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 2
NUMA-Torch: Compiler-Driven NUMA-Aware LLM Prefill on Multi-Socket CPUs
For sufficiently large transformer-based Large Language Models (LLMs), whose parameters cannot be retained in on-chip caches, prefill throughput on multi-socket CPUs is often limited by sustainable…FastAFD: When Does Attention-FFN Disaggregation Pay on Rack-Scale NVLink?
Attention-FFN disaggregation (AFD) separates attention from the experts of a mixture-of-experts (MoE) model and has been reported to raise decode throughput over colocated serving.The Agent Board: Kanban for Machines; Durable Coordination for Agents That Outlive the Conversation
Harnesses for large language models have converged on a single-threaded shape: one agent, one history, one machine, one sitting.LoopKV: Loop-Aware KV Cache Compression for Serving Looped Transformers
Looped transformers apply a shared block several times per token to improve accuracy without adding parameters.When the Consumer Is an Agent: Execution-Grounded Service-Level Agreements
Large language model (LLM) agents increasingly act as service consumers.GC-MoE: Overlapping Expert-Parallel Token Dispatch with FP8/FP4 Grouped GEMM via CUDA Green Contexts
Under expert parallelism, mixture-of-experts (MoE) layers pay all-to-all token dispatch, grouped GEMMs, and a combine step in every layer.Reasoning about Shared-Qubit Concurrency in Quantum Computing
In this paper, we develop a semantic model for the parallel execution of quantum circuits, providing a formal foundation for studying shared-qubit concurrency in quantum computing.FedCSGA: Evolutionary Client Selection with Joint Statistical and System Heterogeneity in Federated Learning
Federated Learning (FL) enables collaborative training of machine learning models across distributed clients while preserving data privacy.Replica-Aware Split Inference for Edge IoT Systems
Split Inference (SI) addresses the hardware resource limitations of Internet of Things (IoT) devices by distributing tiny Machine Learning (TinyML) model segments across multiple IoT devices.Accelerating Offloading-Based MoE Inference by Interleaving Concurrent Requests
Expert offloading enables large mixture-of-experts (MoE) language models to run locally, but conventional batching stalls the GPU while missing experts are fetched.Local Distributed Computation under Crash Failures
We study deterministic algorithms for locally checkable graph problems in the synchronous LOCAL model with crash failures, where a crashing node may send messages to only some neighbors.Characterizing Serverless Workloads: A Large-Scale Analysis of Function-as-a-Service Platforms
Serverless computing is a popular approach to application deployment without having to manage the underlying infrastructure.Workload-Static Optical Circuit Switching For Scalable LLM Inference Decode
LLM inference decode executes fine-grained collectives whose latency directly limits per-user interactivity, yet scale-up fabrics are still built from electronic packet switches designed for training.Distributed Linear Bandits for Freshness-Aware Preprocessing in MEC-Enabled Digital Twin Networks
Digital twins (DTs) require timely updates from Internet of Things (IoT) devices to accurately represent the state of the corresponding physical systems, but transmitting large data volumes can…An Investigation on Numerical Bugs in GPU Programs Towards Automated Bug Detection
General-purpose graphics processing unit (GPU) computing has emerged as a leading parallel computing paradigm, offering significant performance gains in various domains such as scientific computing…Easy Multi-Precision Acceleration via Vectorization
High level programming languages and accelerators are powerful enablers for a wide range of applications.FRESHPart: Feedback-Reshaped Spectral Embedding for Hypergraph Partitioning
With scalable Laplacian solvers now available, the next frontier is to exploit them more effectively for high-quality hypergraph partitioning.Turbo-GMM: FlashAttention-Inspired GPU-Accelerated Gaussian Mixture Model
Expectation-maximization (EM) for Gaussian mixture models (GMMs) requires scoring $N$ data points against $K$ mixture components.Time-Aware Urban Flood Routing with Sticky Edge Closure on Forecast Depth: A Hanoi Case Study
During urban flash floods, commuters and guiding agencies require awareness towards which roads remain passable when a vehicle actually arrives, rather than relying solely on which links appear open…Local Zero-Shot Latency Prediction for Low-End GPUs
Quantifying execution latency is an important consideration across Machine Learning.