high performance computing on graphics processing units: hgpu.org

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GPU Pro 2

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, DirectX, OpenGL, Package, Rendering, Tutorial

December 27, 2011 by hgpu

OpenCL Programming Guide

Aaftab Munshi, Benedict Gaster, Timothy G. Mattson, James Fung, Dan Ginsburg

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Tags: Algorithms, Book, Computer science, OpenCL, Tutorial

December 27, 2011 by hgpu

Parallel Algorithms for GPU accelerated Probabilistic Inference

Nico Piatkowski

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package, Tesla C2050

December 27, 2011 by hgpu

Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

Mikolaj Mackowiak, Krzysztof Kurowski, Aleksandr Igumenov

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Tags: Algorithms, Computer science, CUDA, Distributed computing, Hybrid computing, MPI, nVidia, Optimization, Package

December 27, 2011 by hgpu

Simple Geometry Compression for Ray Tracing on GPU

Kirill Garanzha, Alexander Bely, Vladimir Galaktionov

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing

December 26, 2011 by hgpu

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

Lu Zheng, Ole J. Mengshoel, Jike Chong

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Tags: Algorithms, Bayesian, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 460

December 26, 2011 by hgpu

SSLShader: Cheap SSL Acceleration with Commodity Processors

Keon Jang, Sangjin Han, Seungyeop Han, Sue Moon, KyoungSoo Park

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Tags: AES, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Security

December 26, 2011 by hgpu

Multifrontal Factorization of Sparse SPD Matrices on GPUs

Thomas George, Vaibhav Saxena, Anshul Gupta, Amik Singh, Anamitra R. Choudhury

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Tags: Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla S1070

December 26, 2011 by hgpu

OpenCL in Action: How to Accelerate Graphics and Computations

Matthew Scarpino

Tags: Book, Computer science, OpenCL, Programming techniques, Tutorial

December 26, 2011 by hgpu

A Novel GPU-Based Deformation Pipeline

Muhammad Mobeen Movania, Lin Feng

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, OpenGL, Rendering

December 26, 2011 by hgpu

SHADOW3 API: The Application Programming Interface for the ray tracing code SHADOW

Niccolo Canestrari, Dimitris Karkoulis, Manuel Sanchez del Rio

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Tags: Code generation, Computer science, Fortran, nVidia, OpenCL, Python, Raytracing, Tesla M2050

December 26, 2011 by hgpu

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Qi Li

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Optimization, Sorting, Tesla C1060, Tesla C2050, Tesla C2070, Thesis

December 26, 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

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high performance computing on graphics processing units: hgpu.org

GPU Pro 2

OpenCL Programming Guide

Parallel Algorithms for GPU accelerated Probabilistic Inference

Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

Simple Geometry Compression for Ray Tracing on GPU

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

SSLShader: Cheap SSL Acceleration with Commodity Processors

Multifrontal Factorization of Sparse SPD Matrices on GPUs

OpenCL in Action: How to Accelerate Graphics and Computations

A Novel GPU-Based Deformation Pipeline

SHADOW3 API: The Application Programming Interface for the ray tracing code SHADOW

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

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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