high performance computing on graphics processing units: hgpu.org

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PSCToolkit: solving sparse linear systems with a large number of GPUs

Pasqua D'Ambra, Fabio Durastante, Salvatore Filippone

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Tags: CUDA, Linear Algebra, Mathematical Software, Mathematics, Numerical Analysis, nVidia, nVidia A100, Package, Sparse

July 7, 2024 by hgpu

Performant low-order matrix-free finite element kernels on GPU architectures

Randolph R. Settgast, Yohann Dudouit, Nicola Castelletto, William R. Tobin, Benjamin C. Corbett, Sergey Klevtsov

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Tags: AMD Radeon Instinct MI250X, ATI, FEM, Finite element method, Mathematics, Numerical Analysis, nVidia, nVidia A100, nVidia V100, Package, Sparse

August 28, 2023 by hgpu

GPU Load Balancing

Muhammad Osama

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, load balancing, Matrix multiplication, nVidia, nVidia A100, Package, Sparse, Thesis

December 25, 2022 by hgpu

Providing performance portable numerics for Intel GPUs

Yu-Hsiang M. Tsai, Terry Cojean, Hartwig Anzt

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, OpenCL, Package, performance portability, Sparse, SYCL

October 30, 2022 by hgpu

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU

Jou-An Chen, Hsin-Hsuan Sung, Nathan Tallent, Kevin Barker, Xipeng Shen, Ang Li

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan V, Package, Sparse

January 30, 2022 by hgpu

Porting a sparse linear algebra math library to Intel GPUs

Yuhsiang M. Tsai, Terry Cojean, Hartwig Anzt

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Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, HIP, Linear Algebra, nVidia, Package, Performance, Sparse, Sparse matrix, Tesla V100

March 21, 2021 by hgpu

Hardware Acceleration of HPC Computational Flow Dynamics using HBM-enabled FPGAs

Tom Hogervorst, Tong Dong Qiu, Giacomo Marchiori, Alf Birger, Markus Blatt, Razvan Nane

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Tags: Computer science, CUDA, FPGA, Hardware Architecture, HPC, OpenCL, Sparse

January 10, 2021 by hgpu

Exploring FPGA Optimizations to Compute Sparse Numerical Linear Algebra Kernels

Federico Favaro, Ernesto Dufrechou, Pablo Ezzatti, Juan P. Oliver

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Tags: Computer science, FPGA, Linear Algebra, OpenCL, Optimization, Performance, Sparse

December 6, 2020 by hgpu

AMGCL – A C++ library for efficient solution of large sparse linear systems

Denis Demidov

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Tags: Computer science, CUDA, Mathematical Software, MPI, OpenCL, Package, Sparse, Sparse linear iterative solvers

November 8, 2020 by hgpu

Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse Linear Algebra Computations

Yuhsiang Mike Tsai, Terry Cojean, Hartwig Anzt

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, Performance, Sparse, Sparse matrix

August 23, 2020 by hgpu

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Hartwig Anzt, Terry Cojean, Goran Flegar, Fritz Göbel, Thomas Grützmacher, Pratik Nayak, Tobias Ribizel, Yuhsiang Mike Tsai, Enrique S. Quintana-Ortí

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Tags: Algorithms, AMD Radeon VII, ATI, Computer science, CUDA, HIP, Linear Algebra, Mathematical Software, nVidia, Package, Sparse, Sparse matrix, Tesla V100

July 5, 2020 by hgpu

Synergistic CPU-FPGA Acceleration of Sparse Linear Algebra

Mohammadreza Soltaniyeh, Richard P. Martin, Santosh Nagarakatte

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Tags: Computer science, Factorization, FPGA, HLS, Linear Algebra, Matrix multiplication, OpenCL, Sparse

May 10, 2020 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

PSCToolkit: solving sparse linear systems with a large number of GPUs

Performant low-order matrix-free finite element kernels on GPU architectures

GPU Load Balancing

Providing performance portable numerics for Intel GPUs

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU

Porting a sparse linear algebra math library to Intel GPUs

Hardware Acceleration of HPC Computational Flow Dynamics using HBM-enabled FPGAs

Exploring FPGA Optimizations to Compute Sparse Numerical Linear Algebra Kernels

AMGCL – A C++ library for efficient solution of large sparse linear systems

Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse Linear Algebra Computations

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Synergistic CPU-FPGA Acceleration of Sparse Linear Algebra

Recent source codes

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Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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