Matrix Multiplication using GPU (CUDA)

Cuda Matrix Implementation using Global and Shared memory.

The input follows this pattern:

1. The number of lines of Matrix A
2. The number of columns of Matrix A
3. The number of lines of Matrix B
4. The number of columns of Matrix B
5. The values of Matrix A
6. The values of Matrix B

The Shared method was implemented by dividing the Matrices into blocks.

Tests

Here is a few tests with a GeForce GTX 960M. The times are in milliseconds.

I ran the test 7 times for each line number and then averaged it.

And the difference in time between global and shared memory.

Usage

0. (optional) Use the script generate_input.py to generate a random Matrix
1. Compile it & Run it