high performance computing on graphics processing units: hgpu.org

Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Lujan, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber

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Tags: Algorithms, ARM, Benchmarking, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance

October 10, 2014 by hgpu

Code Refinement of Stencil Codes

Marcel Koster, Roland Leissa, Sebastian Hack

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Tags: Algorithms, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

October 10, 2014 by hgpu

Parallel implementation of linear repetitive processes identification using subspace algorithms

Dominik Kujawa

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460

October 10, 2014 by hgpu

cuDNN: Efficient Primitives for Deep Learning

Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Tesla K40

October 8, 2014 by hgpu

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Mathematical Software, nVidia, Package, Tesla K20

October 8, 2014 by hgpu

A Framework for the Volumetric Integration of Depth Images

Victor Adrian Prisacariu, Olaf Kahler, Ming Ming Cheng, Julien Valentin, Philip H.S. Torr, Ian D. Reid, David W. Murray

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Tags: Computer science, Computer vision, CUDA, nVidia

October 8, 2014 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

GAIN: GPU-based Constraint Checking for Context Consistency

Towards Efficient Indexing of Spatiotemporal Trajectories on the GPU for Distance Threshold Similarity Searches

Mapping dynamic programming algorithms on graphics processing units

Monte Carlo Path Tracing with OpenCL

Performance Improvement of Multichannel Audio by Graphics Processing Units

Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Code Refinement of Stencil Codes

Parallel implementation of linear repetitive processes identification using subspace algorithms

cuDNN: Efficient Primitives for Deep Learning

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

A Framework for the Volumetric Integration of Depth Images

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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