The course teaches how to run CUDA programs on Google Colab and online without a GPU, covers basics of CUDA programming and terminologies like Host, Device, Kernel, Thread, Block, Grid, and Warp. It also delves into CUDA memory and GPU architecture, and includes practical exercises on vector and array addition, matrix addition, and matrix multiplication using shared memory. The intended audience for this course is individuals interested in parallel computing and GPU programming.
Overview
Syllabus
How to run CUDA program on Google Colab | How to run CUDA program online | Run CUDA prog without GPU.
Basics of CUDA Programming | CUDA Terminologies | Host, Device, Kernel, Thread, Block, Grid, Warp.
CUDA Memory Architecture of GPU | CUDA GPU Architecture.
CUDA Vector Addition Program | Basics of CUDA Programming with CUDA Array Addition with All Cases.
CUDA Matrix Addition | CUDA Program for Matrices Addition | CUDA Programming.
CUDA Matrix Multiplication Shared Memory | CUDA Matrix Multiplication Code and Tutorial.
CUDA Terminologies | Basics of CUDA.
CUDA: Memory Architecture of GPU.
What is CUDA | Basics of CUDA | Terminologies in CUDA.
Taught by
Comrevo
