Title – High Performance Networks in the World of AI  

Avi Telyas – Director, System Engineering (APAC) – Mellanox

 
Abstract: This talk is aimed towards professionals interested in discussing the role of current and up-coming Interconnect in the field of Artificial Intelligence. We will start with analysing the latest “in-network computing” architecture of Infiniband and then move on to discuss how these advancements are being applied to address the demands of emerging markets of AI/Machine learning.

Bio: Avi Telyas is a Director of System Engineering in Mellanox Technologies, leading APAC Sales Engineering and FAE teams. Based in Tokyo, Avi is deeply involved in large HPC, Machine learning and AI deployments in Japan and APAC. In his free time Avi is coding over AI frameworks and gets too excited talking about it. Avi holds a BSc (Summa cum laude) in

Computer Science from the Technion Institute of Technology, Israel.

Title – Scalable and Distributed DNN Training on Modern HPC Systems
 

Dr D K Panda – Professor, Computer Sc. & Eng., The Ohio State University, USA

Abstract: This talk will start with an overview of challenges being faced by the AI community to achieve scalable and distributed DNN training on Modern HPC systems. After that, the talk will focus on a range of solutions to address these challenges. The solutions will include: 1) MPI-driven Deep Learning, 2) Co-designing Deep Learning Stacks with High-Performance MPI, 3) Out-of-core DNN training, 4) Accelerating TensorFlow on HPC Systems, 5) Accelerating Big Data Stacks, and 6) Efficient Deep Learning over Big Data.

Bio: DK Panda is a Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University. He has published over 450 papers in the area of high-end computing and networking. The MVAPICH2 (High Performance MPI and PGAS over InfiniBand, Omni-Path, iWARP and RoCE) libraries, designed and developed by his research group (http://mvapich.cse.ohio-state.edu), are currently being used by more than 2,950 organizations worldwide (in 86 countries). More than 511,000 downloads of this software have taken place from the project’s site. This software is empowering several InfiniBand clusters (including the 3 rd , 14 th , 17 th , and 27 th ranked ones) in the TOP500 list. The RDMA packages for Apache Spark, Apache Hadoop and Memcached together with OSU HiBD benchmarks from his group (http://hibd.cse.ohio-state.edu) are also publicly available. These libraries are currently being used by more than 295 organizations in 34 countries. More than 28,500 downloads of these libraries have taken place. High-performance and scalable versions of the Caffe and TensorFlow frameworks are available from https://hidl.cse.ohio-state.edu. Prof. Panda is an IEEE Fellow. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Title –  Engineering IT infrastructure at MBRDI

Vinil Vadakkepurakkal – Solutions Architect  HPC & Deep Learning  Mercedes Benz R&D

Bio: Vinil is an experienced Solutions Architect in High Performance Computing and Deep Learning. He works on numerous demanding engineering domains including, Autonomous driving, HPC simulations, Visualization etc. with Mercedes Benz R&D by providing the most optimal engineering infrastructure solutions.
Vinil holds a Bachelor’s Degree in Computer Applications along with various other prestigious certifications. Machine learning certification from Stanford University, Deep learning for Computer Vision from NVIDIA Deep learning institute, Neural Networks and Deep learning from deeplearning.ai, Red Hat Certified Architect in Infrastructure Level IV etc. are some of his certifications.

Title – Towards Better and Efficient Model Training and Inferencing Using Mixed Precision

Mukund – Sr. Solution Architect in NV-India