Fundamentals of Accelerated Computing with OpenACC

Date and Time

The course will be held online on April 16 from 9:00 a.m. to 5:00 p.m. (CEST).

Registered participants will receive the Zoom participation link via email the day before the course begins.

Prerequisites

A free NVIDIA developer account is required to access the course material. Please register before the training at https://learn.nvidia.com/join.

Participants should additionally meet the following requirements:

• Basic competency in C/C++ or Fortran, including familiarity with variable types, loops, conditional statements, functions, and array manipulations
• No previous knowledge of GPU programming is required

Learning Objectives

At the conclusion of the workshop, participants will have an understanding of the fundamental tools and techniques for GPU-accelerating C++ and Fortran applications with OpenACC and will be able to:

• Profile and optimize CPU-only applications to identify hotspots for acceleration
• Use OpenACC directives to GPU-accelerate your codebase
• Optimize data movement between the CPU and GPU accelerators

Course Structure

Introduction to Parallel Programming

• Introduction to parallelism
• The goals of OpenACC
• Basic parallelization of code using OpenACC

Profiling with OpenACC

• Compiling sequential and OpenACC code
• The importance of code profiling
• Profiling sequential and OpenACC multicore code
• Technical introduction to the code used in introductory modules

Introduction to OpenACC Directives

• The Parallel directive
• The Kernels directive
• The Loop directive

GPU Programming with OpenACC

• Definition of a GPU
• Basic OpenACC data management
• CUDA Unified Memory
• Profiling GPU applications

Data Management with OpenACC

• OpenACC data directive/clauses
• OpenACC structured data region
• OpenACC unstructured data region
• OpenACC update directive
• Data management with C/C++ Structs/Classes

Loop Optimizations with OpenACC

• Seq/Auto clause
• Independent clause
• Reduction clause
• Collapse clause
• Tile clause
• Gang, Worker, Vector

Certification

Upon successfully completing the course assessments, participants will receive an NVIDIA DLI Certificate, recognizing their subject matter expertise and supporting their professional career growth.

Instructors

Dr. Sebastian Kuckuk, certified NVIDIA DLI Ambassador.

The course is co-organised by NHR@FAU and the NVIDIA Deep Learning Institute (DLI).

Prices and Eligibility

This course is open and free of charge for participants affiliated with academic institutions in European Union (EU) member states and Horizon 2020-associated countries.