high performance computing on graphics processing units: hgpu.org

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Application of GPUs for the Calculation of Two Point Correlation Functions in Cosmology

Rafael Ponce, Miguel Cardenas-Montes, Juan Jose Rodriguez-Vazquez, Eusebio Sanchez, Ignacio Sevilla

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Tags: Algorithms, Astrophysics, Computational Physics, Cosmology, Cosmology and Extragalactic Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, MPI, nVidia, nVidia GeForce GTX 295, Package, Tesla C1060, Tesla C2050

May 1, 2012 by hgpu

Image Convolution Processing: a GPU versus FPGA Comparison

Lucas M. Russo, Emerson C. Pedrino, Edilson Kato, Valentin Obac Roda

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Tags: CUDA, FPGA, Image processing, nVidia, nVidia GeForce GTX 295, Performance

April 21, 2012 by hgpu

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

James Bergstra, Nicolas Pinto, David Cox

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Tags: Computer science, CUDA, Filtering, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Optimization, Tesla C1060, Tesla C2070

March 29, 2012 by hgpu

Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs

Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 295, Performance, Sparse matrix

March 21, 2012 by hgpu

Generating optimal CUDA sparse matrix-vector product implementations for evolving GPU hardware

Ahmed H. El Zein, Alistair P. Rendell

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 295, Performance, Sparse matrix, Tesla S2050

March 19, 2012 by hgpu

GPU Enhanced Simulation of Angiogenesis

Marcin Worecki, Rafal Wcislo

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Tags: CUDA, Medicine, nVidia, nVidia GeForce GTX 295

March 19, 2012 by hgpu

Usable assembly language for GPUs: a success story

Daniel J. Bernstein, Hsieh-Chung Chen, Chen-Mou Cheng, Tanja Lange, Ruben Niederhagen, Peter Schwabe, Bo-Yin Yang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Performance, PTX, Security

March 18, 2012 by hgpu

Globally scheduled real-time multiprocessor systems with GPUs

Glenn A. Elliott, James H. Anderson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Task scheduling

March 16, 2012 by hgpu

Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

Seung In Park, Yong Cao, Layne T. Watson, Francis Quek

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 295, Performance

March 10, 2012 by hgpu

PartialRC: A Partial Recomputing Method for Efficient Fault Recovery on GPGPUs

Xin-Hai Xu, Xue-Jun Yang, Jing-Ling Xue, Yu-Fei Lin, Yi-Song Lin

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Tags: Computer science, CUDA, Fault tolerance, Heterogeneous systems, nVidia, nVidia GeForce GTX 295

March 6, 2012 by hgpu

GPGPU and Multi-Core Architectures for Computing Clustering Coefficients of Irregular Graphs

A. Leist, K.A. Hawick, D.P. Playne

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Tags: Algorithms, Cell processor, Clustering, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480

January 24, 2012 by hgpu

Exploratory research on embedding CUDA code into hetrogeneous MP-SOC achitectures programmed with the Daedalus framework

Rick van der Zwet

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 295, Package, Thesis

January 23, 2012 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Application of GPUs for the Calculation of Two Point Correlation Functions in Cosmology

Image Convolution Processing: a GPU versus FPGA Comparison

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs

Generating optimal CUDA sparse matrix-vector product implementations for evolving GPU hardware

GPU Enhanced Simulation of Angiogenesis

Usable assembly language for GPUs: a success story

Globally scheduled real-time multiprocessor systems with GPUs

Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

PartialRC: A Partial Recomputing Method for Efficient Fault Recovery on GPGPUs

GPGPU and Multi-Core Architectures for Computing Clustering Coefficients of Irregular Graphs

Exploratory research on embedding CUDA code into hetrogeneous MP-SOC achitectures programmed with the Daedalus framework

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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