Registration:: https://www.eventbrite.ca/e/1112673288759

Learn to accelerate your Python functions on CPU and GPU using Numba.

Python isn't optimized for high-performance computing and can't be used “as is” on graphics processing units (GPUs). You can overcome these shortcomings by using one the Python just-in-time compilers such as Numba, which combines the ease of Python development with the power of a compiled language that targets both CPUs and GPUs.

In this workshop, you will gain insights into using Numba to accelerate your code on GPUs, to create simple GPU programs and to understand the core principles of GPU programming.

Plan:

• Why use GPUs for computing?
• Understanding difference between CPU and GPU
• Numba: just-in-time compiling
• Parallel computing: distributing workload among CPU and GPU cores
• Very short intro to CUDA
• Numba + CUDA: porting a CPU code to GPU
• Numba + CUDA: more acceleration with shared memory, streams
• Practical Sessions: lots of examples and exercises