Research Papers
Research Papers news — Thursday 22 October 2026
30 stories from 1 sources, every one in English. Each links to its publisher.
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GPU-Accelerated Construction of the Gabriel Graph: Parallelization Strategies and Applications to Large-Margin Classification and Graph-Based Clustering
arXiv cs.DC (Distributed)
arXiv:2610.28759v1 Announce Type: new Abstract: 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…
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The End of Consensus Research?
arXiv cs.DC (Distributed)
arXiv:2610.30114v1 Announce Type: new Abstract: Consensus is a fundamental problem in distributed computing and at the core of state machine replication (SMR). Despite decades of active human research, discovering practical low-latency…
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MCCL: Measurement-based Collective Communication Library
arXiv cs.DC (Distributed)
arXiv:2610.17091v2 Announce Type: replace-cross Abstract: Collective communication is a critical performance bottleneck in large-scale distributed training. Existing libraries and synthesis frameworks compute open-loop schedules once…
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Hard and Soft Real-Time DNN Inference Scheduling on Heterogeneous Multi-Accelerator Systems via Reinforcement Learning
arXiv cs.DC (Distributed)
arXiv:2610.29503v1 Announce Type: cross Abstract: We present a scheduling framework for heterogeneous multi-accelerator systems executing both hard real-time and soft real-time QoS-aware DNN inference workloads. The framework combines an…
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Concepts in Practice: C++ MPI Bindings for the HPC Ecosystem - From a Standardizable Core to a Composable Interface
arXiv cs.DC (Distributed)
arXiv:2606.09102v2 Announce Type: replace Abstract: The official C++ MPI bindings were removed from the standard in 2008, leaving a gap that numerous third-party libraries have attempted to fill. However, existing wrappers typically cover…
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Koala: Non-disruptive Reconfiguration for Long-running Stateful Dataflows
arXiv cs.DC (Distributed)
arXiv:2610.28939v1 Announce Type: new Abstract: Stateful dataflow systems must decide where state lives relative to the tasks that process it. For long-running applications that require frequent reconfiguration due to changes in resource…
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EP-NCO: Latency-Aware Service Placement using Neural Combinatorial Optimisers for Edge-Cloud Systems
arXiv cs.DC (Distributed)
arXiv:2606.25553v2 Announce Type: replace Abstract: Latency-sensitive Internet of Things (IoT) applications are increasingly deployed as interdependent microservices across heterogeneous edge-cloud infrastructures. Placing them under…
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Enumeration-based Triangle Counting on GPUs
arXiv cs.DC (Distributed)
arXiv:2610.29988v1 Announce Type: new Abstract: Subgraph enumeration in partitioned graphs across distributed-memory systems is beset with challenges in balancing data movement with the local computation. Especially, counting the number of…
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Carbon-aware Resource Management for Latency-Sensitive Cloud Computing Environments: A Taxonomy and Future Directions
arXiv cs.DC (Distributed)
arXiv:2609.03270v2 Announce Type: replace Abstract: The proliferation of cloud-based latency-sensitive workloads, such as autonomous driving, real-time healthcare services, industrial automation, immersive interactive services, and…
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NanoCP: Taming Load Imbalance in Data-Expert Parallel Decoding under Variable-Length Workloads
arXiv cs.DC (Distributed)
arXiv:2605.21100v2 Announce Type: replace Abstract: Modern serving systems for Mixture-of-Experts (MoE) models adopt hybrid data-expert parallelism: expert parallelism (EP) shards experts across GPUs to scale capacity, while data…
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RISK-KV: Quality-Aware Selective KV Cache Reconstruction for Distributed LLM Inference
arXiv cs.DC (Distributed)
arXiv:2610.29544v1 Announce Type: new Abstract: Request migration and interruption recovery in distributed large language model (LLM) inference rely on historical key-value (KV) caches. Retaining or transferring a complete cache incurs…
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Semantic-Aware Update Admission and Adaptive Byzantine Redundancy for Secure Computation Offloading in COIN-Enabled Metaverse Systems
arXiv cs.DC (Distributed)
arXiv:2610.29592v1 Announce Type: new Abstract: Computing in the network (COIN) supports latency-sensitive Metaverse services, but blockchain commitment of persistent shared-state updates competes with application execution for limited…
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How Not to Be Censored: Inclusion Safety in Client-Led Consensus
arXiv cs.DC (Distributed)
arXiv:2610.29497v1 Announce Type: new Abstract: Blockchain consensus protocols implicitly follow a client-server architecture: validators are the only active participants, while clients (i.e., users) merely submit transactions and rely on…
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UlaCache: Unified Logical Addressing for Sparse LLM Serving
arXiv cs.DC (Distributed)
arXiv:2610.29820v1 Announce Type: new Abstract: Long contexts increase the memory cost of the key-value (KV) cache in large language model (LLM) inference. Sparse attention reduces attention computation and memory traffic by selecting…
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Correlated Failures of AI Approval Monitors
arXiv cs.DC (Distributed)
arXiv:2610.29178v1 Announce Type: cross Abstract: Before an AI agent takes a consequential action, such as paying, messaging or changing code, several monitors check it. Their verdicts are combined by aggregating scores or by counting…
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XIR: A Framework for Interoperability across Cross-Chain Protocols Based on a Verifiable Intermediate Representation
arXiv cs.DC (Distributed)
arXiv:2609.20010v4 Announce Type: replace-cross Abstract: Cross-chain protocols enable applications to exchange messages across blockchains. Under point-to-point configurations, communication depends on a direct connection between the…
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SeFoRA: Sketch-Aggregated Federated Low-Rank Adaptation with Heterogeneous Client Ranks
arXiv cs.DC (Distributed)
arXiv:2608.10144v2 Announce Type: replace-cross Abstract: We consider federated parameter-efficient fine-tuning of foundation models, e.g., LLMs and LVMs, using low-rank adaptation (LoRA; ~Hu et al.\ 2022). Combining LoRA with federated…
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A Real-time tax compliance architecture for VAT split payments with Making Tax Smart and Open Banking
arXiv cs.DC (Distributed)
arXiv:2610.30055v1 Announce Type: new Abstract: This paper presents Making Tax Smart with Open Banking (MTS-OB), a novel DLT-based architecture designed to integrate real-time VAT compliance into the existing payment system through split…
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To Keep or Not to Keep: Learning KV Cache Retention in Disaggregated LLM Serving Systems
arXiv cs.DC (Distributed)
arXiv:2610.28637v1 Announce Type: cross Abstract: Disaggregated \textsc{LLM} serving separates prefill and decode across node pools, placing a network fabric between \textsc{KV}-cache computation and consumption. This breaks a key…
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Weight Placement Is Not Enough: Synchronization in Multi-Node CPU Decoding of Ternary LLMs
arXiv cs.DC (Distributed)
arXiv:2610.28620v2 Announce Type: replace Abstract: Ternary LLMs read only a few gigabytes per decoded token, yet on dual-socket servers with four NUMA nodes the fastest ternary runtime we found uses less than half of the memory bandwidth…
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Resuming Vision-Language Inference across Onboard Interruptions
arXiv cs.DC (Distributed)
arXiv:2610.29183v1 Announce Type: new Abstract: Executing vision-language models (VLMs) aboard low-Earth orbit satellites enables flexible processing of observation data without first downlinking it to the ground. On commercial…
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Engineering Low-Latency, High-Throughput Quantum Decoders on NVIDIA GPUs
arXiv cs.DC (Distributed)
arXiv:2610.28867v1 Announce Type: new Abstract: 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…
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PQ-Vault: Provably Quantum-Safe Asset Custody for Unmodified Ethereum
arXiv cs.DC (Distributed)
arXiv:2610.29230v1 Announce Type: cross Abstract: A quantum computer could recover the key of any Ethereum account whose public key appears on chain. We prove that no sidechain or bridge that leaves Ethereum's rules unchanged can protect…
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SAT Sampling at Scale via GPU-based Boolean Constraint Propagation
arXiv cs.DC (Distributed)
arXiv:2610.28805v1 Announce Type: cross Abstract: Constrained-random verification tests hardware designs by sampling solutions of Boolean formulas. Existing samplers largely follow one of two approaches: CPU-based SAT samplers (e.g…
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Engineering Scalable Distributed List Ranking
arXiv cs.DC (Distributed)
arXiv:2606.09318v2 Announce Type: replace Abstract: The list ranking problem is one of the classical problems of parallel computing, with nontrivial algorithms and many applications as a subroutine for solving other problems. While it has…
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Amplified Pruning and Path Selectors for Deterministic Radio Gossiping
arXiv cs.DC (Distributed)
arXiv:2610.28930v1 Announce Type: cross Abstract: We study deterministic gossiping in unknown strongly connected directed radio networks with $n$ vertices, $m$ arcs, and distinct identifiers in $\{1,\ldots,N\}$, where $N=n^{\mathcal…
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Reorienting the Vector Axis: Restructuring FlashAttention for Long-Vector Processors
arXiv cs.DC (Distributed)
arXiv:2610.29489v1 Announce Type: cross Abstract: A Transformer is built around attention, whose cost grows with the square of the sequence length and dominates the layer on long sequences. FlashAttention made that cost manageable by…
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Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning
arXiv cs.DC (Distributed)
arXiv:2606.08252v2 Announce Type: replace-cross Abstract: Federated learning aims to protect data privacy by collaboratively learning a model without sharing private data among clients. Unlike traditional parameter-based FL methods that…
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Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
arXiv cs.DC (Distributed)
arXiv:2605.07985v3 Announce Type: replace Abstract: Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, since no single choice performs best…
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HAWK: Heterogeneity-Aware KV Cache Transfer for Efficient GPU-NPU Phase-Disaggregated LLM Inference
arXiv cs.DC (Distributed)
arXiv:2610.29873v1 Announce Type: cross Abstract: Large language model (LLM) inference exhibits distinct computational characteristics across its two phases: prefill is compute-intensive, whereas decode is more memory-bound. As a result…