1

GPGPU using

CUDA ThrustTechnical Talk –15/09/2015

2

General Purpose computing on Graphics Processing Units◦ 2000

Programmable shaders -> Matrices/Vectors computation

◦ 2006 NVIDIA CUDA

Solutions◦ NVIDIA CUDA◦ OpenCL◦ OpenACC

GPGPU

3

4

Multi-core processor

5

CUDA - Grid

6

Adding two vectors

7

Memory access influences the performance

8

Memory access influences the performance

9

Why CUDA then?

10

High-level interface◦ C++ Standard Template Library (STL)◦ Interoperability

CUDA OpenMP

CUDA Thrust

11

Sorting◦ Stable/Unstable◦ By key

Set Operations◦ Difference◦ Intersection◦ Union

Reductions◦ Counting◦ Extremes◦ User-defined

Searching Random Number Generation

Algorithms available in Thrust

http://docs.thrust.googlecode.com/hg/modules.html

12

https://github.com/thrust/thrust/blob/master/examples/weld_vertices.cu

Thou shalt use STL and Templates!!

13

14

Bounding box computation Approximate Voronoi Diagram Dot Product Histograms Monte carlo methods

Some Useful Examples

https://github.com/thrust/thrust/tree/master/examples

15

GPGPU using

CUDA ThrustTechnical Talk –15/09/2015