high performance computing on graphics processing units: hgpu.org

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The PEPPHER Approach to Programmability and Performance Portability for Heterogeneous many-core Architectures

Siegfried Benkner, Sabri Pllana, Jesper Larsson Traff, Philippas Tsigas, Andrew Richards, Raymond Namyst, Beverly Bachmayer, Christoph Kessler, David Moloney, Peter Sanders

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Performance, Tesla C1060

February 8, 2012 by hgpu

Acceleration of a Locally Tuned Sine Non Linear Video Enhancement Algorithm on GPGPU

Julian Daniel John

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla C2070, Thesis

February 8, 2012 by hgpu

Verifiable Computation with Massively Parallel Interactive Proofs

Justin Thaler, Mike Roberts, Michael Mitzenmacher, Hanspeter Pfister

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Tags: Benchmarking, Cloud, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, Package, Security

February 8, 2012 by hgpu

GMP implementation on CUDA – A Backward Compatible Design With Performance Tuning

Hao Jun Liu, Chu Tong

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, nVidia GeForce GTX 280, Performance, Security

February 7, 2012 by hgpu

Seismic imaging based on spectral differentiation matrix and GPU implementation

Jing-Bo Chen, Guo-Feng Liu, Hong Liu

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Tags: Algorithms, CUDA, Earth and Space Sciences, nVidia, Seismology, Tesla C1060, Wave equation

February 7, 2012 by hgpu

Stochastic Differential Equations simulation using GPU

Narayana Darapaneni, Prakalp Somawanshi, Meghana Joshi

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Tags: Algorithms, Computer science, CUDA, Differential equations, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GTX 275, Pseudo-random number generators, Stochastic simulation

February 7, 2012 by hgpu

GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional classical spin systems

Yukihiro Komura, Yutaka Okabe

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, Physics, Spin Systems, Statistical Mechanics

February 6, 2012 by hgpu

A Fast Parallel Implementation of Queue-based Morphological Reconstruction using GPUs

George Teodoro, Tony Pan, Tahsin M. Kurc, Lee Cooper, Jun Kong, Joel H. Saltz

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Tags: Algorithms, CUDA, Image processing, Microscopy, nVidia, nVidia GeForce GTX 580, Tesla C2070

February 5, 2012 by hgpu

Efficient Computation of SOM for Outage Database

Petr Gajdos, Michal Kratky, David Bednar, Radim Baca, Radomir Gono, Jiri Walder

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Tags: Computer science, CUDA, Databases, Neural networks, nVidia, Self-organizing map, Tesla C1060, Visualization

February 5, 2012 by hgpu

Performance Evaluation of Particle Swarm Optimization Algorithms on GPU Using CUDA

V. Krishna Reddy, L.S.S. Reddy

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, nVidia, nVidia GeForce GTS 250, Optimization

February 5, 2012 by hgpu

Raytracing Dynamic Scenes on GPU

Sashidhar Guntury

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing, Rendering, Sorting, Thesis

January 31, 2012 by hgpu

Graphical processing unit implementation of an integrated shape-based active contour: Application to digital pathology

Sahirzeeshan Ali, Anant Madabhushi

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Tags: CUDA, Image processing, Medicine, nVidia, nVidia GeForce 8600 M GT

January 31, 2012 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

The PEPPHER Approach to Programmability and Performance Portability for Heterogeneous many-core Architectures

Acceleration of a Locally Tuned Sine Non Linear Video Enhancement Algorithm on GPGPU

GMP implementation on CUDA – A Backward Compatible Design With Performance Tuning

Seismic imaging based on spectral differentiation matrix and GPU implementation

Stochastic Differential Equations simulation using GPU

GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional classical spin systems

A Fast Parallel Implementation of Queue-based Morphological Reconstruction using GPUs

Efficient Computation of SOM for Outage Database

Performance Evaluation of Particle Swarm Optimization Algorithms on GPU Using CUDA

Raytracing Dynamic Scenes on GPU

Graphical processing unit implementation of an integrated shape-based active contour: Application to digital pathology

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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