cs.DC · 2026-05-25 · No. 9

Distributed, Parallel, and Cluster Computing, 2026-05-25.

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

Enhancing Energy Efficiency in Scientific Workflows through CFD based PIVAEs

Ali Zahir, Ashiq Anjum, Mark Wilkinson, Jeyan Thiyagalingam

cs.DC

The growing complexity and scale of scientific workflows in high performance computing (HPC) environments have led to significant challenges in managing energy consumption without compromising computational performance. Traditional scheduling strategies often fail to account for the complex interplay between thermal dynamics, workload diversity, and system scalability, leading to inefficient and unsustainable energy usage. This paper...

arxiv.org/abs/2605.23850 · PDF
02

HyperParallel-MoE: Multi-Core Interleaved Scheduling for Fast MoE Training on Ascend NPUs

Zewen Jin, Congkun Ai, Guangpeng Zhang, Hanbo Zhang, Haoran Wang, Shihan Xiao, Da Lei, Xuefeng Jin, Teng Su, Cheng Li

cs.DC

Modern Mixture-of-Experts (MoE) models increasingly rely on large-scale AI accelerator clusters for efficient training. Ascend NPUs expose heterogeneous on-chip compute resources, including matrix-oriented AIC units and vector-oriented AIV units with explicit cross-queue synchronization support. However, existing training frameworks largely execute MoE operators in a serialized kernel-by-kernel manner, leaving substantial heterogeneous...

arxiv.org/abs/2605.23764 · PDF
03

Flare: Leveraging Serverless Elasticity to Absorb Microservice Load Spikes

Dilina Dehigama, Shyam Jesalpura, David Schall, Antonios Katsarakis, Marios Kogias, Rakesh Kumar, Boris Grot

cs.DC

Online services strive to maintain application responsiveness even when the traffic is unpredictable and fluctuating. Today's online services are commonly deployed as chains of microservices, each microservice packaged as one or more containers inside virtual machines (VMs). While performant and affordable when the load is steady, VM-based deployments are known to be slow to scale when the load spikes, resulting in degraded performance for...

arxiv.org/abs/2605.23707 · PDF
04

AMP: Arc Multi-Proposer Protocol with Bounded Inclusion Guarantees

Daniel Cason, Gordon Liao, Sergio Mena, Nenad Milošević, Adi Seredinschi, Alessandro Sforzin, João Sousa, Preston Vander Vos

cs.DC

Blockchain systems that settle financial transactions face a structural tension: the single validator that assembles each block holds unilateral power over transaction inclusion and ordering. Traditional markets curb this very power through front-running and market-manipulation laws. Regulators have flagged the absence of such rules as a first-order concern for blockchain-based financial infrastructure. In response, we introduce AMP, a...

arxiv.org/abs/2605.23677 · PDF
05

Herring: Parallel Batch-Order-Fairness on DAG-based Blockchain Consensus

Marko Putnik, Jérémie Decouchant

cs.DC

Transaction ordering attacks extract billions of dollars annually from decentralized finance users in the form of Maximal Extractable Value (MEV). Byzantine Fault-Tolerant (BFT) consensus protocols guarantee total order but place no constraint on how that order is chosen, leaving the door open for adversarial reordering. Batch-order-fairness (batch-OF) protocols close this gap, but existing designs pay a steep performance price for this...

arxiv.org/abs/2605.23648 · PDF
06

Multi-Factor Trust-Driven Secure Communication Model for Cloud-Based Digital Twins

Deepika Saxena, Ashutosh Kumar Singh

cs.DC

Cloud-based Digital Twin (DT) platforms enable real-time monitoring, simulation, and collaborative decision-making across distributed clients. However, ensuring secure and trustworthy communication remains a critical challenge due to heterogeneous client behavior, resource contention, and evolving adversarial threats. This paper proposes the Multi-Factor Trust-Driven Secure Communication (MT-SeCom) framework to enforce resilient and...

arxiv.org/abs/2605.23566 · PDF
07

Multi-Round Visibility: A Post-Consensus Ordering Layer for DAG-Based BFT

Pengkun Ren, Dong Hai, Nasrin Sohrabi, Zahir Tari

cs.DC

Directed acyclic graph (DAG)-based Byzantine Fault-Tolerant (BFT) protocols achieve high throughput by decoupling dissemination from agreement and allowing many vertices to be committed concurrently. This same concurrency, however, weakens ordering evidence at the execution boundary: once units are committed in a shared DAG frontier, their final linearization is driven by traversal or deterministic tie-breaking rather than verifiable...

arxiv.org/abs/2605.23432 · PDF
08

AlignedServe: Orchestrating Prefix-aware Batching to Build a High-throughput and Computing-efficient LLM Serving System

Fengyao Bai, Hongbin Zhang, Zhitao Chen, Jiangsu Du, Zhiguang Chen, Yutong Lu

cs.DC

High-throughput inference serving is essential for applications built on large language models (LLMs). Existing serving frameworks reduce request-level and batch-level bubbles through batching and scheduling, but often overlook bubbles within each decode iteration. Tokens generated in the same iteration may incur different costs because they depend on KV caches of different lengths; tokens with long KV caches can become bottlenecks and delay...

arxiv.org/abs/2605.23389 · PDF
09

XWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms

Tella Rajashekhar Reddy, Atharva Deshmukh, Liangcheng Yu, Chaojie Zhang, Mike Shepperd, Rohan Gandhi, Anjaly...

cs.DC · cs.AI · cs.NI

AI power demand is growing at an unprecedented rate while power grids are often ailing and struggle to keep up. Grid expansion comes with high capital expenditure and long-distance transmission losses, yet there is abundant renewable energy at the source, just not matched to demand. This paper proposes a complementary AI infrastructure deployment model, AI Greenferencing, that brings modular AI compute to renewable energy sources, focusing on...

arxiv.org/abs/2605.23348 · PDF
10

Orbax: Distributed Checkpointing with JAX

Colin Gaffney, Shutong Li, Daniel Ng, Anastasia Petrushkina, Niket Kumar, Adam Cogdell, Mridul Sahu, Yaning Liang,...

cs.DC · cs.LG

In a landscape of high-performance distributed ML systems, JAX has emerged as a framework of choice. However, JAX's modular design philosophy leaves it without a standardized checkpointing solution. In this paper, we introduce Orbax, a modular, JAX-native checkpointing library that abstracts the complexities of distributed accelerator systems while also providing flexibility for user-friendly checkpoint manipulations throughout the ML model...

arxiv.org/abs/2605.23066 · PDF
11

AI-Driven Multi-Region Provisioning for Cloud Services Using Spot Fleets

Javier Fabra, Enrique Molina-Giménez, Pedro García-López

cs.DC

Cloud service platforms increasingly rely on elastic infrastructures to support dynamic workloads. Spot instances provide discounted computing resources but introduce uncertainty due to dynamic pricing, resource availability, and interruption risks that vary across geographical regions. In Amazon Web Services, the EC2 Spot Service simplifies fleet provisioning through allocation strategies, but it cannot estimate fleet costs before deployment...

arxiv.org/abs/2605.22778 · PDF

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