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MAGMA Batched: A Batched BLAS Approach for Small Matrix Factorizations and Applications on GPUs

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

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Tags: BLAS, Computer science, CUDA, Factorization, Fluid dynamics, Linear Algebra, nVidia, Tesla K40

August 23, 2016 by hgpu

A Comparison of Potential Interfaces for Batched BLAS Computations

Samuel D. Relton, Pedro Valero-Lara, Mawussi Zounon

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Source codes

Tags: BLAS, Computer science, CUDA, Linear Algbera, nVidia, Package, Tesla K40

August 11, 2016 by hgpu

Parallel experiments with RARE-BLAS

Chemseddine Chohra, Philippe Langlois, David Parello

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Tags: Algorithms, BLAS, Computer science, Intel Xeon Phi, Linear Algebra

August 4, 2016 by hgpu

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix decomposition, Mixed precision, Numerical Analysis, nVidia, Performance, Tesla K20

July 16, 2016 by hgpu

TTC: A Tensor Transposition Compiler for Multiple Architectures

Paul Springer, Aravind Sankaran, Paolo Bientinesi

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Tags: BLAS, Compilers, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, Mathematical Software, nVidia, nVidia GeForce 840 M, Package, Performance, Tesla K40

July 8, 2016 by hgpu

Matrix Multiplication Beyond Auto-Tuning: Rewrite-based GPU Code Generation

Michel Steuwer, Toomas Remmelg, Christophe Dubach

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Tags: ARM, ATI, ATI Radeon HD 7970, BLAS, Code generation, Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX Titan Black, OpenCL, performance portability

July 8, 2016 by hgpu

Tensor Contractions with Extended BLAS Kernels on CPU and GPU

Yang Shi, U. N. Niranjan, Animashree Anandkumar, Cris Cecka

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

June 22, 2016 by hgpu

GPU performance analysis of a nodal discontinuous Galerkin method for acoustic and elastic models

Axel Modave, Amik St-Cyr, Tim Warburton

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Tags: BLAS, Computational Physics, CUBLAS, CUDA, FEM, Finite element method, Geoscience, Linear Algebra, nVidia, nVidia GeForce GTX 980, OCCA, Physics, Profiling, Seismic modeling, Seismology

March 1, 2016 by hgpu

Implementing Level-3 BLAS Routines in OpenCL on Different Processing Units

Kazuya Matsumoto, Naohito Nakasato, Stanislav Sedukhin

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Tags: ATI, ATI Radeon HD 7970, BLAS, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX Titan, OpenCL

October 29, 2014 by hgpu

Petascale computations for Large-scale Atomic and Molecular collisions

Brendan M McLaughlin, Connor P Ballance

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Tags: BLAS, Computational Physics, Computer science, CUDA, Fortran, Molecular simulation, MPI, nVidia, Tesla K20

April 4, 2014 by hgpu

Lessons learned from contrasting a BLAS kernel implementations

Andres More

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Tags: BLAS, Computer science, CUDA, nVidia, nVidia Quadro FX 770 M, Performance

December 12, 2013 by hgpu

Towards a functional run-time for dense NLA domain

Mauro Blanco, Pablo Perdomo, Pablo Ezzatti, Alberto Pardo, Marcos Viera

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Tags: Algorithms, BLAS, Computer science, CUDA, Factorization, Haskell, Linear Algebra, nVidia, nVidia GeForce GTX 570

September 2, 2013 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

MAGMA Batched: A Batched BLAS Approach for Small Matrix Factorizations and Applications on GPUs

A Comparison of Potential Interfaces for Batched BLAS Computations

Parallel experiments with RARE-BLAS

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

TTC: A Tensor Transposition Compiler for Multiple Architectures

Matrix Multiplication Beyond Auto-Tuning: Rewrite-based GPU Code Generation

Tensor Contractions with Extended BLAS Kernels on CPU and GPU

GPU performance analysis of a nodal discontinuous Galerkin method for acoustic and elastic models

Implementing Level-3 BLAS Routines in OpenCL on Different Processing Units

Petascale computations for Large-scale Atomic and Molecular collisions

Lessons learned from contrasting a BLAS kernel implementations

Towards a functional run-time for dense NLA domain

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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