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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The End of Consensus Research?
Consensus is a fundamental problem in distributed computing and at the core of state machine replication (SMR).Learning-Theoretic Foundation for General Coded Computing: The Adversarial Setting
Adversarial workers pose a severe challenge in distributed computing systems by returning corrupted outputs that can substantially distort the recovered computations.Benchmarking CPU, GPU, and ML Power-Flow Solvers from 14 to 70,000 Buses
Learned surrogates for power-flow (PF) computation are usually motivated by speed, compared against a single CPU-based baseline.Unsupervised Head Network Personalization for Split Computing via Federated Learning
Split Computing (SC) is a distributed inference method designed for balancing computational load and reducing latency by partitioning a neural network into head and tail networks and deploying them…PULSE: Personalized Opportunistic Learning for Wearable Devices
Wearable devices increasingly support personalized health and well-being applications, but post-deployment data can differ substantially from those used for training, while purely local adaptation…BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
For efficient deployment of large language models (LLMs), methods of ultra-low-bit backbones reduce weight storage, memory traffic, and linear-layer execution cost, while multi-token prediction…Discount Yourself: Self-inclusive Freshness-weighted Gossip for Decentralised Learning under Client Outages
Decentralised federated learning (DFL) trains personalised models on devices that average with their neighbours rather than with a central server.The Token-Energy Law of LLM Decode: Active Bytes and Realized Time Account for Joules per Token
Energy-efficient deployment of large language models requires understanding how model architecture, hardware, and serving settings shape energy per generated token.GPU-Accelerated Construction of the Gabriel Graph: Parallelization Strategies and Applications to Large-Margin Classification and Graph-Based Clustering
The Gabriel graph is a proximity graph widely used in computational geometry and geometric machine learning, underlying large-margin classifiers and, as we show in this work, density-aware…Engineering Low-Latency, High-Throughput Quantum Decoders on NVIDIA GPUs
We design and optimize a quantum error correction (QEC) decoder for NVIDIA GPUs, combining Relay belief propagation, a state-of-the-art message-passing algorithm, with order-zero ordered statistics…Amplified Pruning and Path Selectors for Deterministic Radio Gossiping
We study deterministic gossiping in unknown strongly connected directed radio networks with $n$ vertices, $m$ arcs, and distinct identifiers in $[N]$, where $N=n^{\mathcal O(1)}$.Peer-Relative Trust-Guided Update Screening for Robust Semi-Decentralized Federated Learning under Label-Flipping Attacks
Trust and reputation mechanisms can reduce the influence of malicious clients in federated learning (FL), but strict update filtering is difficult under non-independent and identically distributed…Bidirectionality is Necessary in Cellular Machines for Exact-Arrival Multi-Agent Path Finding
On ranked directed acyclic graphs coupled by vertex conflicts we study exact-arrival multi-agent path finding (departure and arrival pinned in place and time) posed as a distributed output task…A Generic On-Board AI Processing Chain for Earth Observation: From Application Development to Embedded Deployment and Mission-Level Orchestration
Earth observation satellites acquire more data than they can downlink.KrMM Recurrences: HPC-Enhanced Estimators for Nonlinear Classical Shadows
While quantum technologies are rapidly evolving, near-term applications heavily rely on hybrid quantum-classical paradigms.SafeWall: A Risk-Aware Job Walltime Recommendation for HPC Scheduling
In high-performance computing (HPC), users must submit resource requirements for their jobs, with user-supplied walltime being a critical parameter.GeoSplit: Selective Edge--Server Map Acquisition for Cross-User Travel-Mode Recognition
Networked mobility sensing couples local trajectory inference with remote geospatial context, making communication decisions part of the prediction system.3D-MoE: Complementarity-Guided Hardware-Software Co-Design for MoE Decode on 3D-Stacked NMP
Mixture-of-Experts (MoE) have become a mainstream way to scale Large Language Models (LLMs), because each token activates only a small subset of experts, reducing inference cost.SweepANN: A GPU-Accelerated Large-K Approximate Vector Search for Drug Discovery
DrugCLIP places small molecules and protein pockets in one space, turning genome-wide drug discovery into large-K retrieval by vector proximity.Conjugate Compilation: Self-Improving Agentic Co-Compilation for Speculative Decoding
As LLM adoption surges, scaling model serving requires unlocking stranded GPU capacity alongside deploying more GPUs.