Embedded Machine Learning

Course Overview

Modern GPUs are powerful high-core-count processors. They are no longer used solely for graphics applications, but are also employed to accelerate computationally intensive general-purpose tasks. In this course, we will look in detail at the GPU’s internal architecture, the differences to general-purpose processors like CPUs, and how to program GPUs. Powerful GPUs are available for exercises and experiments. If we have enough time, we may consider a short introduction to IPUs (Intelligence Processing Units) as well.

Contents

• GPU architecture
• CUDA programming
• Parallel programming
• Scheduling/code/shared memory optimizations
• Introduction to multi-GPU programming
• Advanced GPU architecture
• Introduction to OpenCL & OpenACC

Requirements

Recommended is solid knowledge of C/C++ and the basics of computer architecture.

Notes

• Course starts Oct 17 14:00 c.t.
• Start of exercise is to be negotiated with the teaching assistant.
• Room is OMZ/INF350 basement, U014. Enter the building from the east. If you don’t see a ZITI sign, you are probably at a wrong place.