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 22
Adapting the Actor Model of Concurrency for High-Frequency Trading: Synchronous Message Delivery (fast_send) and a Tick-to-Book Latency Study
The actor model - state isolation, data-race freedom, deadlock resistance, and sequential single-message reasoning - has long been dismissed as unsuitable for high-frequency trading (HFT): actors…Hybrid GPU-CPU Retrieval for Personalized Search at Ultra-Large Scale
Embedding-based retrieval on user-generated content at the trillion-document scale exposes a sharp conflict between two production demands: deep, expressive personalization for queries with rich…Trust-Aware Output Management for Physical Neural Network in Cloud-Continuum Systems
Physical Neural Networks (PNNs) introduce new opportunities for cloud continuum computing, but their outputs may be affected by noise, drift, delay, and incomplete reliability information.Fairly Compensated Distributed Information Retrieval and Augmentation for AI Agents
The increasing reliance of autonomous AI agents on external and distributed knowledge sources introduces a fundamental challenge for decentralized information marketplaces: retrieval agents must…Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach
Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-frontier candidate beyond purely classical…Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication
We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for multithreading parallel programs.The Life of a Token: from Words to Bits on the Wire
Large Language Models (LLMs) transform vast collections of unstructured text into semantic patterns used for language generation and reasoning tasks.Efficiently Distributed Federated Learning
Federated Learning (FL) is experiencing a substantial research interest, with many frameworks being developed to allow practitioners to build federations easily and quickly.FedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction
Urban traffic forecasting often relies on information distributed across stakeholders who may be unable to share raw data due to privacy or commercial constraints, motivating federated…Accelerating Sharded Data Parallelism at Scale with Federated Learning
The symbiotic scaling of artificial intelligence models and high-performance computing systems continually creates algorithmic challenges in their convergence.Multi-center Medical Data Mining with FL-Net - A One-stop Shop for Federated Learning
Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations.FedeRage: Provably Convergent Agnostic Federated Learning under General Client Drift
Federated learning (FL) enables collaborative model training without sharing raw data, but its performance degrades under non-IID data and stochastic client participation.How Much of a Real Workload Can LLM-Generated GPU Kernels Actually Reach?
Language models can now write GPU kernels that outperform PyTorch.The Tethys Dataset: Seven Years of Hourly Smart Water Metering and a Pipeline for Making It Usable
Methods for water demand forecasting and leak detection are based on public datasets, and for water those are scarce, short, or released only after an undocumented cleaning process, hiding defects…ASPIRE: Asynchronous Batched Self-Speculative Decoding for Long-Context LLM Inference
Long-context LLM inference is bottlenecked by attention, whose repeated KV-cache reads make decoding memory-bound.Large Language Model based air quality monitoring and localized alert generation
Poor indoor air quality can cause up to five times more direct health problems to occupants than outdoor air.vidax: A Unified JAX Framework for Video Generative Models on Accelerator Meshes
Open-source video generative models ship almost exclusively as PyTorch/CUDA reference implementations.Token Latency Fairness: Performance Isolation for Multi-Tenant LLM Serving
LLM serving is typically offered as a shared, multi-tenant service, where high-demand workloads from one client can cause latency SLO violations for others.COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads
With the rapid advancement of deep learning technology, shared GPU clusters receive an increasing number of deep learning training (DLT) jobs.Ask the Tool, Don't Guess: Agent Tool Calls Hold Their Progress, and the Serving System Should Read It
An agentic request spends substantial wall-clock time waiting for tools, and its KV cache holds GPU memory the whole time.