quorum formation and fault tolerance. In particular, we derive a tight resilience bound f < max {n/3, m/2}, where n is the total number of replicas and m is the number of TEE-enabled...

    arxiv.org/abs/2609.09742 · PDF

This edition is part of The Daily Abstract — cs.DC archive. Subscribe to receive these in your inbox each morning, automatically translated to Spanish, with reply-to-PDF: arxivdaily.ignorelist.com.

Colophon Set in Georgia, with system sans for interface chrome and a monospaced stack for code and paper identifiers. Sole accent: amber #D99C5E. Built and served on an always-free VM. The masthead is set 14% letterspaced because newspapers do that and it works.