You’ll learn the fundamental tools and techniques for running GPU-accelerated Python applications in this workshop using CUDA and the NUMBA compiler GPUs. You’ll use a live, cloud-based GPU-enabled development environment to work though dozens of hands-on coding exercises.

Learn how to:

  • Write code for a GPU accelerator
  • Configure code parallelization using the CUDA thread hierarchy
  • Manage and optimize memory migration between the CPU and GPU accelerator
  • Generate random numbers on the GPU
  • Intermediate GPU memory management techniques

Finish by implementing your new workflow to accelerate a fully functional linear algebra program originally designed for CPUs to observe impressive performance gains.

After the workshop ends, you’ll have additional resources enabling you to create new GPU-accelerated applications on your own.

Read more


  • 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
Read more

Learning Outcomes

Gain understanding on how to use fundamental tools and techniques for GPU-accelerate Python applications with CUDA and Numba, including:

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

Why Deep Learning Institute Hands-on Training?

  • Learn how build deep learning and accelerated computing applications across a wide range of industry segments such as autonomous vehicles, digital content creation, finance, game development, healthcare, and more.
  • Learn in aguided, hands-on experience using the most widely-used, industry-standard software, tools, and frameworks.
  • Gain real world expertise through content designed in collaboration with industry leaders such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.
  • Earn NVIDIA DLI certification to prove your subject matter competency and support professional career growth.
  • Access content anywhere, anytime with a fully configured GPU-accelerated workstation in the cloud.


Upon successful completion of the workshop, participants will receive NVIDIA DLI Certification to recognize subject matter competency and support professional career growth.

Read more

Course Outline


  • Getting started

The first 15 minutes introduces how to set-up your training environment.

Introduction to CUDA Python with Numba

  • Optimize CPU code with the Numba compiler
  • GPU-accelerate NumPy ufuncs
  • Optimize host-to-device and device-to-host memory transfers

Begin to working with the Numba compiler and CUDA programming in Python. Learn to use Numba decorators to accelerate numerical Python functions. Complete an assessment to accelerate a neural network layer.

Custom CUDA Kernels in Python with Numba

  • Learn CUDA’s parallel thread hierarchy
  • Launch massively parallel custom CUDA kernels on the GPU
  • Utilize atomic operations to avoid race conditions during parallel execution.

Learn how to extend parallel program possibilities,. including the ability to design and write flexible and powerful CUDA kernels. You’ll grasp ho to easily handle race conditions with CUDA atomic operations and parallel thread synchronization. You’ll also complete an assessment to accelerate a Mandelbrot set calculator and visualizer.

RNG, Multidimensional Grids, and Shared Memory for CUDA Python with Numba

  • Use xoroshiro128+ RNG to support GPU-accelerated monte carlo methods
  • Learn multidimensional grid creation and how to work in parallel on 2D matrices
  • Leverage on-device shared memory to communicate between threads

Generate a random number state for thousands of parallel threads in this intermediate-level module. Use shared memory for on-device caching and promoting memory coalescing while reshaping 2D matrices.


  • Accelerate a CPU-only linear algebra subprogram

This module teaches you to leverage your learning to accelerate a CPU-only linear algebra subroutine for massive performance gains.

Next Steps

  • Complete workshop survey
  • Set up your own GPU enabled environment

Finally, learn how to set up your CUDA and GPU-enabled environment to begin work on your own projects.

  • Tools, Libraries, and Frameworks: Numba, NumPy
Read more

Why choose QA

Frequently asked questions

See all of our FAQs

How can I create an account on myQA.com?

There are a number of ways to create an account. If you are a self-funder, simply select the "Create account" option on the login page.

If you have been booked onto a course by your company, you will receive a confirmation email. From this email, select "Sign into myQA" and you will be taken to the "Create account" page. Complete all of the details and select "Create account".

If you have the booking number you can also go here and select the "I have a booking number" option. Enter the booking reference and your surname. If the details match, you will be taken to the "Create account" page from where you can enter your details and confirm your account.

Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.

How do QA’s virtual classroom courses work?

Our virtual classroom courses allow you to access award-winning classroom training, without leaving your home or office. Our learning professionals are specially trained on how to interact with remote attendees and our remote labs ensure all participants can take part in hands-on exercises wherever they are.

We use the WebEx video conferencing platform by Cisco. Before you book, check that you meet the WebEx system requirements and run a test meeting (more details in the link below) to ensure the software is compatible with your firewall settings. If it doesn’t work, try adjusting your settings or contact your IT department about permitting the website.

Learn more about our Virtual Classrooms.

How do QA’s online courses work?

QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.

Learn more about QA’s online courses.

When will I receive my joining instructions?

Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.

When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

Contact Us

Please contact us for more information