Introduction to GPU computing with CUDA

Introduction to GPU computing with CUDA, available at $34.99, has an average rating of 4.58, with 14 lectures, based on 161 reviews, and has 873 subscribers.

You will learn about Understanding the basics of parallel programming on GPU. Understanding the basics of GPU architecture. Writing simple programs in CUDA language. This course is ideal for individuals who are People aiming at a first approach to parallel programming on GPUs. It is particularly useful for People aiming at a first approach to parallel programming on GPUs.

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Summary

Title: Introduction to GPU computing with CUDA

Price: $34.99

Average Rating: 4.58

Number of Lectures: 14

Number of Published Lectures: 14

Number of Curriculum Items: 14

Number of Published Curriculum Objects: 14

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Understanding the basics of parallel programming on GPU.
Understanding the basics of GPU architecture.
Writing simple programs in CUDA language.

Who Should Attend

People aiming at a first approach to parallel programming on GPUs.

Target Audiences

People aiming at a first approach to parallel programming on GPUs.

Self-driving cars, machine learning and augmented reality are some of the examples of modern applications that involve parallel computing.�

With the availability of high performance GPUs and a language, such as CUDA, which greatly simplifies programming, everyone can have at home and easily use a supercomputer.�

The aim of this course is to provide the basics of the architecture of a graphics card and allow a first approach to CUDA programming by developing simple examples with a growing degree of difficulty.

Course Curriculum

Chapter 1: Introduction and Basics

Lecture 1: Introduction to GPU Computing with CUDA

Lecture 2: CUDA and the Related Parallelization Paradigms

Lecture 3: Threads Blocks Cores and Streaming Multiprocessors

Lecture 4: Heterogeneous Computing and NVIDIA Compiler Driver

Lecture 5: CUDA Download Installation and IDEs

Chapter 2: Cuda Programming

Lecture 1: CUDA Program Workflow and Simple Example – Part 01

Lecture 2: Simple Example – Part 02

Lecture 3: Error Checking and Simple Example – Part 03

Chapter 3: Memories and Performance

Lecture 1: CUDA Memories

Lecture 2: CUDA Profiling and the Visual Profiler

Lecture 3: Coalesced Global Memory Accesses

Lecture 4: Shared Memory and Adjacent Differences

Lecture 5: Shared Memory and Moving Average Example

Lecture 6: Two Dimensional Grids

Instructors

Orange Owl
Consultants

Rating Distribution

1 stars: 12 votes
2 stars: 15 votes
3 stars: 35 votes
4 stars: 50 votes
5 stars: 49 votes

Frequently Asked Questions

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