We’ve just run another successful 3-day NVIDIA CUDA Workshop via the Deep Learning Network. Dr Anthony Morse (Plymouth University) went all the way from an introduction to CUDA through to CUDA libraries and multi-GPU computing. Thanks again to NVIDIA for sponsoring the event!
We’re just coming to the end of the 2-day NVIDIA CUDA Workshop, organised via the Deep Learning Network. Our instructor, Dr Anthony Morse (Plymouth University), covered a breadth of topics ranging from an introduction to CUDA, through optimisation to multi-GPU computing. He was able to draw from years of practical usage to cover some of the intricacies of CUDA that isn’t readily available through documentation and online courses.
After many hours of building Kai and Jose have finished constructing three new servers. The identical builds make it easier to transfer software between the machines, and also to investigate distributed computation for computer vision and machine learning. As scaling up becomes infeasible, the alternative is scaling out.
Each machine has a 8-core CPU, 64GB of RAM and 4 NVIDIA GPUs for General-Purpose computing on Graphics Processing Units (GPGPU). With such hardware we can make use of both parallelisation and virtualisation, the former enabling the training of large machine learning models and the latter allowing multiple users to trial different application environments on the same physical machine. The servers will see their first major test in the near future with the upcoming NVIDIA CUDA Workshops.