Translations:CUDA tutorial/1/en
Introduction
This tutorial introduces the graphics processing unit (GPU) as a massively parallel computing device; the CUDA parallel programming language; and some of the CUDA numerical libraries for high performance computing.
This tutorial uses CUDA to accelerate C or C++ code: a working knowledge of one of these languages is therefore required to gain the most benefit. Even though Fortran is also supported by CUDA, for the purpose of this tutorial we only cover CUDA C/C++. From here on, we use term CUDA C to refer to CUDA C/C++. CUDA C is essentially a C/C++ that allows one to execute functions on both GPUs and CPUs.
- Understand the architecture of a GPU
- Understand the workflow of a CUDA program
- Manage and understand the various types of GPU memories
- Write and compile an example of CUDA code
What is a GPU?
A GPU, or graphics processing unit, is a single-chip processor that performs rapid mathematical calculations for the purpose of rendering images. In the recent years however, such capability has been harnessed more broadly to accelerate computational workloads in cutting-edge scientific research.