high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Robert Dietrich, Thomas Ilsche, Guido Juckeland

Tags: Computer science, CUDA, nVidia, OpenCL, Performance

April 1, 2011 by hgpu

Application of the OpenCL API for Implementation of the NIPALS Algorithm for Principal Component Analysis of Large Data Sets

Joshua C. Bowden

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Tags: BLAS, Computer science, GPU cluster, MPI, nVidia, nVidia Quadro FX 580, OpenCL, Performance, Tesla C1060, Tesla S2050, Tesla T10

March 31, 2011 by hgpu

Evaluation Framework for GPU Performance Based on OpenCL Standard

M. Jurecko, J. Kocisova, J. Busa, T. Kasanicky, M. Domiter, M. Zvada

Tags: ATI, Computer science, GPU cluster, nVidia, OpenCL, Performance

March 31, 2011 by hgpu

An Empirically Optimized Radix Sort for GPU

B. Huang, Jinlan Gao, Xiaoming Li

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Tags: Algorithms, Computer science, MPI, nVidia, Performance, Sorting

March 28, 2011 by hgpu

A parallelization cost model for GPU

Zhang Dan, Zhao Rongcai, Han Lin, Wang Tao, Qu Jin

Tags: Computer science, Optimization, Performance

March 27, 2011 by hgpu

Modeling GPU-CPU Workloads and Systems

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8600 GS, nVidia GeForce GTX 280, Performance, Task scheduling, Tesla C1060

March 23, 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

Improving accuracy for matrix multiplications on GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Performance

March 22, 2011 by hgpu

Performance comparison of FPGA, GPU and CPU in image processing

Shuichi Asano, Tsutomu Maruyama, Yoshiki Yamaguchi

Tags: Filtering, FPGA, Image processing, Performance

March 21, 2011 by hgpu

An approach for the effective utilization of GP-GPUs in parallel combined simulation

David W. Bauer, Matthew McMahon, Ernest H. Page

Tags: Computer science, Heterogeneous systems, Partial differential equations, PDEs, Performance

March 21, 2011 by hgpu

Joint Forces: From Multithreaded Programming to GPU Computing

Frank Feinbube, Peter Troger, Andreas Polze

Tags: Computer science, Optimization, Performance

March 20, 2011 by hgpu

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

J. Myre, S. D. C. Walsh, D. Lilja, M. O. Saar

Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, OpenMP, Performance

March 17, 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

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Application of the OpenCL API for Implementation of the NIPALS Algorithm for Principal Component Analysis of Large Data Sets

Evaluation Framework for GPU Performance Based on OpenCL Standard

An Empirically Optimized Radix Sort for GPU

A parallelization cost model for GPU

Modeling GPU-CPU Workloads and Systems

Aspects of GPU for general purpose high performance computing

Improving accuracy for matrix multiplications on GPUs

Performance comparison of FPGA, GPU and CPU in image processing

An approach for the effective utilization of GP-GPUs in parallel combined simulation

Joint Forces: From Multithreaded Programming to GPU Computing

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on 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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