EE563 Programming Massively Parallel Processors

Schedule

The course will follow the schedule shown below. Component 1 will take place during weeks 1 to 7 while components 2 and 3 will cover weeks 8 to 13.

Wk

Date

Lectures

References

Others

Laboratories

1

21-15 Mai

Introduction to Massively Parallel Computing

Introduction to CUDA

Chap 1-2

Download all lectures

slides in pdf

itune videos

Connect to the CUDA server
(Instructions, videos, commands and example code)

Complete the CUDA Tutorial
(read the entire tutorial and refer back to it as needed throughout the course)

2

28 Mai - 1 Jun

CUDA Threads & Atomic operations

CUDA Memories

Performance Considerations

Chap 3-6

 

Lab 1

(due on 11 Jun)

3

4-8 Jun

Parallel Patterns I

Parallel Patterns II

Chap 7-9

   

4

11-15 Jun

Introduction to Thrust

Sparse Matrix Vector Operations

Chap 10

 NVIDIA Cub example

Lab 2

(due on 25 Jun)

5

18-22 Jun

Solving Partial Differential Equations with CUDA

The Fermi Architecture

Chap 13

   

6

25-29 Jun

NVIDIA OptiX: Ray Tracing on the GPU

Future of Throughput

Chap 17

 

Lab 3

(due on 9 Jul)

7

2-6 Jul

Path Planning System on the GPU

Optimizing Parallel GPU Performance

Parallel Sorting

Chap 11-12

Project proposal due

 

8

9-13 Jul

Project work    

Lab 4

(due on 23 Jul)

9

16-20 Jul

Project work

 

 

 

10

23-27 Jul

Project work

 

 

 

11

30 Jul - 3 Aug

Project work

 

 

 

12

6-10 Aug

Project work

     

13

13-17 Aug Project work

 

 

 

14

20-24 Aug

Presentations on 20 Aug at 11h00

  Paper critique and project report due on 20 Aug  

15

27-31 Aug Debrief