NVIDIA GPU Programming Training Course

Course Code

CUDAProg

Duration

14 hours (usually 2 days including breaks)

Requirements

C Programming, Linux GCC

Overview

This course covers how to program GPUs for parallel computing. Some of the applications include deep learning, analytics, and engineering applications.

Course Outline

Day 1 - Introduction and Basics

  1. Why Parallel Computing? Need for parallel Computing
  2. Multi-Core processors - Architecture and Design
  3. Introduction to Threads, Thread Basics and Basic concepts of parallel programming
  4. OpenMP- A Standard for Directive based Parallel Programming
  5. Hands on / Demonstration of various programs on multicore machines

Day 2 - GPU Programming

  1. GPU's for parallel Computing
  2. GPU's Programming Model
  3. Hands on /Demonstration of various programs on GPU
  4. SDK, Toolkit and Installation of environemnt for GPU
  5. Working with various Libraries
  6. Demonstration of GPU and Tools with Sample Programs and OpenACC

Testimonials

★★★★★
★★★★★

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