GPU Acceleration

GPU: Graphics Processing Unit

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Overview

GPU acceleration studies how to map computation onto many parallel cores to speed workloads such as language-model inference, rendering, robotics, and scientific simulation. Common approaches include hand-tuned CUDA and Triton kernels, tiling and operator fusion, lower-precision arithmetic, and algorithm reformulations that expose more parallel work. Compilers and coding agents increasingly help generate and tune kernels, while multi-GPU systems focus on scheduling, memory use, and communication. A central challenge is that speedups depend on the workload and hardware: specialized kernels can be fast but difficult to port, and gains in isolated operations may disappear once memory movement, dispatch, or numerical accuracy is considered.

Latest papers

CardsList

174 papers17 papers in the last four weeks, up 31% on the four weeks before. 0.1% of all new papers.

  1. socx: GPU-Accelerated Chance-Constrained Stochastic Optimal Control using JAX

    Oct 29, 2026Tanmay Dokania, Yashwanth Kumar NakkaStochastic Optimal ControlChance-Constrained Optimization

    Authors are with the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, Atlanta, GA, 30332 USA.

  2. PhysicsNeMo-Mesh: GPU-Native Meshes and Simulation Cases for Physics AI

    Oct 29, 2026Peter D. Sharpe, Corey Adams, Negin Sobhani +1GPU AccelerationPhysics-Based Simulation

    NVIDIA Corporation

  3. MCCL: Training Pytorch models across a fleet of Macs at Skywalker Sound

    Oct 28, 2026Kevin Sasso, Chris Fiegel, Francis Aitken +2Distributed TrainingHigh-Performance Computing

    Skywalker Sound, Nicasio, California, USA.

  4. Accelerating SO(2)-Equivariant Materials Models through Low-Precision Emulation

    Oct 26, 2026Denghui Lu, Alexander Maeder, Alexandros Nikolaos Ziogas +2Equivariant Neural NetworksEquivariant GNNs

    D-ITET, ETH Zurich, Zurich, Switzerland

  5. From GPU to TPU with Coding Agents: What Works, What Fails, and What It Costs?

    Oct 25, 2026Hui Sun, Anderson Uchôa, Wesley K. G. AssunçãoSoftware Engineering AgentsCoding Agent Benchmarks

    North Carolina State University Raleigh, NC, USA · Federal University of Cear´a Itapaj´e, Cear´a, Brazil

  6. HyperDrone: Simulation-to-Reality Transfer at Millions of Frames per Second

    Oct 20, 2026Jonas Eschmann, Giuseppe LoiannoRobotics SimulationGPU Acceleration

    University of California, Berkeley

  7. GPU-Accelerated Construction of the Gabriel Graph: Parallelization Strategies and Applications to Large-Margin Classification and Graph-Based Clustering

    Oct 20, 2026Diego Sanches Nere dos Santos, Luiz Carlos Bambirra TorresGraph ConstructionGPU Acceleration

    Department of Computing and Systems, Institute of Exact and Applied Sciences, Federal University of Ouro Preto (UFOP), João Monlevade, MG, Brazil · Department of Computing, Institute of Exact and Biological Sciences, Federal University of Ouro Preto (UFOP), Ouro Preto, MG, Brazil

  8. CusADi2: Latency-Optimized Batch Computation of Robot Kinematics, Jacobians, and Hessians on the GPU

    Oct 18, 2026John Viljoen, Lasse Peters, Masayoshi Tomizuka +1GPU AccelerationRobot Kinematics

    Department of Mechanical Engineering, University of California, Berkeley, CA, USA.

  9. DiffGIPC: Differentiable Mixed-Coordinate Contact Dynamics on GPU

    Oct 13, 2026Kemeng Huang, Bowen Ren, Xinyu Lu +2Differentiable PhysicsInverse Problems

    The University of Hong Kong, Hong Kong SAR, China · TransGP, Hong Kong SAR, China · Carnegie Mellon University, USA

  10. LunaTP: Enabling Efficient and Scalable Tensor Product for Equivariant MLIPs

    Oct 13, 2026Yuanchang Zhou, Mingzhen Li, Chen Wang +3Machine Learning Interatomic PotentialsGPU Kernel Optimization

    State Key Lab of Processors, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences

  11. FORGE: Procedural Weight Generation for Sparse MoE Inference

    Oct 12, 2026Chanyoung Moon, Travis Pence, Daisuke Yamada +4Mixture-of-Experts InferenceLLM Inference Acceleration

    University of Wisconsin-Madison Madison, Wisconsin, USA · Korea University Seoul, Republic of Korea · NVIDIA Santa Clara, California, USA

  12. Minions: A Dynamic and Distributed Virtual GPU Cloud Built on Idle Apple Silicon Devices

    Oct 9, 2026Jianhua Li, Yun Xing, Girisha De Silva +3Distributed InferenceGPU Acceleration

    Apple USA

  13. The Operator Mismatch Problem: Deploying BEV Perception with Portable GPU Compute

    Oct 8, 2026Rohit Verma, Anand V BodasAutonomous Driving PerceptionGPU Acceleration

    Intel

  14. GPU-Accelerated Computation of Persistent Homology for Topological Analysis of Image Data

    Oct 7, 2026Fan Wang, Hubert Wagner, Rezaul Chowdhury +1Persistent HomologyTopological Data Analysis

    Department of Computer Science, Stony Brook University, Stony Brook, NY 11794 USA · Department of Mathematics, University of Florida, Gainesville, FL 32611 USA · Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794 USA

  15. The Missing Fourth Term for the Emulation Tensor Memory Equilibrium (TME) Model: The Residue Deconstruction Cost

    Oct 7, 2026Harun Bayraktar, John Gunnels, Peter CadayRoofline ModelingGPU Acceleration

    NVIDIA Corporation

  16. GPU-Accelerated Bregman Douglas-Rachford Splitting for Discrete Optimal Transport

    Oct 3, 2026Yifan Xu, Shiqian MaOptimal TransportGPU Acceleration

    Department of Computational Applied Mathematics and Operations Research, Rice University, Houston, TX, USA · Data Science and AI Institute, and Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA

  17. Windfoil: Closed-Form Coverage for Real-Time and Differentiable Vector Graphics

    Oct 1, 2026Matt DesLauriersDifferentiable RenderingGPU Acceleration

    Creative Computing Institute University of the Arts London London, United Kingdom

  18. GPU-Accelerated Path-Dependent Marginal Information Gain for Autonomous Exploration

    Sep 30, 2026João Félix Mendes, Rodrigo Ventura, Meysam BasiriGPU AccelerationRobot Navigation

    Institute for Systems and Robotics, Department of Electrical and Computer Engineering, Instituto Superior Técnico, Lisboa, Portugal

  19. Trident: Unifying Guarded Dispatch and Host Execution for PyTorch Triton Workloads

    Sep 29, 2026Jinjie Liu, Xiaoyan Liu, Shuhan Zhang +5Inference-Time OptimizationGPU Acceleration

    The Chinese University of Hong Kong · Beijing Academy of Artificial Intelligence

  20. Beneath the Tokens: A Performance Engineering Study of Multi-Token Prediction in GPU-Accelerated LLM Inference

    Sep 28, 2026Suwesh Prasad SahLLM Inference EfficiencyMulti-Token Prediction

  21. E3J: An Efficient and Open-Source Backend for Euclidean Equivariant Operations on GPU and TPU

    Sep 28, 2026Olivier Peltre, Armand Picard, Adrien Pichard +6AI Accelerator InferenceGPU Kernel Optimization

    InstaDeep · Prima Mente

  22. Fast Differentiable SVD on GPU via Polar Decomposition

    Sep 26, 2026Uliana Parkina, Askar Tsyganov, Sergei Kudriashov +2Singular Value DecompositionMatrix Factorization

    HSE University

  23. VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan

    Sep 24, 2026Ole Hoffmann, Mateo de Mayo, Daniel CremersVisual-Inertial OdometryGPU Acceleration

    Technical University of Munich, Munich, Germany · Munich Center for Machine Learning, Munich, Germany

  24. Exact Factorisation and Fast Computation of Invertible Constant-Q Transforms

    Sep 24, 2026Facundo Franchino, Eloi Moliner, Vesa VälimäkiGPU AccelerationTime-Frequency Analysis

    Massachusetts Institute of Technology, Cambridge, MA, USA · Acoustics Lab, Dept. of Information and Communications Eng., Aalto University, Espoo, Finland

  25. GLASS: Architecture-Tuned, Composable, Device-Side Linear Algebra for Edge Robotics and Beyond

    Sep 23, 2026Brian PlancherGPU AccelerationGPU Kernel Optimization

    Dartmouth College

  26. XLOG: A CUDA-Native Engine for Neurosymbolic Integration

    Sep 23, 2026Levi Dubrovin, Nikita Pospelov, Kirill SabitovNeuro-Symbolic ReasoningProbabilistic Logic

    Brainyblaze Dynamics Inc.

  27. One Simple Trick for Improving the Performance of Energy-Limited Local Inference and Training

    Sep 14, 2026Erik Schultheis, Maximilian Kleinegger, Dan AlistarhEnergy-Efficient MLGPU Acceleration

    ISTA · TU Wien · RedHat AI

  28. Dissecting GPU Utilization for LLM Inference on Nvidia Hopper

    Sep 11, 2026Mohammad Siavashi, Gerald Q. Maguire, Dejan Kostic +1LLM Inference EfficiencyGPU Acceleration

    KTH Royal Institute of Technology, Stockholm, Sweden

  29. GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay

    Sep 10, 2026Boning Li, Longbo HuangGPU Kernel OptimizationGPU Acceleration

    Institute for Interdisciplinary Information Sciences, Tsinghua University

  30. From Splats to Silicon: Rethinking Computational Efficiency of 3DGS

    Sep 5, 2026Minnan Pei, Qiwei Dong, Yihan Zhou +73D Gaussian Splatting3DGS Acceleration

    Institute of Automation, Chinese Academy of Sciences, and also with the University of Chinese Academy of Sciences · Nanjing University · Eindhoven University of Technology +1