Systems & Networks · Computer Science & AI
Distributed & Parallel Computing
The newest papers in Distributed & Parallel Computing that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
507 papers, from 4 September 2026 to 5 November 2026: 507 arXiv preprints.
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Newest papers, page 25
GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay
Counterfactual regret minimization (CFR) is one of the few large numerical workloads that still runs faster on CPUs than on GPUs.Efficient Vision-Language-Action Management and Serving for Robot Factories
Vision-Language-Action (VLA) models show high robotic manipulation capabilities via a two-stage design: a Vision-Language Model (VLM) stage followed by an Action Diffusion Transformer (ADiT) stage.Introvert Clustering for Distributed Graph Algorithms
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…Avatar: Toward Autonomous End-to-End Orchestration of Scientific Workflows using LLMs
Scientific workflow management (WMSs) systems automate execution, yet orchestrate using fixed, hand-tuned rules.Composable CXL Memory as a Kubernetes-Native Shared Memory for LLM Serving
We present a Kubernetes Dynamic Resource Allocation (DRA) driver that makes composable CXL memory a schedulable cluster resource, and evaluate the resulting shared-memory tier for cross-node…Navigating Small-World Networks with Distance Predictions
The small-world phenomenon was given an algorithmic foundation by Kleinberg, who showed that in an augmented $k$-dimensional lattice a decentralized greedy algorithm delivers a message in $O(\log^2…A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware
Large language models (LLMs) are increasingly used as backends for intelligent web services, but serving them across the edge continuum requires balancing quality, latency, model footprint, and…GraphFAS: A Distributed System for Automated Graph Feature Generation and Selection in Industrial Transaction Networks
Industrial fraud detection often relies on costly expert-crafted features that overlook graph-structured relational signals, while GNNs often do not meet the interpretability and deployment…Smart Adaptive Computing Across the Continuum: LLMs in IoT-Edge-Cloud Resource Management
Managing resources across IoT, edge, and cloud layers calls for continuous, context-aware decisions under constraints that rarely stay fixed.Online Draft Co-Training for Speculative Decoding in Large-Scale, Long-Context RL Post-Training
Speculative decoding accelerates rollout generation, which dominates the cost of reinforcement learning (RL) post-training.Robust Decentralized Federated Distillation via Multi-Modality Knowledge Collaboration
This paper propose a robust decentralized federated distillation method that enables clients with heterogeneous models to collaborate through predictions on shared unlabeled public data.Parallelism Strategy Chaining for Fast Training Convergence
Selecting a parallelism strategy - the configuration of data, tensor, and pipeline parallelism degrees together with micro- and global-batch sizes - largely determines the training efficiency of…The Maximum Mutual Visibility Set on a Cactus Graph and the Self-stabilizing Constructions
Given a graph $G=(V,E)$, let $S$ ($\subseteq V$) be a set of vertices.Robust Decentralized Personalized Federated Learning via Prediction-Constrained Neighborhood Collaboration
This paper proposes a robust decentralized personalized federated learning method R-DPFL, that enables clients to reduce the impact of Byzantine attacks via robust neighborhood direction estimation…PLATOS: A Power and Latency-Aware Task-Oriented Scheduling Strategy for Healthcare IoT in Fog Computing
Healthcare Internet of Things (HIoT) technology is revolutionising the healthcare industry by enabling real-time data collection and analysis for personalised patient care.Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems
Kolmogorov-Arnold Networks (KANs) replace the fixed activation functions and linear weights of Multi-Layer Perceptrons (MLPs) with learnable univariate functions on network edges, offering improved…Phase-cycled randomized benchmarking of quantum processors: recovering hidden classical noise correlations
Randomized benchmarking can hide classical temporal correlations because its Clifford-twirled response is even in the noise phase.PACO: A Fully Cache-Oblivious Parallel FFT with One Global Redistribution
Fast Fourier transforms on parallel machines incur two forms of data movement: processor-local transfers through the memory hierarchy and global redistribution between processors.EStream: Fast and Memory-Efficient MoE Prefill through Expert Virtualization on Mobile NPUs
Mobile vendors and application developers increasingly deploy LLMs on smartphones for diverse prefill-only services.Constrained Bayesian Optimization for Hierarchical Federated Learning in IoT Networks for Plant Disease Classification
The deployment of Hierarchical Federated Learning (HFL) in resource-constrained Internet of Things (IoT) environments requires careful configuration to balance predictive performance with energy…