Fundamentals of Accelerated Computing with CUDA Python (FACCP)

 

Course Overview

This course explores how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs. You’ll learn how to: · Use Numba to compile CUDA kernels from NumPy universal functions (ufuncs). Use Numba to create and launch custom CUDA kernels · Apply key GPU memory management techniques Upon completion, you’ll be able to use Numba to compile and launch CUDA kernels to accelerate your Python applications on NVIDIA GPUs.

Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be cancelled and no refund will be issued, regardless of attendance.

Prerequisites

  • Basic Python competency, including familiarity with variable types, loops, conditional statements, functions, and array manipulations
  • NumPy competency, including the use of ndarrays and ufuncs
  • No previous knowledge of CUDA programming is required

Course Objectives

At the conclusion of the workshop, you’ll have an understanding of the fundamental tools and techniques for GPU-accelerated Python applications with CUDA and Numba:

  • GPU-accelerate NumPy ufuncs with a few lines of code.
  • Configure code parallelization using the CUDA thread hierarchy.
  • Write custom CUDA device kernels for maximum performance and flexibility.
  • Use memory coalescing and on-device shared memory to increase CUDA kernel bandwidth.

Prices & Delivery methods

Online Training

Duration
1 day

Price
  • on request
Classroom Training

Duration
1 day

Price
  • on request
 

Schedule

English

8 hours difference

Online Training Time zone: Eastern Daylight Time (EDT)
Online Training Time zone: Eastern Daylight Time (EDT)

9 hours difference

Online Training Time zone: Eastern Standard Time (EST)
Online Training Time zone: Eastern Standard Time (EST)

10 hours difference

Online Training Time zone: Central Standard Time (CST)
Online Training Time zone: Central Standard Time (CST)
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.