high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Weifeng Liu

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Tags: Algorithms, AMD Radeon R9 290X, ATI, Benchmarking, Computer science, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan Black, OpenCL, Sparse matrix, Thesis

February 16, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

High-Performance Tensor Contractions for GPUs

A. Abdelfattah, M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, Tz. Kolev, I. Masliah, S. Tomov

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Tags: Algorithms, Code generation, Computer science, CUDA, FEM, Finite element method, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Tesla K40

January 29, 2016 by hgpu

Batched Linear Algebra Problems on GPU Accelerators

Tingxing Dong

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40, Thesis

January 4, 2016 by hgpu

Study of basic vector operations on Intel Xeon Phi and NVIDIA Tesla using OpenCL

Edoardo Coronado, Guillermo Indalecio, Antonio Garcia-Loureiro

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Tags: Computer science, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Performance, Tesla S2050

December 31, 2015 by hgpu

CuMF: scale matrix factorization using just ONE machine with GPUs

Wei Tan, Liangliang Cao

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Tags: Computer science, CUDA, Data parallelism, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX Titan X

December 6, 2015 by hgpu

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Anton Lokhmotov

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Tags: ARM, Benchmarking, Computer science, Linear Algebra, Mathematical Software, Matrix multiplication, OpenCL, Package, Performance

November 13, 2015 by hgpu

Efficient Sparse Matrix-Vector Multiplication on GPUs using the CSR Storage Format

Joseph L. Greathouse, Mayank Daga

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Tags: Algorithms, AMD FirePro W9100, ATI, Computer science, Linear Algebra, OpenCL, Sparse matrix

November 4, 2015 by hgpu

Structural Agnostic SpMV: Adapting CSR-Adaptive for Irregular Matrices

Mayank Daga, Joseph L. Greathouse

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Tags: Algorithms, AMD FirePro W9100, APU, ATI, Computer science, Linear Algebra, OpenCL, Package, Sparse matrix

November 3, 2015 by hgpu

A general tridiagonal solver for coprocessors: Adapting g-Spike for the Intel Xeon Phi

Ioannis E. Venetis, Alexandros Sobczyk, Alexandros Kouris, Alexandros Nakos, Nikolaos Nikoloutsakos, Efstratios Gallopoulos

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Tags: Computer science, Factorization, Intel Xeon Phi, Linear Algebra, nVidia

October 31, 2015 by hgpu

Padding Free Bank Conflict Resolution for CUDA-Based Matrix Transpose Algorithm

Ayaz ul Hassan Khan, Mayez Al-Mouhamed, Allam Fatayer, Anas Almousa, Abdulrahman Baqais, Mohammed Assayony

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 7000, Performance

October 29, 2015 by hgpu

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K40

October 22, 2015 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

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

High-Performance Tensor Contractions for GPUs

Batched Linear Algebra Problems on GPU Accelerators

Study of basic vector operations on Intel Xeon Phi and NVIDIA Tesla using OpenCL

CuMF: scale matrix factorization using just ONE machine with GPUs

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Efficient Sparse Matrix-Vector Multiplication on GPUs using the CSR Storage Format

Structural Agnostic SpMV: Adapting CSR-Adaptive for Irregular Matrices

A general tridiagonal solver for coprocessors: Adapting g-Spike for the Intel Xeon Phi

Padding Free Bank Conflict Resolution for CUDA-Based Matrix Transpose Algorithm

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

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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