high performance computing on graphics processing units: hgpu.org

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GPGPU Processing in CUDA Architecture

Jayshree Ghorpade, Jitendra Parande, Madhura Kulkarni, Amit Bawaskar

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Tags: Computer science, CUDA, Data parallelism, DirectCompute, nVidia, OpenCL, Review

February 21, 2012 by hgpu

Review: Kd-tree Traversal Algorithms for Ray Tracing

M. Hapala, V. Havran

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Tags: 3D Graphics and Realism, Algorithms, Computer science, KD-tree, nVidia, Raytracing, Review

February 20, 2012 by hgpu

Computational Fluid Dynamics using OpenCL – a Practical Introduction

T. Bednarz, Luke Domanski, J. A. Taylor

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Tags: Algorithms, Finite difference, Fluid dynamics, Navier-Stokes equations, nVidia, nVidia GeForce GT 330 M, OpenCL, Review

January 25, 2012 by hgpu

The State of the Art in Interactive Global Illumination

Tobias Ritschel, Carsten Dachsbacher, Thorsten Grosch, Jan Kautz

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Raytracing, Rendering, Review

January 21, 2012 by hgpu

Programming on Parallel Machines: GPU, Multicore, Clusters and More

Norm Matloff

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Tags: Book, Computer science, CUDA, MPI, nVidia, Package, Programming techniques, Review, Tutorial

January 16, 2012 by hgpu

Designing Numerical Solvers for Next Generation High Performance Computing

Mark James Mawson

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia Quadro FX 6000, PC cluster, Review, Thesis

January 9, 2012 by hgpu

Numerical solution of PDEs with hybrid and heterogeneous computing models

Markus Hegland

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Tags: Algorithms, CUDA, Differential equations, Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs, Physics, Plasma physics, Review

December 23, 2011 by hgpu

Performance and Quality of Random Number Generators

V. du Preez, M.G.B. Johnson, A. Leist, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, Monte Carlo simulation, Numerical simulation, nVidia, nVidia GeForce GTX 580, Pseudo-random number generators, Review

December 20, 2011 by hgpu

Implementation and Evaluation of Scientific Simulations on High Performance Computing Architectures

Bibrak Qamar, Jahanzeb Maqbool

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Tags: Algorithms, CUDA, Finance, Fluid dynamics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Review, Thesis, Visualization

December 16, 2011 by hgpu

Architecture-Aware Algorithms and Software for Peta and Exascale Computing

Jack J. Dongarra

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Tags: Algorithms, Computer science, Mixed precision, MPI, Review

November 30, 2011 by hgpu

Parallel Pseudo-Random Number Generation

Nimalan Nandapalan, Richard Brent

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, Pseudo-random number generators, Review

November 28, 2011 by hgpu

The Optimization of Algorithms in the Process of Temporal Data Mining Using the Compute Unified Device Architecture

Alexandru Pirjan

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Tags: Algorithms, Computer science, CUDA, Data mining, MapReduce, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Review

November 24, 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

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

BoltzGen:Toward Universal Binder Design

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

GPGPU Processing in CUDA Architecture

Review: Kd-tree Traversal Algorithms for Ray Tracing

Computational Fluid Dynamics using OpenCL – a Practical Introduction

The State of the Art in Interactive Global Illumination

Programming on Parallel Machines: GPU, Multicore, Clusters and More

Designing Numerical Solvers for Next Generation High Performance Computing

Numerical solution of PDEs with hybrid and heterogeneous computing models

Performance and Quality of Random Number Generators

Implementation and Evaluation of Scientific Simulations on High Performance Computing Architectures

Architecture-Aware Algorithms and Software for Peta and Exascale Computing

Parallel Pseudo-Random Number Generation

The Optimization of Algorithms in the Process of Temporal Data Mining Using the Compute Unified Device Architecture

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

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

BoltzGen:Toward Universal Binder Design

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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