POSTPONED: Introduction to GPU programming: When and how to use GPU-acceleration?

Introduction to GPU programming: When and how to use GPU-acceleration?

ATTENTION: Due to the current situation with the covid-19 virus, the course has been postponed. More information will follow.

GPU-acceleration has been shown to provide significant performance benefits in many different applications. However, for a novice, or even for a moderately experienced scientist or programmer, it is not always clear which applications could potentially benefit from GPU-acceleration and which do not. For example, a Nvidia V100 GPU can perform artificial intelligence (AI) related computations in a fraction of the time it takes a regular CPU to perform the same computations but ill-informed OpenACC compiler pragma can actually make a code run slower. Why is this? When should one invest time in GPU-acceleration? How much speedup can be expected with a given application?

Purpose: The main goal of this one day course is to start answering these questions. The course also covers the basics of GPU programming and aims to provide the necessary information for avoiding the most common pitfalls.

Requirements:

• The course does not require any existing GPU programming knowledge but basic understanding of the C language is required for the hands-ons.
• For the hand-on practicals participants should bring a laptop. The laptop should be able to access the internet via eduroam (needs to be arranged in your home institution) and have a ssh-client installed.
• All participants should register in the SUPR-portal prior to the course start (more info will be sent out to registered participants prior to course start).

Date: 2020-04-21
Time: 9:00-17:00
Location: Chalmers center for computational science and engineering (C3SE), Chalmers, Göteborg
Room PJ at Campus Johanneberg, building Fysik Origo, entrance from Fysikgården 2B, Entrance floor.
Instructors: Mirko Myllykoski (mirkom@cs.umu.se)
Deadline for registration: 2020-04-15

Schedule

To be announced.

Coffee and tea will be provided. Please bring a laptop for the hands-on. 

Materials (previous course, to be updated)

• Example codes: https://git.cs.umu.se/mirkom/gpu_course
• Introduction to the course
• Introduction to HPC2N and Kebnekaise
• GPU hardware and CUDA basics
• Where is my performance?

Registration

Registration conditions: The registration becomes binding 7 days before the course begins. No-shows and late cancellations (less than 7 day in advance) are fined a fee (500 SEK) and may be blacklisted from attending future workshops at C3SE.

Please fill in the below form to sign up. All fields marked with * are required.