high performance computing on graphics processing units: hgpu.org

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Design and Storage Optimization of GPU-based Parallel Program of Image Registration for Remote Sensing

Zhou Haifang, Xu Rulin, Jiang Jingfei

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Tags: CUDA, Image processing, Image registration, nVidia, Sensing, Tesla M2050, Wavelet

November 30, 2013 by hgpu

GPU Accelerated Parallel Occupancy Voxel Based ICP for Position Tracking

Adrian Ratter, Claude Sammut

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 570, OpenCL

November 30, 2013 by hgpu

Highly Optimized Full GPU-Acceleration of Non-hydrostatic Weather Model SCALE-LES

Mohamed Wahib, Naoya Maruyama

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Tags: CUDA, Earth and Space Sciences, nVidia, OpenACC, Tesla K20, Tesla M2075, Weather Prediction Model

November 29, 2013 by wahibium

Benchmarking Parallel Performance on Many-Core Processors

Bryant C. Lam, Ajay Barboza, Ravi Agrawal, Alan D. George, Herman Lam

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Phi, Intel Xeon Phi, Performance

November 29, 2013 by hgpu

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Kamil Rocki, Martin Burtscher, Reiji Suda

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Programming techniques

November 28, 2013 by hgpu

The Use of Automated Search in Deriving Software Testing Strategies

Simon Marcus Poulding

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, Tesla C1060, Thesis

November 28, 2013 by hgpu

American Basket Option Pricing on a multi GPU Cluster

Michael Benguigui, Francoise Baude

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Tags: Algorithms, Computer science, GPU cluster, nVidia, OpenCL, Tesla M2050, Tesla S1070

November 28, 2013 by hgpu

Hybrid Programming using OpenSHMEM and OpenACC

Matthew Baker, Swaroop Pophale, Jean-Charles Vasnier, Haoqiang Jin, Oscar Hernandez

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Tags: Computer science, CUDA, MPI, nVidia, OpenACC, Performance, Tesla K20

November 28, 2013 by hgpu

Accelerated Primality Testing Using GPUs

Duncan McBain

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Tags: Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 570, Thesis

November 27, 2013 by hgpu

Autotuning of Pattern Runtimes for Accelerated Parallel Systems

Enes Bajrovic, Siegfried Benkner, Jiri Dokulil, Martin Sandrieser

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C1060, Tesla C2050

November 27, 2013 by hgpu

Evaluating the Performance and Energy Efficiency of N-Body Codes on Multi-Core CPUs and GPUs

Ivan Zecena, Martin Burtscher, Tongdan Jin, Ziliang Zong

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Tags: Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 480, Performance

November 27, 2013 by hgpu

Performance Analysis of GPU-based SAR and Interferometric SAR image processing

Achille Peternier, Marco Defilippi, Paolo Pasquali, Alessio Cantone, Rolf Krause, Raffaele Vitulli, Fumitaka Ogushi, Alberto Meroni

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Tags: Algorithms, CUDA, Image processing, nVidia, OpenCL, Tesla C2050

November 27, 2013 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

Applications

Design and Storage Optimization of GPU-based Parallel Program of Image Registration for Remote Sensing

GPU Accelerated Parallel Occupancy Voxel Based ICP for Position Tracking

Highly Optimized Full GPU-Acceleration of Non-hydrostatic Weather Model SCALE-LES

Benchmarking Parallel Performance on Many-Core Processors

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

The Use of Automated Search in Deriving Software Testing Strategies

American Basket Option Pricing on a multi GPU Cluster

Hybrid Programming using OpenSHMEM and OpenACC

Accelerated Primality Testing Using GPUs

Autotuning of Pattern Runtimes for Accelerated Parallel Systems

Evaluating the Performance and Energy Efficiency of N-Body Codes on Multi-Core CPUs and GPUs

Performance Analysis of GPU-based SAR and Interferometric SAR image processing

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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