high performance computing on graphics processing units: hgpu.org

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Sparse systems solving on GPUs with GMRES

Raphael Couturier, Stephane Domas

Tags: Computer science, CUBLAS, CUDA, nVidia, Sparse linear iterative solvers, Sparse matrix

February 18, 2011 by hgpu

EigenCFA: accelerating flow analysis with GPUs

Tarun Prabhu, Shreyas Ramalingam, Matthew Might, Mary Hall

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Tags: Computer science, CUBLAS, Flow analysis, nVidia, nVidia GeForce GTX 480, Optimization

February 11, 2011 by hgpu

Evaluating multi-core platforms for HPC data-intensive kernels

Alexander S. van Amesfoort, Ana Lucia Varbanescu, Henk J. Sips, Rob V. van Nieuwpoort

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Tags: Algorithms, Cell processor, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Programming techniques, Tesla C1060

February 6, 2011 by hgpu

Uncontracted Rys Quadrature Implementation of up to G Functions on Graphical Processing Units

Andrey Asadchev, Veerendra Allada, Jacob Felder, Brett M. Bode, Mark S. Gordon and Theresa L. Windus

Tags: Chemistry, CUBLAS, CUDA, Molecular modeling, Molecular simulation, nVidia, nVidia GeForce GTX 275, Tesla T10

February 1, 2011 by hgpu

Fast development of dense linear algebra codes on graphics processors

M. Jesus Zafont, Alberto F. Martin, Francisco Igual, Enrique S. Quintana-Orti

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

January 20, 2011 by hgpu

A Mixed-Precision Algorithm for the Solution of Lyapunov Equations on Hybrid CPU-GPU Platforms

Peter Benner, Pablo Ezzatti, Daniel Kressner, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: CUBLAS, CUDA, Mathematics, Mixed precision, nVidia, Tesla C1060

January 16, 2011 by hgpu

Neville elimination on multi- and many-core systems: OpenMP, MPI and CUDA

P. Alonso, R. Cortina, F. Martinez-Zaldivar, J. Ranilla

Tags: Computer science, CUBLAS, CUDA, MPI, nVidia, OpenMP

January 10, 2011 by hgpu

Evaluation and tuning of the Level 3 CUBLAS for graphics processors

S. Barrachina, M. Castillo, F. D. Igual, R. Mayo, E. S. Quintana-Orti

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

January 9, 2011 by hgpu

BLAS Comparison on FPGA, CPU and GPU

Srinidhi Kestur, John D. Davis, Oliver Williams

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Tags: BLAS, Computer science, CUBLAS, CUDA, Energy-efficient computing, FPGA, Linear Algebra, nVidia, nVidia GeForce 9500 GT, Performance, Tesla C1060

December 6, 2010 by hgpu

A GPGPU compiler for memory optimization and parallelism management

Yi Yang, Ping Xiang, Jingfei Kong, Huiyang Zhou

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Source codes

Tags: Computer science, CUBLAS, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Package

November 18, 2010 by hgpu

Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

Stanimire Tomov, Rajib Nath, Jack Dongarra

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Source codes

Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Package

November 17, 2010 by hgpu

Parallel GPU Implementation of Iterative PCA Algorithms

M. Andrecut

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Tags: Algorithms, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

November 13, 2010 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

Sparse systems solving on GPUs with GMRES

EigenCFA: accelerating flow analysis with GPUs

Evaluating multi-core platforms for HPC data-intensive kernels

Uncontracted Rys Quadrature Implementation of up to G Functions on Graphical Processing Units

Fast development of dense linear algebra codes on graphics processors

A Mixed-Precision Algorithm for the Solution of Lyapunov Equations on Hybrid CPU-GPU Platforms

Neville elimination on multi- and many-core systems: OpenMP, MPI and CUDA

Evaluation and tuning of the Level 3 CUBLAS for graphics processors

BLAS Comparison on FPGA, CPU and GPU

A GPGPU compiler for memory optimization and parallelism management

Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

Parallel GPU Implementation of Iterative PCA Algorithms

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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