|Date: 9th September 2020||TechExeter|
|Track: 2||Type of session: Talk|
|Start Time: 13:45||Level: No prior knowledge / entry-level|
Note: Speaker information is preliminary and subject to change
Writing code for GPUs has come a long way over the last few years and it is now easier than ever to get started. You can even do it in Python! This talk will cover setting up your Python environment for GPU development. How coding for GPUs differs from CPUs, and the kind of problems GPUs excel at solving. We will dive into some real examples using Numba and also touch on a suite of Python Data Science tools called RAPIDS.
- you don't need to learn C++ to develop on GPUs
- GPUs are useful for more than just machine learning
- hardware accelerators like GPUs are going to be more important than ever in order to scale our current workloads
Jacob works on Cloud, infrastructure and deployments for Dask and RAPIDS at NVIDIA. He is also one of the leaders at TechExeter.