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 4
Robustness Starts with the Objective: Designing and Certifying Robust LLM-Generated Heuristics
LLMs are increasingly used to design heuristics for computer systems.Weights That Stay: On-Chip Megakernels for Serial Heads in Speculative Decoding
Parallel speculative drafters use a lightweight serial head to recover token dependencies within a block generated in parallel.Running a 20B Video Diffusion Transformer on Consumer Hardware: A Deployment and Measurement Report for MiniMax H3 on Apple Silicon
We report the end-to-end deployment and measurement of MiniMax H3, a 20.38-billion-parameter video diffusion transformer (DiT) - the count measured from the safetensors headers of the Q8 checkpoint…Wave Forcing: Towards Speed-of-Light Streaming Video Generation
Real-time long-video generation requires continuous output with consistent appearance and natural motion.Clockwork: Scheduling Compound AI Systems in Space Data Centers
Space data centers built on LEO constellations create an opportunity to serve Compound AI workflows close to where observations are captured.Ripple: Deadline-Aware CPU-GPU Sharing for Embodied Inference
Unified-memory edge devices increasingly run LLM/VLM inference alongside time-critical CPU tasks for perception and control.Multi-Turn Semantic Caching for Low-Cost LLM Serving
Semantic caching lowers the cost of serving large language models (LLMs) by reusing stored responses for similar requests.CuPH: Parallel Cubical Persistent Homology via Level-Synchronous Component Tracking
Persistent homology (PH) is a mathematically principled multi-scale topological descriptor of shape and connectivity in data.TRIAGE: Reliability- and Load-Conditioned Escalation for Two-Tier LLM Serving with a Semantic Evidence Judge
Two-tier LLM serving escalates selected requests from a small model to a large one, but prompt-based routers cannot see whether retrieved evidence supports an answer, and they treat the GPU cost of…Fast and Exact Relative-Position Attention via Structure-Aware Kernels
Relative-position attention mechanisms offer compelling alternatives to RoPE across various transformer architectures, delivering superior performance in domains such as audio.STLT: A Novel System for Energy-Aware Distributed Inference in the Edge-Cloud-Space Continuum
Low Earth Orbit satellites are pivotal for Earth observation tasks such as wildfire detection, capturing imagery for analysis by Deep Neural Networks (DNNs).AdapBench: Adaptive Early-Stopping and Prioritization for Efficient Microbenchmarking in Cloud-based CI/CD
Cloud-based software systems frequently release new versions, a fact further accelerated through agentic coding.ZenKO: Guided and Iterative Quantum-Classical Method for Molecular Electronic Structure using Sample-Based Quantum Diagonalization
The electronic structure of molecules is foundational for scientific advancement, however determining it remains challenging due to the growth of the molecular Hilbert space with system size.ARK: Avoiding Routing Collisions for KV Cache Transfer in Disaggregated LLM Inference
Disaggregated LLM inference separates the prefill and decode phases across GPU pools, generating massive KV-cache transfers.AuditFL: A Contract-Backed Clearing Layer for Open Federated Learning
Federated learning (FL) keeps raw data local, but most deployments still rely on a trusted coordinator for client admission, checkpoint distribution, update collection, aggregation, and rewards.DICE: Decentralized Incentive-driven Federated Learning for Efficient & Scalable Customization of Pretrained Models in Web3
Customizing Pretrained Models (PMs) for downstream tasks demands task-specific data, which burgeoning Web3 applications provide abundantly.More Is Better? Exploring Latent Correspondence in Federated Hypergraph Learning
Federated hypergraph learning with latent cross-client hyperedge correspondence poses fundamental identifiability and computational challenges, as the same local release can correspond to multiple…Learning to Formulate: Agentic Hardware-Software Co-Design of AI Infrastructure through Progressive Optimization and Verification
AI infrastructure, the chips and software that train and serve AI models, is designed in layers.Dobb: Shard-Local Preconditioning in Block-Diagonal Eigenbases
Training language models whose parameters and optimizer state exceed a single node's memory requires sharding these tensors across devices.SeQUeNCe.DQC: Full-stack Simulation of Distributed Quantum Computing
Distributed quantum computing (DQC) connects multiple quantum processing units to overcome the scale limits of monolithic hardware.