Exploit Your GPU Power with PyCUDA - and Friends

Explore GPU computing with PyCUDA in this EuroPython 2011 conference talk. Dive into the differences between CPU and GPU processing, compare CUDA and OpenCL, and understand the CUDA programming model. Learn about memory spaces, vector summation using CUDA, and practical applications in medical imaging. Discover when to use PyCUDA, its advantages over CUDA, and potential drawbacks. Gain insights into high-level functions, Nvidia libraries, and modern GPU capabilities. Address common questions about GPU programming complexity and explore the potential of exploiting GPU power in Python applications.

Introduction
Topics
GPU
CPU vs GPU
GPU computing
CUDA vs OpenCL
CUDA Programming Model
Memory Spaces
khuda
sum of vectors
Imports
Code
Medical intensity
Practical intensity
Cooperation
When to use PyCUDA
PyCUDA vs CUDA
Cons
Summary
Metrics
Highlevel functions
Questions
Is everything more complicated
Nvidia libraries
Modern GPUs