Systems & Networks · Computer Science & AI
Distributed & Parallel Computing
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507 papers, from 4 September 2026 to 5 November 2026: 507 arXiv preprints.
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Newest papers, page 13
Democratizing MoE inference on commodity GPUs with CoMoE
Deploying Mixture-of-Experts (MoE) models relies heavily on Expert Parallelism, which generates intense inter-GPU communication.Differential Refresh Policies for Models Trained on Lagging Data Snapshots: From a Single-Age Equivalence Limit to an Optimal Per-Segment Allocation
Production machine-learning models are derived artifacts of time-bounded training snapshots: a deployed model is a materialized view over a training cut that ages the instant it is built.Almost Optimal Constant-Round Approximation of Dominating Set in Graph Classes with Excluded Minors
For every fixed proper minor-closed class $\mathscr C$ and every $ε>0$, we give a deterministic LOCAL algorithm that returns a dominating set of size at most $(2a(\mathscr C)+1+ε)γ_f(G)$ on every…Communication-Aware Qubit Placement and Automatic Node-Count Allocation for Distributed State-Vector Simulation
Distributed quantum circuit simulation enables the execution of large-scale quantum algorithms by partitioning qubits across multiple computational nodes.AeroEval: Staged Program and Execution Validation for AI-Generated Drone Missions
Large Language Models (LLMs) can generate drone programs from natural-language mission descriptions, but syntactically valid programs may still violate user intent, environmental constraints, and…Real Long-Term Memory for AI: A 50-Million-Token Window That Is Faster and Cheaper Than Recompute
A large language model can only use the text that fits in its context window, and it recomputes its internal key-value (KV) state for a prompt every time the prompt is sent.Adaptive Multi-Discriminator WGAN Framework for Resource-Constrained Internet of Vehicles Using Reinforcement Learning and Game Theory
Managing machine learning workloads as a network service introduces a resource-orchestration problem distinct from conventional model training; which nodes should be allocated to a task, how…When Can Stateless Recovery Defeat Byzantine Quorum Safety? A Tight Normal Form for Single-Step BFT
Byzantine quorum safety relies on correct replicas refusing to sign conflicting values.Persistent Memory in Multi-Agent LLM Inference: What It Costs, What It Buys, and When You Can Tell
Decomposing long-context inference across cooperating agents bounds the active KV cache per call rather than total evidence, which matters when KV-cache memory binds.Do I Need the Cloud? Uncertainty-Aware Step-Level Handoff for Small Language Model Agents
Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet structured tool errors can cause an agent step to…Tram-FL: Reducing Communication and Computation Costs through Sequential Model Circulation in Decentralized Federated Learning
Conventional decentralized federated learning (DFL) often focuses on clients, with each client maintaining a model copy, performing updates individually, and undertaking model exchange and…Beyond Marginal Monitoring: Distributed Joint-Distribution Testing for Data Concept Drift in Large Scale E-Commerce Operations
Concept drift threatens production machine learning, yet the empirical behavior of multivariate two-sample drift detectors at scale remains under-characterized.GPU Acceleration of Awkward Arrays: Using Python cuda.compute
Awkward Array is a widely used library in high-energy physics (HEP) for representing and manipulating nested, variable-length data in Python.DySCo: Dynamic Sharding for Collaborative Edge-Cloud LLM Inference with Depth-Synchronized Batching
Pervasive intelligent applications are increasingly deployed on mobile and Internet of Things (IoT) edge devices.NeMo-DCR: Bit-Exact Delta-Compressed Refit for Scalable Agentic RL at Trillion-Parameter Scale
Agentic reinforcement learning (RL) disaggregates training from rollout, so each policy update must reach the rollout clusters before the next batch.Automatically Detecting and Fixing Deadlocks in Go Code with GoDDaR
The Go programming language provides a lightweight abstraction for concurrent programming through goroutines, which are prone to deadlocks.RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof
AI systems can now write and optimize production GPU kernels, but validating them remains an important challenge.Nexus: An Execution Fabric for AI Agents Across Cloud, Edge, and Devices
Language-model agents are evolving into long-running services that interact with models, tools, computers, mobile devices, and distributed environments.Fine-Tuning a 3B-Parameter LLM on a Smartphone: Characterizing Sustained Training
Multi-billion-parameter LLMs now run on phones for inference, and training them on the device would personalize them without user data leaving the phone.GPU-Initiated Discrete Simulated Bifurcation: Low-Latency Requests and Streaming Dense Couplings
GPU-based optimization faces two communication bottlenecks: coordinating frequent requests and delivering dense models that exceed device memory.