high performance computing on graphics processing units: hgpu.org

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GPU Computing in Discrete Optimization – Part I: Introduction to the GPU

Andre R. Brodtkorb, Trond R. Hagen, Christian Schulz, Geir Hasle

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

April 19, 2013 by hgpu

Parallel Sorting on the Heterogeneous AMD Fusion Accelerated Processing Unit

Michael Christopher Delorme

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Tags: APU, ATI, ATI Radeon HD 5870, ATI Radeon HD 6530, ATI Radeon HD 6550, Computer science, Heterogeneous systems, nVidia, OpenCL, Sorting, Thesis, Tutorial

March 26, 2013 by hgpu

General Purpose Computation on Graphics Processing Units Using OpenCL

Fiaz Gul Khan

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Tags: Computer science, Electrodynamics, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia Quadro FX 6000, OpenCL, Sorting, Thesis, Tutorial

March 26, 2013 by hgpu

Ray Tracing on GPUs

Tom Morris Feist, Florian Wende

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, Raytracing, Tesla C1060, Tesla M2090, Tutorial

February 21, 2013 by hgpu

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

Shane Cook

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Tags: Book, Computer science, CUDA, nVidia, Tutorial

November 5, 2012 by hgpu

A short guide to CUDA C: For physicists with multi-core graphics cards

David Plotzki

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia Quadro NVS 3100 M, Package, Physics, Tesla C1060, Tutorial

October 19, 2012 by hgpu

Parallel Programming using OpenCL on Modern Architectures

Allan Svejstrup Nielsen, Allan Peter Engsig-Karup, Bernd Dammann

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Tags: ATI, ATI Radeon HD 6990, Computer science, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 590, OpenCL, Overview, Tutorial

October 15, 2012 by hgpu

Invitation to a Standard Programming Interface for Massively Parallel Computing Environment: OpenCL

Shinichi Yamagiwa

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Quadro NVS 4200 M, OpenCL, Overview, Programming techniques, Tutorial

July 11, 2012 by hgpu

Using OpenCL: Programming Massively Parallel Computers

Janusz Kowalik, Tadeusz Puzniakowski

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Tags: Book, Computer science, OpenCL, Tutorial

July 3, 2012 by hgpu

An Introduction to the OpenCL Programming Model

Jonathan Thompson, Kristofer Schlachter

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 6750 M, Computer science, Matrix multiplication, nVidia, nVidia Quadro FX 2000, OpenCL, Overview, Tutorial

May 16, 2012 by hgpu

CUDA Fortran for Scientists and Engineers

Greg Ruetsch, Massimiliano Fatica

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Tags: Book, Computer science, CUDA, Fortran, High-level Languages, nVidia, Optimization, Tutorial

January 26, 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

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

GPU Computing in Discrete Optimization – Part I: Introduction to the GPU

Parallel Sorting on the Heterogeneous AMD Fusion Accelerated Processing Unit

General Purpose Computation on Graphics Processing Units Using OpenCL

Ray Tracing on GPUs

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

A short guide to CUDA C: For physicists with multi-core graphics cards

Parallel Programming using OpenCL on Modern Architectures

Invitation to a Standard Programming Interface for Massively Parallel Computing Environment: OpenCL

Using OpenCL: Programming Massively Parallel Computers

An Introduction to the OpenCL Programming Model

CUDA Fortran for Scientists and Engineers

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

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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