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An experimental study on performance portability of OpenCL kernels

Sean Rul, Hans Vandierendonck, Joris D'Haene and Koen De Bosschere

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Tags: ATI, ATI FirePro V8700, Cell processor, Computer science, nVidia, OpenCL, Performance, Playstation, Tesla C1060

February 16, 2011 by hgpu

Multi-agent traffic simulation with CUDA

D. Strippgen, K. Nagel

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Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce 8600 GT, nVidia GeForce GTX 280

February 16, 2011 by hgpu

Cyclic Reduction Tridiagonal Solvers on GPUs Applied to Mixed-Precision Multigrid

Dominik Goeddeke and Robert Strzodka

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Tags: Computer science, CUDA, Finite element method, Mixed precision, nVidia, nVidia GeForce GTX 280

February 15, 2011 by hgpu

PRNG Random Numbers on GPU

W. B. Langdon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Pseudo-random number generators, RapidMind

February 15, 2011 by hgpu

A Fast High Quality Pseudo Random Number Generator for Graphics Processing Units

W. B. Langdon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Pseudo-random number generators, RapidMind

February 15, 2011 by hgpu

A CUDA SIMT Interpreter for Genetic Programming

W. B. Langdon

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Tags: Computer science, CUDA, Genetic programming, nVidia, Package, Tesla T10P

February 15, 2011 by hgpu

Evolving gzip matches Kernel from an nVidia CUDA Template

W. B. Langdon and M. Harman

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295

February 15, 2011 by hgpu

Graphics Processing Units and Genetic Programming: An overview

W. B. Langdon

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Tags: Bioinformatics, Computer science, CUDA, Genetic programming, nVidia, Review

February 15, 2011 by hgpu

Simulation Modelling and Visualisation: Toolkits for Building Artificial Worlds

D.P. Playne, A.P. Gerdelan, A. Leist, C.J. Scogings and K.A. Hawick

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Tags: Algorithms, Computer science, OpenGL, Visualization

February 14, 2011 by hgpu

Visualising Interfaces in Scalar and Vector Field-Model Simulations

D.P. Playne and K.A. Hawick

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Tags: Algorithms, Computer science, Visualization

February 14, 2011 by hgpu

Automatically Generating Efficient Simulation Codes on GPUs from Partial Differential Equations

K.A. Hawick and D.P. Playne

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Tags: Code generation, Compilers, Computer science, CUDA, Finite difference, nVidia, Partial differential equations, PDEs

February 14, 2011 by hgpu

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

K.A. Hawick, A. Leist, and D.P. Playne

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Tags: Cell processor, Computer science, CUDA, Data parallelism, Finite difference, nVidia, nVidia GeForce GTX 295, OpenCL, Partial differential equations, PDEs, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

See all packages

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high performance computing on graphics processing units: hgpu.org

An experimental study on performance portability of OpenCL kernels

Multi-agent traffic simulation with CUDA

Cyclic Reduction Tridiagonal Solvers on GPUs Applied to Mixed-Precision Multigrid

PRNG Random Numbers on GPU

A Fast High Quality Pseudo Random Number Generator for Graphics Processing Units

A CUDA SIMT Interpreter for Genetic Programming

Evolving gzip matches Kernel from an nVidia CUDA Template

Graphics Processing Units and Genetic Programming: An overview

Simulation Modelling and Visualisation: Toolkits for Building Artificial Worlds

Visualising Interfaces in Scalar and Vector Field-Model Simulations

Automatically Generating Efficient Simulation Codes on GPUs from Partial Differential Equations

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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