Every year NVIDIA’s GPU Technology Conference (GTC) gets bigger and better. One of the aims of GTC is to give developers, scientists, and practitioners opportunities to learn with hands-on labs how to use accelerated computing in their work. This year we are nearly doubling the amount of hands-on training provided from last year, with almost 2,400 lab hours available to GTC attendees!
We have two types of training this year at GTC: instructor-led labs and self-paced labs. And to help you keep up with one of the hottest trends in computing, this year we’re featuring a Deep Learning training track. Keep reading for details. If you haven’t registered for GTC yet this year, keep reading for a discount code.
Deep Learning Track
There is an explosion of Deep Learning topics at GTC, and it’s not limited to the keynotes, talks and tutorial sessions. We’ll feature at least six hands-on labs related to accelerating facets of Deep Learning on GPUs. From an introduction to Deep Learning on GPUs to cutting-edge techniques and tools, there will be something for everyone. Be sure to get to these labs early to get yourself a seat! Here are a few of the labs available in this track:
- Introduction to Machine Learning with GPUs: Handwritten digit classification (S5674)
- DIY Deep Learning for Vision with Caffe (S5647)
- Applied Deep Learning for Vision, Natural Language and Audio with Torch7 (S5574)
- Deep Learning with the Theano Python Library (S5732)
- Deep Belief Networks Using ArrayFire (S5722)
- Accelerate a Machine Learning C++ example with Thrust (S5822)
Just like GTC last year, there will be twenty hands-on instructor-led labs. These are 80-minute labs led by an expert on the topic. These labs are Bring-Your-Own-Computer (BYOC), but don’t worry if your system doesn’t have an NVIDIA GPU in it. The majority of the labs will run on GPUs hosted in the cloud or in systems you can easily connect to. In fact, for most of the labs you only need a web browser to access the interactive content! Some new labs scheduled for this year are:
- CUDA4J – learn how to access the power of a GPU from Java (S5823)
- Mobile device labs – get experience with GPU computing on a mobile device. Very interesting for Computer Vision applications
- In situ data analysis and visualization – get started working with ParaView, Calalyst and VTK-m (S5710)
- Developing, Debugging and Optimizing GPU Codes for High Performance Computing with Allinea (S5814)
You can see a full list of the hands-on labs available by checking out the GTC schedule planner.
New Self-Paced Lab Space
If you visited the NVIDIA Booth at the Supercomputing conferences in the last two years, you certainly have seen the NVIDIA Devzone Live space; home to our 45-minute self-paced labs. These short hands-on labs have been incredibly popular, so we’ve added them to GTC 2015. Located on the main concourse, there will be 20 laptops set up in a special lab area, ready for attendees to learn GPU computing topics in under an hour. Labs range in complexity from introductory to advanced and cover a wide array of topics. Here’s a sampling:
- What’s new in CUDA 7;
- CUDA C++, CUDA Fortran, and CUDA Python;
- OpenACC in C and Fortran;
- Accelerated computing with MATLAB;
- Optimizations in CUDA and OpenACC;
- Multi-GPU programming;
- and more.
You should register for a time slot ahead of time to make sure you get a chance to try one of the labs. To reserve a seat, use one of these EventBrite links:
- Tuesday Labs: tuesdaylabs-gtc15.eventbrite.com
- Wednesday Labs: wednesdaylabs-gtc15.eventbrite.com
- Thursday Labs: thursdaylabs-gtc15.eventbrite.com
- Friday Labs: fridaylabs-gtc15.eventbrite.com
If you don’t register, seats are assigned on a first-come, first-served basis and will be opened up a few minutes after the start of a lab session.
Free Online Lab Access Codes After the Show
In addition to all the training opportunities available at GTC, everyone who attends a hands-on lab will receive free lab access codes for use after the show at nvidia.qwiklab.com. This site has in-depth versions of all our self-paced hands-on labs – only a web browser and internet required!
Make sure to join us for some great hands-on training at GTC 2015! Readers of Parallel Forall can use the discount code GM15PFAB to get 20% off any conference pass! Register Now!