high performance computing on graphics processing units: hgpu.org

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Developing an OO Model for Generalized Matrix Multiplication: Preliminary Considerations

Maria Ganzha, Marcin Paprzycki, Stanislav G. Sedukhin

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Tags: Algorithms, Computer science, Linear Algebra, Matrix multiplication

December 13, 2011 by hgpu

Scalable Query Evaluation in Relational Databases

Rasmus Resen Amossen

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Tags: Algorithms, Computer science, Databases, Matrix multiplication, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Python, Thesis

December 5, 2011 by hgpu

Computation of Large Covariance Matrices by SAMMY on Graphical Processing Units and Multicore CPUs

G. Arbanas, M.E. Dunn, D. Wiarda

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Tags: CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, Nuclear Experiment, nVidia, Physics, Tesla C2050

December 3, 2011 by hgpu

Autotuning GEMMs for Fermi

Jakub Kurzak, Stanimire Tomov, Jack Dongarra

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Tags: Benchmarking, BLAS, Computer science, CUDA, Linear Algebra, Mathematical Software, Matrix multiplication, nVidia, Package, Tesla S2050

November 20, 2011 by hgpu

Auto-tunable GPU BLAS

Jarle Erdal Steinsland

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Tags: Algorithms, ATI, ATI Radeon HD 5750, ATI Radeon HD 5870, BLAS, Computer science, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Optimization, Tesla C2070, Thesis

November 18, 2011 by hgpu

Many-body quantum chemistry on graphics processing units

A. Eugene DePrince III, Jeff R. Hammond, Stephen K. Gray

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Tags: Algorithms, Chemistry, Computational chemistry, CUDA, Heterogeneous systems, Matrix multiplication, Molecular modeling, nVidia, Tesla C2050

November 11, 2011 by hgpu

The conjugate gradient solver accelerated by GPU for solving wave-propagation problems

Chao Chen

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, Linear Algebra, Matrix multiplication, nVidia

November 6, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Fast Implementation of DGEMM on Fermi GPU

Guangming Tan, Linchuan Li, Sean Triechle, Everett Phillips, Yungang Bao, Ninghui Sun

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Optimization, Performance, Tesla C2050

October 17, 2011 by hgpu

Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

W. Zuo, A. McNeil, M. Wetter, E.S. Lee

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Tags: Algorithms, Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 460, OpenCL, Raytracing

October 4, 2011 by hgpu

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUDA, Data parallelism, FFT, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

October 2, 2011 by hgpu

Parallelizing fuzzy rule generation using GPGPU

Takesuke Uenishi, Tomoharu Nakashima and Noriyuki Fujimoto

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 295, Optimization, Performance

September 28, 2011 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

Developing an OO Model for Generalized Matrix Multiplication: Preliminary Considerations

Scalable Query Evaluation in Relational Databases

Computation of Large Covariance Matrices by SAMMY on Graphical Processing Units and Multicore CPUs

Autotuning GEMMs for Fermi

Auto-tunable GPU BLAS

Many-body quantum chemistry on graphics processing units

The conjugate gradient solver accelerated by GPU for solving wave-propagation problems

Matrix inversion speed up with CUDA

Fast Implementation of DGEMM on Fermi GPU

Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Parallelizing fuzzy rule generation using GPGPU

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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