cs.DC · 2026-09-16 · No. 115

Distributed, Parallel, and Cluster Computing, 2026-09-16.

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

01 — The papers

7 entries
  1. 01

    DS2-Based Cross-Data-Space Interoperability for Precision Agriculture

    Katerina Kyriakou, Ilias Syrigos, Ioannis Moutsinas, Panagiotis Tzimotoudis, Thanasis Korakis

    cs.DC

    Despite the strategies of modern precision agriculture to leverage the integration of legacy agricultural systems, the challenges of IoT data fragmentation, farmers' sovereignty preservation, and limited interoperability still persist. This paper presents our work, conducted within the Horizon Europe DS2 project (DataSpace, DataShare 2.0), that applies an interoperability-oriented framework supporting participants of different agricultural...

    arxiv.org/abs/2609.17185 · PDF

  2. 02

    Byzantine Reliable Broadcast with Causal Ordering

    Mariarosaria Barbaraci, Christian Cachin

    cs.DC

    Reliable and total-order broadcasts in the Byzantine-fault model are well studied, but adding causal order has received comparatively little attention, largely due to the complexity that stems from actions of Byzantine processes. Existing solutions almost exclusively build causal ordering on top of total-order broadcast. The combination of causal order with reliable broadcast remains rare, and the few solutions that exist adopt the classical...

    arxiv.org/abs/2609.17074 · PDF

  3. 03

    Nested Parallel von Neumann Architecture and Nested BSP

    Heng Liao

    cs.DC · cs.AR

    Large-scale AI computing is no longer a contest of ''one stronger processor,'' but of how an army of processors under one command can still be one computer. This paper offers two interlocking extensions. First, extend BSP to Nested BSP. The Turing machine describes computation as a single tape, in sequence. A million processors need not a longer tape, but a battle plan nested layer within layer: at every layer, parallel work, barrier,...

    arxiv.org/abs/2609.16787 · PDF

  4. 04

    The Price of Random Access: Measuring Block Granularity Across Four Compressed Formats

    Yakiv Shavidze

    cs.DC · cs.DS

    Random access into compressed data is normally bought with density. We measure the exchange rate. Across four formats and nine axes on a common corpus, the cost of cutting a 254 MB archive into independently addressable 16 KiB units is 1.632% of the archive for an absolute-offset format against 6.57% for seekable zstd, and the gap widens as the unit shrinks: at 4 KiB, 5.33% against 10.06%. Because the cost is small, several properties follow...

    arxiv.org/abs/2609.16731 · PDF

  5. 05

    DeepShare: Assurance-Driven Deep Learning Job Scheduling for Multi-Tenant Clusters

    Jinghao Wang, Yihang Zhou, Xiao Zhou, Xinlei Zheng, Xiaoyang Sun, Tianyu Wo, Chunming Hu, Renyu Yang

    cs.DC

    Multi-tenant GPU clusters frequently remain underutilized even when tenants experience long queueing delays, because quota control, queue ordering, preemption, and GPU sharing are driven by different local signals. We present DeepShare, a scheduler that uses a continuous tenant-assurance signal to coordinate these decisions at runtime. DeepShare combines elastic quota borrowing, tenant-specific runtime prediction, cost-aware best-effort...

    arxiv.org/abs/2609.16682 · PDF

  6. 06

    XMPIaaS: Towards Cloud Native MPI via Cooperative Process Migration

    Shunyu Yao, Dimitrios S. Nikolopoulos, Ali R. Butt

    cs.DC

    Message Passing Interface (MPI) has been the dominant programming model for High Performance Computing (HPC) for three decades, and as HPC workloads increasingly migrate to cloud infrastructure for scalability and cost efficiency, MPI applications must contend with an execution environment fundamentally unlike traditional supercomputers: ephemeral resources, dynamic pricing and preemptable instances. In such a volatile setting, the ability to...

    arxiv.org/abs/2609.16531 · PDF

  7. 07

    PipeSwift: Revisiting Pipeline Parallelism for Large-Scale Completion-Oriented Agentic Serving

    Shiju Wang, Fei Ren, Fangcheng Fu, Zhanhong Tan, Kairui Li, Jingwei Cai, Kaisheng Ma

    cs.DC

    LLM agents execute long-horizon workflows where each model response determines the progress of subsequent tool interactions and environment transitions. Unlike chatbot serving, where TTFT and TPOT SLO constraints are critical, agentic workloads are increasingly governed by completion time. This shift challenges existing LLM serving designs, which are optimized around token-level SLOs. We revisit scheduling and parallelism under this...

    arxiv.org/abs/2609.16491 · PDF

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