Remote Sensing | Free Full-Text | Accelerating a Geometrical Approximated PCA Algorithm Using AVX2 and CUDA
GitHub - gsheni/MatrixMultiplication: A matrix multiplication implementation in C and CUDA.
Summit User Guide — OLCF User Documentation
Comparing the performance of general matrix multiplication routine on heterogeneous computing systems - ScienceDirect
Fast Multidimensional Matrix Multiplication on CPU from Scratch
CUTLASS: Fast Linear Algebra in CUDA C++ | NVIDIA Technical Blog
Inq, a Modern GPU-Accelerated Computational Framework for (Time-Dependent) Density Functional Theory | Journal of Chemical Theory and Computation
Single instruction, multiple data - Wikipedia
CUTLASS: Fast Linear Algebra in CUDA C++ | NVIDIA Technical Blog
CUTLASS: Fast Linear Algebra in CUDA C++ | NVIDIA Technical Blog
CUDA C++ Programming Guide
GPU matrix multiplication with C# – Coding Stuff
Towards Optimal Fast Matrix Multiplication on CPU-GPU Platforms | SpringerLink
A sparse matrix‐vector multiplication method with low preprocessing cost - Aktemur - 2018 - Concurrency and Computation: Practice and Experience - Wiley Online Library
CUTLASS: Fast Linear Algebra in CUDA C++ | NVIDIA Technical Blog
CUDA C++ Best Practices
python - Matrix multiplication on CPU (numpy) and GPU (gnumpy) give different results - Stack Overflow
Speedup trends of Parallel Matrix Multiplication using OpenMP, TBB,... | Download Scientific Diagram
tensorflow - Why can GPU do matrix multiplication faster than CPU? - Stack Overflow
CUDA C++ Programming Guide
How to increase speed transfer of matrices GPU<->CPU for matrix multiplication (it is the limiting factor). - CUDA Programming and Performance - NVIDIA Developer Forums
Main code of the draw matrix tile method. | Download Scientific Diagram
How to increase speed transfer of matrices GPU<->CPU for matrix multiplication (it is the limiting factor). - CUDA Programming and Performance - NVIDIA Developer Forums
gpu - Matrix-vector multiplication in CUDA: benchmarking & performance - Stack Overflow
GitHub - pnnl/s-blas: This package includes the implementation for four sparse linear algebra kernels: Sparse-Matrix-Vector-Multiplication (SpMV), Sparse-Triangular-Solve (SpTRSV), Sparse-Matrix-Transposition (SpTrans) and Sparse-Matrix-Matrix ...
High-Performance Matrix Multiplication : r/cpp
Matrix-Matrix Multiplication on the GPU with Nvidia CUDA | QuantStart
GPU matrix multiplication with C# – Coding Stuff
