high performance computing on graphics processing units: hgpu.org

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Programming Future Parallel Architectures with Haskell and Intel ArBB

Bo Joel Svensson, Ryan Newton

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Programming Languages

November 17, 2011 by hgpu

Characterization and Transformation of Unstructured Control Flow in GPU Applications

Haicheng Wu, Gregory Diamos, Si Li, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Programming Languages

November 17, 2011 by hgpu

Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

Allen D. Malony, Scott Biersdorff, Sameer Shende, Heike Jagode, Stanimire Tomov, Guido Juckeland, Robert Dietrich, Duncan Poole, Christopher Lamb

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C870

November 17, 2011 by hgpu

Large Scale Plane Wave Pseudopotential Density Functional Theory Calculations on GPU Clusters

Long Wang, Weile Jia, Xuebin Chi, Yue Wu, Weiguo Gao, Lin-Wang Wang

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Tags: Algorithms, Computational chemistry, CUDA, GPU cluster, MPI, nVidia, Performance, Physics, Tesla C2050

November 14, 2011 by hgpu

Comprehensive Performance Monitoring for GPU Cluster Systems

K. Furlinger, N.J. Wright, D. Skinner

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, MPI, nVidia, Performance, Tesla C2050

November 13, 2011 by hgpu

Evaluation of an accelerator architecture for Speckle Reducing Anisotropic Diffusion

Siddharth Nilakantan, Srikanth Annangi, Nikhil Gulati, Karthik Sangaiah, Mark Hempstead

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Tags: Algorithms, Computer science, CUDA, Embedded high-performance computing, nVidia, nVidia GeForce 8800 GTX, OpenMP, Performance, Ultrasound

November 12, 2011 by hgpu

Building a Real-Time Multi-GPU Platform: Robust Real-Time Interrupt Handling Despite Closed-Source Drivers

Glenn A. Elliott, James H. Anderson

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Source codes

Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 470, Package, Performance

November 11, 2011 by hgpu

Improving GPU Performance via Large Warps and Two-Level Warp Scheduling

Veynu Narasiman, Chang Joo Lee, Michael Shebanow, Rustam Miftakhutdinov, Onur Mutlu, Yale N. Patt

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Tags: Computer science, CUDA, nVidia, Performance, Warp level parallelism

November 11, 2011 by hgpu

Understanding the impact of CUDA tuning techniques for Fermi

Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance

November 10, 2011 by hgpu

Performance Tuning for CUDA-Accelerated Neighborhood Denoising Filters

Ziyi Zheng, Wei Xu and Klaus Mueller

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Tags: Computed tomography, CT, CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX 480, Performance, Signal denoising

November 9, 2011 by hgpu

Effects of GPU and CPU Loads on Performance of CUDA Applications

Maksim Bobrov, Roy Melton, Stanislaw Radziszowski, Marcin Lukowiak

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Tags: AES, Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 285, Performance, Security

November 9, 2011 by hgpu

Large data visualization on distributed memory multi-GPU clusters

Thomas Fogal, Hank Childs, Siddharth Shankar, Jens Kruger, R. Daniel Bergeron, Philip Hatcher

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Tags: Algorithms, Computer science, GLSL, GPU cluster, nVidia, nVidia GeForce 8800 GTX, nVidia Quadro FX 5800, OpenGL, Performance, Rendering, Visualization

November 9, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming Future Parallel Architectures with Haskell and Intel ArBB

Characterization and Transformation of Unstructured Control Flow in GPU Applications

Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

Large Scale Plane Wave Pseudopotential Density Functional Theory Calculations on GPU Clusters

Comprehensive Performance Monitoring for GPU Cluster Systems

Evaluation of an accelerator architecture for Speckle Reducing Anisotropic Diffusion

Building a Real-Time Multi-GPU Platform: Robust Real-Time Interrupt Handling Despite Closed-Source Drivers

Improving GPU Performance via Large Warps and Two-Level Warp Scheduling

Understanding the impact of CUDA tuning techniques for Fermi

Performance Tuning for CUDA-Accelerated Neighborhood Denoising Filters

Effects of GPU and CPU Loads on Performance of CUDA Applications

Large data visualization on distributed memory multi-GPU clusters

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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