Accelerating AI with GPUs - ITaP Research Computing Guest Speaker
October 18, 2018 1:30pm – 2:30pm
ITaP Research Computing is proud to present Purdue alum and Nvidia Advocate for Deep Learning and HPC Dr. Jeff Layton as a special guest speaker this Thursday, October 18, 2018 at 1:30PM in LWSN 1142.
The title of Dr. Layton’s talk is: Accelerating AI with GPUs
Data scientists in both industry and academia have been using GPUs for AI and machine learning to make groundbreaking improvements across a variety of applications including image classification, video analytics, speech recognition and natural language processing. In particular, deep learning – the use of sophisticated, multi-level “deep” neural networks to create systems that can perform feature detection from massive amounts of unlabeled training data – is an area that has been seeing significant investment and research.
Although AI has been around for decades, two relatively recent trends have sparked widespread use of Deep Learning within AI: the availability of massive amounts of training data, and powerful and efficient parallel computing provided by GPU computing. Early adopters of GPU accelerators for machine learning include many of the largest web and social media companies, along with top tier research institutions in data science and machine learning. With thousands of computational cores and 10-100x application throughput compared to CPUs alone, GPUs have become the processor of choice for processing big data for data scientists.
Those interested in attending are asked to RSVP via:
About Dr. Layton:
Dr. Jeff Layton received his PhD from Purdue University in 1992 in Aeronautical and Astronautical Engineering. He was a professor in the Mechanical and Aeronautical Department at Clarkson University and has worked at Boeing, Lockheed Martin, and NASA Langley on various projects with most of the work focusing on CFD, Flight Dynamics, Design, and Flight Manuals. At Lockheed he brought HPC clusters into the company and acted as the admin for several years. He then moved into the HPC field working in turn for Linux Networx, Panasas, Dell, Intel, Amazon Web Services (AWS), and now at NVIDIA.
Jeff is currently an HPC Advocate at NVIDIA. There, his focus has been helping customers get started with Deep Learning, Python, and scientific codes on GPUs. In his 30+ years of experience he has been a professor, engineer, cluster builder, cluster user and cluster admin, code writer, system architect/engineer, manager, and benchmark/IO engineer. He also writes articles about HPC, storage, and Linux for Linux Magazine, Enterprise Storage Forum, HPC Admin Magazine, and Admin Magazine.