high performance computing on graphics processing units: hgpu.org

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Benchmarking GPUs to tune dense linear algebra

Vasily Volkov, James W. Demmel

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280

November 4, 2010 by hgpu

Fast multipole methods on graphics processors

Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX

November 4, 2010 by hgpu

Solving Dense Linear Systems on Graphics Processors

Sergio Barrachina, Maribel Castillo, Francisco D. Igual, Rafael Mayo, Enrique S. Quintana Ort'?

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

November 4, 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

GAMER with out-of-core computation

Hsi-Yu Schive, Yu-Chih Tsai, Tzihong Chiueh

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Tesla T10

November 4, 2010 by hgpu

Relational joins on graphics processors

Bingsheng He, Ke Yang, Rui Fang, Mian Lu, Naga Govindaraju, Qiong Luo, Pedro Sander

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Tags: Algorithms, ATI, ATI CAL, ATI R600, ATI Stream, Computer science, CUDA, Join, nVidia, nVidia GeForce 8800 GTX, Sorting

November 4, 2010 by hgpu

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Nathan Bell, Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Package, Sparse matrix

November 4, 2010 by hgpu

CuPP – A framework for easy CUDA integration

Jens Breitbart

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

November 4, 2010 by hgpu

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

R. Capuzzo-Dolcetta, A. Mastrobuono-Battisti, D. Maschietti

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenMP, Package, Stellar dynamics, Tesla C1060

November 4, 2010 by hgpu

High performance discrete Fourier transforms on graphics processors

Naga K. Govindaraju, Brandon Lloyd, Yuri Dotsenko, Burton Smith, John Manferdelli

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Tags: Computer science, CUDA, FFT, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280

November 3, 2010 by hgpu

Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA

Dimitri Komatitsch, David Michea, Gordon Erlebacher

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Tags: CUDA, Finite element method, Geoscience, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Spectral methods

November 3, 2010 by hgpu

Harvesting graphics power for MD simulations

J. A. van Meel, A. Arnold, D. Frenkel, Portegies S. F. Zwart, R. G. Belleman

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Tags: Condensed matter, CUDA, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX, Soft Condensed Matter

November 3, 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

Benchmarking GPUs to tune dense linear algebra

Fast multipole methods on graphics processors

Solving Dense Linear Systems on Graphics Processors

Parallel Computing Experiences with CUDA

GAMER with out-of-core computation

Relational joins on graphics processors

Implementing sparse matrix-vector multiplication on throughput-oriented processors

CuPP – A framework for easy CUDA integration

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

High performance discrete Fourier transforms on graphics processors

Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA

Harvesting graphics power for MD simulations

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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