high performance computing on graphics processing units: hgpu.org

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MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing

Azzam Haidar, Stanimire Tomov, Piotr Luszczek, Jack Dongarra

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia Jetson TK1, Package

October 6, 2015 by hgpu

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Terry Cojean, Abdou Guermouche, Andra Hugo, Raymond Namyst, Pierre-Andre Wacrenier

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, OpenMP, Task scheduling, Tesla K40

August 5, 2015 by hgpu

Flexible Linear Algebra Development and Scheduling with Cholesky Factorization

Azzam Haidar, Chongxiao Cao, Stanimire Tomov, Asim YarKhan, Piotr Luszczek, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, nVidia, Tesla M2090

August 5, 2015 by hgpu

Dense Symmetric Indefinite Factorization on GPU Accelerated Architectures

Marc Baboulin, Jack Dongarra, Adrien Remy, Stanimire Tomov, Ichitaro Yamazaki

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40

August 5, 2015 by hgpu

Bulk GCD Computation Using a GPU to Break Weak RSA Keys

Toru Fujita, Koji Nakano, Yasuaki Ito

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 780 Ti, Security

June 19, 2015 by hgpu

Algorithm 9xx: Sparse QR Factorization on the GPU

Sencer Nuri Yeralan, Timothy A. Davis, Sanjay Ranka

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Package, Sparse matrix, Tesla C2070

April 25, 2015 by hgpu

Framework for Batched and GPU-resident Factorization Algorithms Applied to Block Householder Transformations

Azzam Haidar, Tingxing "Tim" Dong, Stanimire Tomov, Piotr Luszczek, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

April 12, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40

April 12, 2015 by hgpu

Fast Radix Sort for Sparse Linear Algebra on GPU

Lukas Polok, Viorela Ila, Pavel Smrz

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780, OpenCL, Sorting, Sparse matrix

March 18, 2015 by hgpu

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Edgardo Mejia-Roa, Daniel Tabas-Madrid, Javier Setoain, Carlos Garcia, Francisco Tirado, Alberto Pascual-Montano

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Factorization, GPU cluster, MPI, Nonnegative matrix factorization, nVidia, Package, Tesla C1060

February 19, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators Based on GPUs

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

January 15, 2015 by hgpu

Hierarchical DAG Scheduling for Hybrid Distributed Systems

Wei Wu, Aurelien Bouteiller, George Bosilca, Mathieu Faverge, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40, Tesla M2090

January 5, 2015 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

MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Flexible Linear Algebra Development and Scheduling with Cholesky Factorization

Dense Symmetric Indefinite Factorization on GPU Accelerated Architectures

Bulk GCD Computation Using a GPU to Break Weak RSA Keys

Algorithm 9xx: Sparse QR Factorization on the GPU

Framework for Batched and GPU-resident Factorization Algorithms Applied to Block Householder Transformations

Batched Matrix Computations on Hardware Accelerators

Fast Radix Sort for Sparse Linear Algebra on GPU

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Batched Matrix Computations on Hardware Accelerators Based on GPUs

Hierarchical DAG Scheduling for Hybrid Distributed Systems

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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