GPU

• Graphics Processing Unit

• https://www.omnisci.com/technical-glossary/cpu-vs-gpu

• GPUs offer many cores, but narrow instruction set and lower clock speed

• VS video card: Video Card generated feed of output images; has a GPU in its core. Also usually has dedicated RAM (unlike integrated video cards that share RAM with the rest of the system).

• GPUs offer many cores, but narrow instruction set and lower clock speed

• Major brands: NVIDIA (GeeForce), AMD Radeon, Intel.

CUDA

• CUDA - NVIDIA's platform and API for accessing their GPU's instruction sets. CUDA-powered GPUs also support open standards like OpenMP or OpenCL.

• Natively supports C, C++, Fortran. Third-party wrappers exist for Python, Ruby and many other languages.

• Parallelize functions by making a function doing only a part of the job depending on its thread id.

• Threads are grouped into blocks; blocks form a grid.

• Lower-level Driver API and higher-level Runtime API.

• https://developer.nvidia.com/how-to-cuda-c-cpp

DL

Thinks like convolution or even matrix multiplication can easily be parallelized to run much faster on GPU.