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.
Get the few papers worth your time in Distributed & Parallel Computing every morning.
Follow Distributed & Parallel Computing and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 5
Sandman: A Sandbox Service for Production Agentic Reinforcement Learning
Agentic reinforcement learning (RL) needs stateful environments for tool execution and evaluation.An Exact Parallel Dense Gauss-Seidel Algorithm with Trade-Offs between Parallel Execution Time and Preprocessing Time
The Gauss-Seidel iterative method is commonly used for solving systems of linear equations because of its good convergence properties.Only Accepted Tokens Count: An Energy Accounting of Speculative Decoding Under Latency Targets
Large language model serving is limited by facility power.AI in the EGI e-infrastructure -- Past experiences and future strategies
The EGI Federation has provided federated e-infrastructure services to European and global science for over 15 years.Nearly-Optimal Time-Sample Trade-off in Consensus Dynamics
How does the number of sampled opinions affect the time required to reach consensus in distributed consensus dynamics?GearUp: DAG-aware Acceleration for Serverless Inference Serving via Slack-guided Pre-loading
Serverless platforms increasingly host machine learning (ML) inference workflows, modeled as directed acyclic graphs (DAGs) of interdependent functions.The Endgame of FSDP Communication: Layout-Aware Collectives on Copy Engines, RDMA, and NVSwitch
Fully Sharded Data Parallelism (FSDP2) maintains parameters and gradients as per-parameter tensors, whereas its collective path operates on flat, rank-major buffers.Integrated data, metadata, and paradata management system for 3D Digital Cultural Heritage objects: Workflow automation, federated authentication, and publication
The complexity of high-quality 3D digitised cultural heritage objects creates challenges for existing data management systems as they need to develop metadata management and processing capabilities…Rennala NSGD: Asynchronous Stochastic Optimization Beyond Euclidean Geometry
The empirical success of matrix-aware optimizers, such as Muon (Jordan et al., 2024) and Shampoo (arXiv:1802.09568), highlights the potential of non-Euclidean geometry for deep learning, including…Trustworthy Distributed Machine Learning in Cloud-Edge-IoT Systems: A Heterogeneity-Aware Survey of Security, Privacy, and Robustness
Distributed machine learning (DML), including conventional distributed training and federated learning (FL), enables collaborative model development across cloud-edge-IoT systems without fully…MCCL: Training Pytorch models across a fleet of Macs at Skywalker Sound
Skywalker Sound, a premier audio post-production facility, operates more than 200 M4 Max Mac Studios on a 10Gb Ethernet network.InfraDev: Can Coding Agents Develop AI Infrastructure, and How Can We Tell?
Coding agents are beginning to develop the production-grade AI infrastructure that trains and serves large models, yet existing benchmarks cover only single kernels or single-GPU tasks, and grade…LRMoE: Demand-Side Load Re-Calibration for Efficient MoE Training on Memory-Constrained Nodes
Sparse Mixture-of-Experts (MoE) models offer scalable capacity for Web applications, but uneven routing creates computation and communication bottlenecks.Federated Learning for Semantic Communications over Multiple Access Channels
This paper presents a federated learning (FL) framework for semantic communication (SemCom) over the multiple access channel (MAC), where multiple distributed transmitters simultaneously convey…Waypoint: Analytically Modeling GEMM for CPUs
High-performance General Matrix Multiplication (GEMM) implementations rely on breaking down GEMM into carefully selected tiles to achieve peak performance.Priority-Aware Scheduler for Serverless Functions Provision and Load Balancing
Serverless computing has emerged as a pivotal cloud deployment paradigm due to its efficient utilization of on-demand resources.Accelerating SO(2)-Equivariant Materials Models through Low-Precision Emulation
Rotationally equivariant architectures improve the physical fidelity of machine-learned (ML) universal materials models based on graph neural networks (GNNs).Efficient Exact Unlearning for Federated Zeroth-Order Optimization
Federated zeroth-order optimization (FedZOO) reduces the memory and communication costs of collaborative training for edge intelligence by avoiding backpropagation while communicating only random…One-Shot Federated Model Editing for Device Dynamics at the Edge
Standard federated learning (FL) requires persistent device connectivity across multiple communication rounds, making it unsuitable for dynamic environments such as vehicular networks, where devices…Context Is Not Free: Carbon-Aware LLM Routing for Multi-Turn LLM Web Services across Geo-Distributed Data Centers
The sustainability of the Web has drawn growing attention, as large language model (LLM)-based web services leave a substantial carbon footprint.