FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA C/C++ ONLINE TRAINING - EORIC

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• eoric_admin
• April 4, 2022

Course Description

Fundamentals of Accelerated Computing with CUDA C/C++ workshop hosted by NVIDIA DLI and the Earth Observation Research & Innovation Centre (EORIC).

This workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA®. You’ll learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that you’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. At the end of the workshop, you’ll have access to additional resources to create new GPU-accelerated applications on your own.

Learning Objectives

At the conclusion of the workshop, you’ll have an understanding of the fundamental tools and techniques for GPU-accelerating C/C++ applications with CUDA and be able to:

• Write code to be executed by a GPU accelerator
• Expose and express data and instruction-level parallelism in C/C++ applications using CUDA
• Utilize CUDA-managed memory and optimize memory migration using asynchronous prefetching
• Leverage command line and visual profilers to guide your work
• Utilize concurrent streams for instruction-level parallelism
• Write GPU-accelerated CUDA C/C++ applications, or refactor existing CPU-only applications, using a profile-driven approach

Why Deep Learning Institute Hands-On Training?

• Learn to build deep learning and accelerated computing applications for industries such as autonomous vehicles, finance, game development, healthcare, robotics, and more.
• Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
• Gain real-world expertise through content designed in collaboration with industry leaders such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.
• Earn an NVIDIA DLI certificate to demonstrate your subject matter competency and support career growth.
• Access content anywhere, anytime with a fully configured, GPU-accelerated workstation in the cloud.

Date, Venue, Fee

• Date: Date to be communicated soon
• Venue: Online
• Fee: Free

Prerequisites

To get the most out of this lab you should already be able to:

• Declare variables, write loops, and use if / else statements in C.
• Define and invoke functions in C.
• Allocate arrays in C.

No previous CUDA knowledge is required.

Registration

• Deadline for Registration: Friday, 22nd April 2022
• Click here to register (Only 20 Participants will be selected)

Contacts

• Mobile: 055 006 0038 / 055 168 2072
• Email: eoric@uenr.edu.gh