[opensource] Big Data Analytics and Associated Deep Learning

Moore, Jack moore.3337 at buckeyemail.osu.edu
Tue Nov 27 19:51:33 EST 2018

Hello Everyone,

This week at Open Source Club we will be having DK Panda in to present on Big Data Analytics and Deep Learning!

Significant growth has been witnessed during the last decade in High-Performance Computing (HPC) clusters with multi-/many-core processors, accelerators, and high-performance interconnects (such as InfiniBand, Omni-Path, iWARP, and RoCE). Many supercomputers in the world are currently being designed with commodity HPC clusters. The Network-Based Computing Laboratory (http://nowlab.cse.ohio-state.edu) at OSU/CSE in actively engaged in designing software libraries (HPC, Big Data, Deep Learning, and Cloud) for such supercomputers. An overview of these activities will be covered in four presentations. These presentations will also provide an outline of the associated research, publications, designs, testing and support framework for these libraries. Opportunities for students to get involved in the R&D activities in these projects will be outlined.

During the second talk of this academic year, we will focus on the High-Performance Big Data (HiBD) project (http://hibd.cse.ohio-state.edu). As a part of this project, high-performance designs of many Big Data Analytics software stacks such as Spark, Hadoop, HBase, Memcached, and Kafka has been designed. We will discuss about these software stacks and their architectures and features. Next, we will present the challenges in accelerating this software stacks for modern supercomputers with multi-core processors, GPUs, and high-performance interconnects. We will also discuss about the new emerging trend of Deep Learning over Big Data (DLoBD) and how to accelerate these stacks on modern supercomputers.

The talk will follow with an open Q&A session with several members of the Network-Based Computing Laboratory. The session will conclude with a tour of the Laboratory consisting of multiple high-end clusters involving thousands of cores.

We look forward to seeing everyone this week in Caldwell 120 at 7:30 on Thursday!

More information about the Opensource mailing list