README.md

A Simple Example of C level Acceleration Using Parallelism

To start,

$ make
$ ./cpu
$ ./avx2
$ ./cuda

It calculates saxpy function, and print system time elapse.

1. Realization without parallelism: cpu.cpp. Here, you should not use -O3 tag during compilation, otherwise, g++ uses avx2 automatically. Notice this automatic optimization is only achievable for simple functions.
2. CPU parallelism using AVX2 instruction set: avx2.cpp.
3. GPU parallelism using CUDA programming model: cuda.cu. It requires a CUDA library, and compiles using nvcc. Here, you will not see a GPU acceleration! Because the data transfer between system memory and GPU memory has a lot overhead and the complexity of saxpy function is only $O(N)$. To confirm this, time the excution part of program only please, you will see an amazing acceleration.