high performance computing on graphics processing units: hgpu.org

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Scalable instruction set simulator for thousand-core architectures running on GPGPUs

Shivani Raghav, Martino Ruggiero, David Atienza, Christian Pinto, Andrea Marongiu, Luca Benini

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Programming techniques

April 9, 2011 by hgpu

Data-parallel algorithms for large-scale real-time simulation of the cellular potts model on graphics processing units

Jose Juan Tapia, Roshan D'Souza

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Tags: Biophysics, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 280, OpenGL, Physics, Programming techniques

April 9, 2011 by hgpu

Practical examples of GPU computing optimization principles

Goorts, Patrik; Rogmans, Sammy; Vanden Eynde, Steven; Bekaert, Philippe;

Tags: Computer science, CUDA, DirectCompute, nVidia, OpenCL, Programming techniques

April 7, 2011 by hgpu

Parallel computing with CUDA

M. Garland

Tags: Computer science, CUDA, nVidia, Programming techniques

April 2, 2011 by hgpu

Image parallel processing based on GPU

Nan Zhang, Yun-shan Chen, Jian-li Wang

Tags: Algorithms, Filtering, Image processing, Programming techniques

March 27, 2011 by hgpu

HCW 2009 keynote talk: GPU computing: Heterogeneous computing for future systems

J. Owens

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Tags: Computer science, Heterogeneous systems, Programming techniques

March 27, 2011 by hgpu

General-purpose GPU computing: practice and experience

Bartlett S. H. (Scott) Michel

Tags: Computer science, Programming techniques, Review

March 24, 2011 by hgpu

Aspects of GPU for general purpose high performance computing

Takayuki Aoki, Shoichi Hirasawa, Akira Nukada, Hiroki Honda, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques, Task scheduling

March 23, 2011 by hgpu

Efficient stream reduction on the GPU

David Roger, Ulf Assarsson, Nicolas Holzschuch

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 8800 GTS, OpenGL, Programming techniques

March 23, 2011 by hgpu

Implementing a GPU Programming Model on a non-GPU Accelerator Architecture

Stephen M. Kofsky, Daniel R. Johnson, John A. Stratton, Wen-Mei W. Hwu, Sanjay J. Patel, Steven S. Lumetta

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Tags: Computer science, CUDA, nVidia, Optimization, Programming techniques, Tesla T10

March 19, 2011 by hgpu

Implementation of algorithms with a fine-grained parallelism on GPUs

K. Kalgin

Tags: Algorithms, Cellular automata, Computer science, CUDA, nVidia, Programming techniques

March 17, 2011 by hgpu

GPU-Based Techniques For Global Illumination Effects

L Szirmay-Kalos, Laszlo Szecsi, Mateu Sbert

Tags: 3D Graphics and Realism, Book, Computer science, DirectX, OpenGL, Programming techniques

March 16, 2011 by hgpu

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

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Scalable instruction set simulator for thousand-core architectures running on GPGPUs

Data-parallel algorithms for large-scale real-time simulation of the cellular potts model on graphics processing units

Practical examples of GPU computing optimization principles

Parallel computing with CUDA

Image parallel processing based on GPU

HCW 2009 keynote talk: GPU computing: Heterogeneous computing for future systems

General-purpose GPU computing: practice and experience

Aspects of GPU for general purpose high performance computing

Efficient stream reduction on the GPU

Implementing a GPU Programming Model on a non-GPU Accelerator Architecture

Implementation of algorithms with a fine-grained parallelism on GPUs

GPU-Based Techniques For Global Illumination Effects

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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

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