high performance computing on graphics processing units: hgpu.org

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CUDA: Scalable parallel programming for high-performance scientific computing

D. Luebke

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Tags: Computer science, CUDA, High-level Languages, nVidia

December 12, 2010 by hgpu

BSGP: bulk-synchronous GPU programming

Qiming Hou, Kun Zhou, Baining Guo

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX

December 7, 2010 by hgpu

Scout: a data-parallel programming language for graphics processors

Patrick McCormick, Jeff Inman, James Ahrens, Jamaludin M. Yusof, Greg Roth, Sharen Cummins

Tags: Computer science, High-level Languages, Visualization

December 5, 2010 by hgpu

GPU Computing: Programming a Massively Parallel Processor

Ian Buck

Tags: Computer science, CUDA, High-level Languages, nVidia, Review

December 4, 2010 by hgpu

Implementing an embedded GPU language by combining translation and generation

Calle Lejdfors, Lennart Ohlsson

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Tags: ATI, High-level Languages, Image processing, nVidia, OpenGL

December 3, 2010 by hgpu

Glift: Generic, efficient, random-access GPU data structures

Aaron E. Lefohn, Joe Kniss, Robert Strzodka, Shubhabrata Sengupta, John D. Owens

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Tags: Cg, Computer science, Data Structures and Algorithms, High-level Languages, nVidia, nVidia GeForce 6800 GT

December 2, 2010 by hgpu

Synergistic execution of stream programs on multicores with accelerators

Abhishek Udupa, R. Govindarajan, Matthew J. Thazhuthaveetil

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTS, Package

November 23, 2010 by hgpu

hiCUDA: a high-level directive-based language for GPU programming

Tianyi D. Han, Tarek S. Abdelrahman

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GT

November 23, 2010 by hgpu

A GPGPU compiler for memory optimization and parallelism management

Yi Yang, Ping Xiang, Jingfei Kong, Huiyang Zhou

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Tags: Computer science, CUBLAS, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Package

November 18, 2010 by hgpu

Cg in Two Pages

Mark J. Kilgard

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Tags: Cg, Computer science, High-level Languages, HLSL, nVidia, Review

November 13, 2010 by hgpu

Accelerator: using data parallelism to program GPUs for general-purpose uses

David Tarditi, Sidd Puri, Jose Oglesby

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Tags: ATI, ATI Radeon X1800, ATI Radeon X850 XT, Computer science, High-level Languages, nVidia, nVidia GeForce 6800 Ultra, nVidia GeForce 7800 GTX

November 5, 2010 by hgpu

Parallel Computing Experiences with CUDA

M. Garland, S. Le Grand, J. Nickolls, J. Anderson, J. Hardwick, S. Morton, E. Phillips, Yao Zhang, V. Volkov

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Tags: Computer science, CUDA, High-level Languages, nVidia

November 4, 2010 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

CUDA: Scalable parallel programming for high-performance scientific computing

BSGP: bulk-synchronous GPU programming

Scout: a data-parallel programming language for graphics processors

GPU Computing: Programming a Massively Parallel Processor

Implementing an embedded GPU language by combining translation and generation

Glift: Generic, efficient, random-access GPU data structures

Synergistic execution of stream programs on multicores with accelerators

hiCUDA: a high-level directive-based language for GPU programming

A GPGPU compiler for memory optimization and parallelism management

Cg in Two Pages

Accelerator: using data parallelism to program GPUs for general-purpose uses

Parallel Computing Experiences with CUDA

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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