cs.DC · 2026-07-22 · No. 61

Distributed, Parallel, and Cluster Computing, 2026-07-22.

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

01 — The papers

11 entries

01

Keeping the Cache Warm Pays: Keepalive Economics for Agentic Workloads

Maxim Khailo

cs.DC

Frontier LLM providers cache a prompt's processed prefix so that a follow-up request sharing it pays ~10% of the input price and skips most of the prefill latency. Agentic workloads systematically destroy this benefit: the agent sends a request, runs a tool or waits for approval for minutes, and by the time the follow-up is sent the cached prefix has been evicted, so the agent pays the full prefill again. A client-side keepalive, replaying...

arxiv.org/abs/2607.19214 · PDF
02

ARBITER: Guarded Agentic Control for SLO-Oriented Kubernetes Remediation

Pooyan Habibi, Alberto Leon-Garcia

cs.DC

Maintaining service-level objectives (SLOs) on Kubernetes microservices remains difficult because autoscalers observe coarse resource metrics, recent SLO controllers often depend on custom telemetry, and unconstrained agentic operators cannot safely mutate production clusters. We present ARBITER, a guarded control plane for SLO-oriented Kubernetes remediation. ARBITER builds an OpenTelemetry-native causal resource graph, assembles bounded...

arxiv.org/abs/2607.19182 · PDF
03

Coherence in Control: Bridging Many-Core Mapping and Routing through Cost Unification

Guochu Xiong, Xiangzhong Luo, Weichen Liu

cs.DC

The rapid growth of data-intensive applications increases communication demands in many-core systems, where cache coherence, while essential for correct communication and data consistency, introduces substantial overhead due to frequent data sharing and coherence activities. As system scale and workload complexity grow, the resulting coherence traffic intensifies communication pressure, making the co-optimization of task mapping and routing...

arxiv.org/abs/2607.19158 · PDF
04

A Scalable Pattern Mining Workflow for Interpretable Machine Log Analysis in High-Performance Computing Environments

Shilpika Shilpika, Bethany Lusch, Eric Pershey, Carlo Graziani, Venkatram Vishwanath, Michael E. Papka

cs.DC

Modern supercomputers housed in High Performance Computing (HPC) environments generate massive volumes of log data daily, revealing intricate information and performance metrics about these complex systems. The sheer size and heterogeneous nature of HPC logs, especially text data, pose significant challenges for traditional analytical techniques. Consequently, more complex workflows are necessary for pattern extraction when analyzing these...

arxiv.org/abs/2607.19143 · PDF
05

Enabling Multi-Dimensional Distributed Trace Comparison with Contrast

Vaastav Anand, Rodrigo Fonseca, Jonathan Mace, Antoine Kaufmann

cs.DC

Diagnosis using distributed traces is fundamentally a comparative task: operators seek to understand how an anomalous execution differs from expected behavior, how a deployment changes system execution, or how two individual executions differ. Trace comparison is challenging because useful differences between executions can manifest across multiple dimensions, and no single diagnostic interface is effective at capturing all of them. Moreover,...

arxiv.org/abs/2607.19102 · PDF
06

InstantInfer: Enabling Fast LLM Cold Start with Communicating Finite Automata

Yitao Yuan, Yongchao He, Shaoke Fang, Wenfei Wu

cs.DC

Cold starts in large language model (LLM) inference services significantly affect user experience, yet they remain inefficient due to sequential initialization and a massive number of fine-grained I/O requests issued by complex software components. Although refactoring the program can yield advantages such as concurrent execution and I/O merging, this approach is error-prone and carries correctness risks when dealing with massive,...

arxiv.org/abs/2607.18957 · PDF
07

A User-oriented Portable, Reproducible, and Scalable Software Ecosystem

Alfio Lazzaro, Utz-Uwe Haus, Sandrine Charousset, Nina Mujkanovic

cs.DC

It is normal for scientists to perform their research on a diverse set of hardware, ranging from laptops and workstations to supercomputers and cloud resources. The standard scenario requires a mix of these resources. In this paper we describe a software ecosystem that enables users to rely on the same development environment for running their workflows across the different computational resources. We describe a modular, unified command-line...

arxiv.org/abs/2607.18929 · PDF
08

Mapping Without Graphs: Learning Coherence Traffic for Task Placement

Guochu Xiong, Tianrui Ma, Weichen Liu

cs.DC

Cache coherence is essential for communication in many-core Network-on-Chip (NoC)-based systems. As application scale and complexity increase, efficiently managing communication becomes increasingly challenging, making task mapping a key optimization technique. However, existing task mapping approaches suffer from two major limitations. First, they rely on predefined task graphs whose dependencies are typically derived from program structure...

arxiv.org/abs/2607.18879 · PDF
09

Unstructured Hydrodynamics on Spatial Dataflow Architectures: A Joint Code and Data Decomposition Approach

Piotr Luczynski, Tal Ben-Nun, Leighton Wilson, Brian Van Essen

cs.DC

Spatial Dataflow Architectures are an emerging hardware pattern in high-performance computing, whose mesh-connected fixed-memory processing elements are tailored for structured grid kernels with two-dimensional neighborhoods. However, practical multiphysics codes are often computed on unstructured grids, which induce indirect memory accesses and high-dimensional communication patterns, making them infeasible to directly map onto said...

arxiv.org/abs/2607.18650 · PDF
10

Searching for Plans You Can Actually Build: A Realizability-Aware Full-Space Optimizer for MoE Training and Serving

Quan Yuan, Jie Zhao

cs.DC

Mixture-of-Experts (MoE) systems split a program's plan space in two: the space a cost model can rank, and the smaller space a real toolchain can actually build. Automatic optimizers rank the first and silently assume the two coincide -- so they can return a plan that is optimal on paper and impossible to emit. We present moefs, a realizability-aware full-space optimizer for MoE training and serving that makes deployment realizability a...

arxiv.org/abs/2607.18631 · PDF
11

What Governs Decode Throughput in Absolute-Offset GPU LZ77? A Work-Granularity Mechanism and an Encode-Time Min-Match-Length Lever

Yakiv Shavidze

cs.DC · cs.PF

The ACEAPEX line of work established a lossless LZ77 format whose back-references are absolute output positions, giving parallel, compressed-resident GPU decode with sub-millisecond region seek. What it did not establish is what governs the decode throughput of such a format, or how to improve it. This paper answers both. Through controlled ablations on an NVIDIA H100 we show that decode throughput is governed not by occupancy, compute,...

arxiv.org/abs/2607.18541 · PDF

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