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Evaluation of computational and energy performance in matrix multiplication algorithms on CPU and GPU using MKL, cuBLAS and SYCL

L.A. Torres, Carlos J. Barrios H, Yves Denneulin

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia A100, Package, Performance, SYCL

June 2, 2024 by hgpu

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Jianhua Gao, Bingjie Liu, Weixing Ji, Hua Huang

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Tags: Computer science, FPGA, Heterogeneous systems, Linear Algebra, Machine learning, Overview, Sparse matrix

April 14, 2024 by hgpu

Seer: Predictive Runtime Kernel Selection for Irregular Problems

Ryan Swann, Muhammad Osama, Karthik Sangaiah, Jalal Mahmud

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, Linear Algebra, load balancing, Performance, Sparse matrix

April 7, 2024 by hgpu

Parallel Gaussian process with kernel approximation in CUDA

Davide Carminati

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Tags: Benchmarking, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2080, Package

March 24, 2024 by hgpu

Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

Andres E. Tomas, Enrique S. Quintana-Orti, Hartwig Anzt

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100

March 18, 2024 by hgpu

Performance Optimization of Deep Learning Sparse Matrix Kernels on Intel Max Series GPU

Mohammad Zubair, Christoph Bauinger

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Tags: Computer science, CUDA, Deep learning, Intel, Intel Data Center GPU Max 1550, Linear Algebra, Machine learning, Mathematical Software, Matrix multiplication, nVidia, nVidia V100, Sparse matrix, SYCL

November 5, 2023 by hgpu

Bandicoot: C++ Library for GPU Linear Algebra and Scientific Computing

Ryan R. Curtin, Marcus Edel, Conrad Sanderson

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Programming techniques

July 30, 2023 by hgpu

Improving the Performance, Portability, and Productivity of Hardware Accelerators

Pablo Antonio Martínez Sánchez

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 2080 Ti, Performance, performance portability, Thesis

July 16, 2023 by hgpu

DGEMM on Integer Matrix Multiplication Unit

Hiroyuki Ootomo, Katsuhisa Ozaki, Rio Yokota

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Tags: Computer science, CUBLAS, CUDA, Deep learning, Linear Algebra, Machine learning, Matrix multiplication, nVidia, nVidia A100, nVidia Jetson AGX Orin, nVidia RTX 6000 Ada, nVidia Titan RTX, Package

June 25, 2023 by hgpu

Improving Energy Efficiency of Basic Linear Algebra Routines on Heterogeneous Systems with Multiple GPUs

Hadi Zamani Sabzi

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Factorization, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 1660, nVidia GeForce GTX 980, Thesis

May 21, 2023 by hgpu

Anatomy of High-Performance GEMM with Online Fault Tolerance on GPUs

Shixun Wu, Yujia Zhai, Jinyang Liu, Jiajun Huang, Zizhe Jian, Bryan M. Wong, Zizhong Chen

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Tags: Code generation, Computer science, CUDA, GEMM, Linear Algebra, Matrix multiplication, nVidia, nVidia A100, Package, Performance, Reliability, Tesla T4

May 7, 2023 by hgpu

Optimizing High-Performance Linpack for Exascale Accelerated Architectures

Noel Chalmers, Jakub Kurzak, Damon McDougall, Paul T. Bauman

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, Computer science, Factorization, HIP, Linear Algebra, MPI, Package, Performance

April 23, 2023 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

Evaluation of computational and energy performance in matrix multiplication algorithms on CPU and GPU using MKL, cuBLAS and SYCL

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Seer: Predictive Runtime Kernel Selection for Irregular Problems

Parallel Gaussian process with kernel approximation in CUDA

Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

Performance Optimization of Deep Learning Sparse Matrix Kernels on Intel Max Series GPU

Bandicoot: C++ Library for GPU Linear Algebra and Scientific Computing

Improving the Performance, Portability, and Productivity of Hardware Accelerators

DGEMM on Integer Matrix Multiplication Unit

Improving Energy Efficiency of Basic Linear Algebra Routines on Heterogeneous Systems with Multiple GPUs

Anatomy of High-Performance GEMM with Online Fault Tolerance on GPUs

Optimizing High-Performance Linpack for Exascale Accelerated Architectures

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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