Search: “hardware”

MathOptAI.jl: Embed trained machine learning predictors into JuMP models

arXiv:2507.03159v2 Announce Type: replace Abstract: We present exttt{MathOptAI.jl}, an open-source Julia library for embedding trained machine learning predictors into a JuMP model. exttt{MathOptAI.jl

26 May 2026

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Optimizing Multidimensional Scaling in Gini Metric Spaces

DGX agent

arXiv:2605.25124v1 Announce Type: new Abstract: The Gini Multidimensional Scaling (Gini MDS) framework extends the Euclidean multidimensional scaling. We introduce a Gini pseudo-distance based on valu

hardwarearxiv-cs-lg

26 May 2026

Paris 2.0: A Decentralized Diffusion Model for Video Generation

arXiv:2605.26064v1 Announce Type: cross Abstract: We present Paris 2.0, the first video generation model pre-trained through decentralized computation. Its training recipe builds upon Paris 1.0 (arXiv

26 May 2026

Local Ai

Profiling-Driven Adaptive Distributed Transformer Inference on Embedded Edge Deployment

arXiv:2605.25682v1 Announce Type: cross Abstract: Distributing Transformer inference across embedded edge devices can alleviate individual memory and compute constraints, yet practical benefits on rea

local-aiarxiv-cs-ai

26 May 2026

Convex Low-resource Accent-Robust Language Detection in Speech Recognition

arXiv:2605.23235v1 Announce Type: new Abstract: Globalization and multiculturalism continue to produce increasingly diverse speech varieties. Yet current spoken dialogue systems frequently fail on und

DFSAttn: Dynamic Fine-grained Sparse Attention for Efficient Video Generation

arXiv:2605.23445v1 Announce Type: new Abstract: Diffusion transformers have achieved remarkable success in high-quality video generation, yet their reliance on spatiotemporal 3D full attention incurs

Graph Learning via Logic-Based Weisfeiler-Leman Variants and Tabularization

arXiv:2508.10651v3 Announce Type: replace Abstract: We present a novel approach for graph classification based on tabularizing graph data via new variants of the Weisfeiler-Leman algorithm and then ap

PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion

arXiv:2605.23902v1 Announce Type: new Abstract: Most practical high-resolution text-to-image systems, including latent diffusion and autoregressive models, perform generation in a compact latent space

ThriftAttention: Selective Mixed Precision for Long-Context FP4 Attention

arXiv:2605.23081v1 Announce Type: new Abstract: Efficient attention algorithms are critical to mitigate the quadratic cost of attention in long-context workloads. Prior work utilises block-scaled quan

XWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms

arXiv:2605.23348v1 Announce Type: cross Abstract: AI power demand is growing at an unprecedented rate while power grids are often ailing and struggle to keep up. Grid expansion comes with high capital

FlashSinkhorn: IO-Aware Entropic Optimal Transport on GPU

arXiv:2602.03067v3 Announce Type: replace Abstract: Entropic optimal transport (EOT) via Sinkhorn iterations is widely used in modern machine learning, yet GPU solvers remain inefficient at scale. Ten

From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal k-Sparse GLMs

arXiv:2605.22188v1 Announce Type: new Abstract: GPUs have significantly accelerated first-order methods for large-scale optimization, especially in continuous optimization. However, this success has n

ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation

arXiv:2605.22556v1 Announce Type: new Abstract: Digital elevation models (DEMs) underpin terrain analysis in Geographic Information Systems (GIS), but in their common raster form, they rely on interpo

LiteCoOp: Lightweight Multi-LLM Shared-Tree Reasoning for Model-Serving Compiler Optimizations

arXiv:2602.01935v2 Announce Type: replace Abstract: LLM-guided compiler optimization has recently shown promise, but existing approaches rely on a single large LLM throughout search, making them expen

Reading Task Failure Off the Activations: A Sparse-Feature Audit of GPT-2 Small on Indirect Object Identification

arXiv:2605.22719v1 Announce Type: new Abstract: We report a small, reproducible audit of which sparse-autoencoder (SAE) features of GPT-2 small fire differently on failed versus successful trials of t

WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving

arXiv:2512.09472v2 Announce Type: replace-cross Abstract: Deploying multiple models within shared GPU clusters is a key strategy to improve resource efficiency in large language model (LLM) serving. E

Don't Collapse Your Features: Why CenterLoss Hurts OOD Detection and Multi-Scale Mahalanobis Wins

arXiv:2605.21493v1 Announce Type: cross Abstract: The ability to detect out-of-distribution (OOD) inputs is fundamental to safe deployment of machine learning systems. Yet, current methods often rely

EasyVFX: Frequency-Driven Decoupling for Resource-Efficient VFX Generation

arXiv:2605.22051v1 Announce Type: new Abstract: Generating high-fidelity visual effects (VFX) typically demands massive datasets and prohibitive computational power due to the intricate coupling of sp

PALS: Power-Aware LLM Serving for Mixture-of-Experts Models

arXiv:2605.21427v1 Announce Type: new Abstract: Large language model (LLM) inference has become a dominant workload in modern data centers, driving significant GPU utilization and energy consumption.

WorldKV: Efficient World Memory with World Retrieval and Compression

arXiv:2605.22718v1 Announce Type: new Abstract: Autoregressive video diffusion models have enabled real-time, action-conditioned world generation. However, sustaining a persistent world, where revisit

Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models

arXiv:2605.20624v1 Announce Type: new Abstract: Diffusion models provide powerful priors for zero-shot video inverse problems, but their real-time deployment is hindered by two inefficiencies: high in

Depth Completion in Unseen Field Robotics Environments Using Extremely Sparse Depth Measurements

arXiv:2602.03209v2 Announce Type: replace Abstract: Autonomous field robots operating in unstructured environments require robust perception to ensure safe and reliable operations. Recent advances in

hardwarearxiv-cs-ro

Frontier: Towards Comprehensive and Accurate LLM Inference Simulation

arXiv:2605.21312v1 Announce Type: cross Abstract: Modern LLM serving is no longer homogeneous or monolithic. Production systems now combine disaggregated execution, complex parallelism, runtime optimi

HyperBones: Realtime Bone-driven Neural Garment Simulation with Hypernetwork Conditioning

arXiv:2605.20460v1 Announce Type: cross Abstract: Recent advances in garment simulation have brought high-quality results closer to real-time performance. Physics-based simulators can produce accurate

OlmoEarth v1.1: A more efficient family of OlmoEarth models

arXiv:2605.20804v1 Announce Type: new Abstract: We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training (1.7 imes reduction in GPU ho

PlexRL: Cluster-Level Orchestration of Serviceized LLM Execution for RLVR

arXiv:2605.20863v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has recently unlocked strong reasoning capabilities in large language models (LLMs), triggering

PulseCol: Periodically Refreshed Column-Sparse Attention for Accelerating Diffusion Language Models

arXiv:2605.20813v1 Announce Type: new Abstract: Inference in diffusion large language models (dLLMs) is computationally expensive, as full self-attention must be repeatedly executed at each step of th

hardwarearxiv-cs-cl

Understanding Deterioration Random Effects for Causal Discovery in Infrastructure Management

arXiv:2605.20400v1 Announce Type: cross Abstract: Infrastructure deterioration poses significant challenges for asset management, yet existing approaches rely on population-averaged models that overlo

Accelerating Sparse Transformer Inference on GPU

arXiv:2506.06095v4 Announce Type: replace Abstract: Large language models (LLMs) are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerat

Decentralized Direct Volume Rendering: A Browser-Native GPU Architecture for MRI Digital Twins in Resource-Constrained Settings

arXiv:2605.19737v1 Announce Type: cross Abstract: Digital Twin (DT) technology holds immense potential for surgical planning and personalized medicine. However, generating interactive, patient-specifi

FiLark: a streaming-first software framework for end-to-end exploration, annotation, and algorithm integration in distributed acoustic sensing

arXiv:2605.20132v1 Announce Type: cross Abstract: Distributed acoustic sensing (DAS) systems generate continuous, ultra-high-channel-count data streams at rates that exceed the capabilities of convent

GEM: GPU-Variability-Aware Expert to GPU Mapping for MoE Systems

arXiv:2605.19945v1 Announce Type: cross Abstract: Mixture-of-Expert (MoE) models enable efficient inference by employing smaller experts and activating only a subset of them per token. MoE serving eng

HiLiftAeroML: High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics

arXiv:2605.19565v1 Announce Type: cross Abstract: This paper describes the first-ever open-source high-fidelity CFD dataset of a high-lift aircraft for the purpose of AI surrogate model development. T

Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

arXiv:2605.18959v1 Announce Type: cross Abstract: The NSF-DOE Vera C. Rubin Observatory, Roman Space Telescope, Euclid, and other next-generation surveys will deliver imaging, spectroscopic, and time-

OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond

arXiv:2605.19660v1 Announce Type: cross Abstract: The rapid advancement toward long-context reasoning and multi-modal intelligence has made the memory footprint of the Key-Value (KV) cache a dominant

hardwarearxiv-cs-cl

PiKV: KV Cache Management System for Mixture of Experts

arXiv:2508.06526v3 Announce Type: replace-cross Abstract: As large-scale language models continue to scale up in both size and context length, the memory and communication cost of key-value (KV) cache

SuperInfer: SLO-Aware Rotary Scheduling and Memory Management for LLM Inference on Superchips

arXiv:2601.20309v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) serving faces a fundamental tension between stringent latency Service Level Objectives (SLOs) and limited GPU memor

UCCI: Calibrated Uncertainty for Cost-Optimal LLM Cascade Routing

arXiv:2605.18796v1 Announce Type: cross Abstract: LLM cascades and model routing promise lower inference cost by sending easy queries to a small model and escalating hard ones to a large model, but mo

hardwarearxiv-cs-cl

3D Skew Gaussian Splatting with Any Camera Trajectory Visualization Engine

arXiv:2605.18334v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributi

Research

AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code

arXiv:2605.17978v1 Announce Type: new Abstract: Vectorization via Single Instruction, Multiple Data (SIMD) architectures is a cornerstone of high-performance computing. To fully exploit hardware poten

researcharxiv-cs-cl

Bundle Adjustment in the Eager Mode

arXiv:2409.12190v4 Announce Type: replace-cross Abstract: Bundle adjustment (BA) is a critical technique in various robotic applications such as simultaneous localization and mapping (SLAM), augmented

cuNRTO: GPU-Accelerated Nonlinear Robust Trajectory Optimization

arXiv:2603.02642v2 Announce Type: replace Abstract: Robust trajectory optimization enables autonomous systems to operate safely under uncertainty by computing control policies that satisfy the constra

hardwarearxiv-cs-ro

DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention

arXiv:2605.18753v1 Announce Type: cross Abstract: Current hierarchical attention methods, such as NSA and InfLLMv2, select the top-k relevant key-value (KV) blocks based on coarse attention scores and

Efficient 3D Content Reconstruction and Generation

arXiv:2605.18052v1 Announce Type: new Abstract: Automatic 3D content creation seeks to replace labor-intensive modeling and scanning pipelines with systems that can synthesize or recover 3D assets dir

GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment

arXiv:2605.16435v1 Announce Type: cross Abstract: Heatwaves are an important problem in cities, and climate change makes this problem more difficult. In this paper, we present a GPU-based deep learnin

Guard: Scalable Straggler Detection and Node Health Management for Large-Scale Training

arXiv:2605.17879v1 Announce Type: cross Abstract: Training frontier-scale foundation models involves coordinating tens of thousands of GPUs over multi-month runs, where even minor performance degradat

Hawkeye: Reproducing GPU-Level Non-Determinism

arXiv:2603.20421v2 Announce Type: replace-cross Abstract: We present Hawkeye, a system for analyzing and reproducing GPU-level arithmetic operations. Using our framework, anyone can re-execute on a CP

IVF-TQ: Streaming-Robust Approximate Nearest Neighbor Search via a Codebook-Free Residual Layer

arXiv:2605.17415v1 Announce Type: cross Abstract: We propose IVF-TQ, an IVF index with a codebook-free residual layer: a fixed random rotation followed by precomputed Lloyd-Max scalar quantization dep