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Tuesday, September 15
 

10:00am CDT

Weather Forecasting: An Application of Artificial Intelligence, Cloud, IOT & High-Performance Computing - Dr Manish Modani, IBM India Pvt Ltd
The Weather Company, an IBM Business, offers the personalized & actionable weather data and insights to millions of users. Weather Company uses 100+ state of art weather models to provide hyper-local weather forecast across the world. The Artificial Intelligence techniques and Human Intelligence (150 + Meteorologists) used to have the most accurate weather forecast for better decisions. Recently IBM operationalized the unique weather model IBM GRAF, developed & deployed jointly by NCAR & IBM, running on IBM Power 9 and NVIDIA GPUs. IBM GRAF runs at 3 KM resolution, across the world with the hourly update. This talk will explore the weather forecast models, translation of those forecasts into insights and impacts for decision-makers, using high-performance computing, artificial intelligence and the internet of things. The performance of IBM Weather models in predicting the cyclone NISARGA & AMPHAN will also be discussed.

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Speakers
DM

Dr Manish Modani

Senior Meteorologists, IBM India Pvt Ltd
Dr Manish Modani is PhD from Centre of Atmospheric Sciences, Indian Institute of Technology (IIT) Delhi, India. Manish is working in IBM since 2010, where he has worked on various HPC Application Development, Optimization & Benchmarking on Power & X86 based architectures. Presently... Read More →


Tuesday September 15, 2020 10:00am - 10:30am CDT
Track 4

11:45am CDT

Competitive Analysis of the Top Gradient Boosting Machine Learning Algorithms - Sai Ayachit, Shyam R, Anubhav Singh & Vinayak Patil, The National Institute of Engineering
Given the rapid increase in computing power and data-driven approaches to tackle many real-world problems today, ML has become an integral part of many solutions.As per a Kaggle survey in 2019, boosting algorithms are among the top 3 preferred methods used by data scientists. Their popularity is due to their robustness against overfitting, faster training times, ability to handle multimodal data while leaving a small memory footprint. In this paper, we compare four state-of-the-art gradient boosting algorithms XGBoost, CatBoost, LightGBM, and SnapBoost on 4 diverse datasets. We perform this competitive analysis on the IBM PowerAI AC922 server. This platform helps end-users experience faster iterations and training than the standard x86. Finally, we present the accuracy and training times of all the algorithms across the 4 datasets. We perform analysis using two approaches; One with only the baseline algorithms, and the other with systematic Hyperparameter Optimization with HyperOpt.

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Speakers
SA

Sai Ayachit

Student, The National Institute of Engineering
Sai is a final year undergraduate student at The National Institute of Engineering. Her recent work experience was with IBM under the Global Remote Mentorship(GRM) Program. She made significant contribution to the proposal "GENDER IDENTIFICATION OF SILKWORM PUPAE USING TRANSFER LEARNING... Read More →
SR

Shyam R

Student, The National Institute of Engineering
Shyam is a final year computer science undergraduate at The National Institute of Engineering. He loves to solve challenging problems and explore various Tech-stacks. He is passionate about  Predictive Modelling, Deep Neural Networks, Adversarial models, and Inferential statistics... Read More →
AS

Anubhav Singh

Student, The National Institute of Engineering
Anubhav is a CS undergraduate from The National Institute of Engineering. His interests lie in the emerging technologies like AI and blockchain and competitive coding. He strives to find an optimized solution for real world use cases. His competitive spirit has helped him excel in... Read More →
VP

Vinayak Patil

Student, The National Institute of Engineering
Vinayak is majoring in Computer Science and Engineering at NIE, Mysuru. He likes to code and learn new technologies. He has expertise in various programming languages, Data Structures, and Algorithms. His work experience spans across various domains like Machine Learning, Deep Learning... Read More →



Tuesday September 15, 2020 11:45am - 12:15pm CDT
Track 4
  AI  Software
  • See Session Slides yes

12:45pm CDT

Distributed AI for Automated and Scalable Quality Inspection using EDGE Computing on OpenPower - Igor Khapov, IBM
AI-assisted quality inspection is a critical feature for all manufacturing companies. Igor led IBM Development team to create production solution using Edge computing approach. Igor will present how to use Kuberntes and edge computing technologies in data science and video inspection. From this presentation you will understand how to combine ppc64le, arm and x86 architectures to get the cost-effective solutions. The team developed an AI-assisted automated quality inspection solution cross multiple plants for manufacturing. The solution is based on the latest technologies, for example, IBM PowerAI Vision for model training, edge computing for model deployment and management, and Nvidia Jetson TX2 devices for inferencing. The solution includes a centralized web dashboard for Model Developers and Quality Engineers. This solution now at the production stage across the globe.

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Speakers
avatar for Igor Khapov

Igor Khapov

Chief Technology Officer for Russia/CIS, IBM
Chief Technology Officer for Russia/CIS, team manager, architect and development lead with more than 15 years of development experience. Containers and K8s/OpenShift expert. Speaker at multiple international conferences (KubeCon, Think, blockchain and development conferences). Multiple... Read More →


Tuesday September 15, 2020 12:45pm - 1:15pm CDT
Track 4

1:20pm CDT

Hit-reco: ProtoDUNE Raw Data Denoising with DL models - Marco Rossi, CERN
We present Hit-reco model for denoising and region of interest selection on raw simulation data from ProtoDUNE experiment. ProtoDUNE detector is hosted by CERN and it aims to test and calibrate technologies for DUNE, a forthcoming experiment in neutrino physics. Hit-reco leverages deep learning algorithms to make a first step in the reconstruction workchain, that consists in converting digital detector signals into physical high level quantities. We benchmark the artificial intelligence based approach against traditional algorithms implemented by the DUNE collaboration. We investigate the capability of graph convolutional neural networks, while exploiting the IBM Minsky multi-GPU setup to accelerate training and inference processes.

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Speakers
MR

Marco Rossi

Doctoral Student at CERN, CERN
I am pursuing the PhD in Physics at the University of Milan. The main research topics are application of artificial intelligence and deep learning to high energy physics. In this context, I am working as a doctoral student at CERN funded by IBM corporation on the development of machine... Read More →



Tuesday September 15, 2020 1:20pm - 1:50pm CDT
Track 4
  Use Case  AI
  • See Session Slides yes

1:55pm CDT

HAL: Computer System for Scalable Deep Learning - Volodymyr Kindratenko, University of Illinois at Urbana-Champaign
This presentation will describe the design, deployment and operation of a computer system built to efficiently run deep learning frameworks. The system consists of 16 IBM POWER9 servers with 4 NVIDIA V100 GPUs each, interconnected with Mellanox EDR InfiniBand fabric, and a DDN all-flash storage array. This system is tailored towards efficient execution of the IBM Watson Machine Learning enterprise software stack that combines popular open-source deep learning frameworks. We build a custom management software stack to enable an efficient use of the system by a diverse community of users and provide guides and recipes for running deep learning workloads at scale utilizing all available GPUs. We demonstrate scaling of a PyTorch and TensorFlow based deep neural networks to produce state-of-the-art performance results.

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Speakers
VK

Volodymyr Kindratenko

Senior Research Scientist, University of Illinois at Urbana-Champaign
Dr. Volodymyr Kindratenko is a Senior research Scientist at the National Center for Supercomputing Applications, an Adjunct Associate Professor in the Department of Electrical and Computer Engineering and a Research Associate Professor in the Department of Computer Science at the... Read More →


Tuesday September 15, 2020 1:55pm - 2:25pm CDT
Track 4

2:55pm CDT

IBM open sources PowerAI as Open Cognitive Environment! - Jason Furmanek, IBM & Chris Sullivan, Oregon State University
This talk is an introduction to a new open source project called Open Cognitive Environment (Open-CE).
Open-CE is a mid-stream integration community project that aims to foster collaboration between communities, vendors, user/enterprises, and academic institutions. Open-CE is designed to minimize the time to value and increase the consumability and inclusivity of important foundational AI and deep learning frameworks, libraries and tools, including TensorFlow and PyTorch, by providing a pre-integrated, multi-architectural set of recipes, build scripts, predefined Continuous Integration pipeline code and cutting edge models for building a complete environment of packages for AI development and/or production capacities.

Open-CE is based on the code from IBM's PowerAI project, which was launched to market as IBM Watson Machine Learning Community Edition. Therefore, Open-CE supports OpenPOWER (ppc64le) out of the box with options for GPU acceleration enablement throughout.
 
OpenCE provides even greater flexibility to users by embracing open source and removing barriers for users to build integrated packages and environments from source targeting platforms, environments and applications that users care about most. Build what you want, how you want it. We also hope to gain more members, users, builders and hosters for the project.

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Speakers
avatar for Chris Sullivan

Chris Sullivan

Assistant Director for Biocomputing, Oregon State University
Christopher Sullivan has been working in the field of computational science for 19 years and currently has over 30 co-authored scientific publications. His work has focused on Biocomputing and life sciences that change the way we look at and interact with the environment. Over the... Read More →



Tuesday September 15, 2020 2:55pm - 3:25pm CDT
Track 4
  AI
  • See Session Slides yes

3:30pm CDT

High-Performance MPI and Deep Learning with Introspection on OpenPOWER Platform - Dhabaleswar K (DK) Panda, X-ScaleSolutions and The Ohio State University & Donglai Dai, X-ScaleSolutions
This talk will focus on high-performance and scalable middleware for Message Passing Interface (MPI) and Deep Learning on OpenPOWER platform with NVIDIA GPGPUs and RDMA-enabled interconnects (InfiniBand and RoCE). The focus will be on two packages with commercial support being available from X-ScaleSolutions. The first package will focus on the OSU MVAPICH2 MPI libraries and their capabilities for high-performance computing with both CPUs (OpenPOWER) and GPUs (NVIDIA). The second package will focus on tight integration between the OSU MVAPICH2-GDR MPI library and the Horovod stack to provide high-performance and scalable Deep Learning (DL) with deep introspection (DI) capabilities for DL frameworks like TensorFlow, PyTorch and MXNet. The DI capabilities allow DL users and runtime developers to easily optimize their DL applications on modern systems. Performance results from the ORNL SUMMIT system (#2nd) and Lassen (#14th) with thousands of GPUs and POWER9 CPUs will be presented.

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Speakers
DK

Dhabaleswar K (DK) Panda

Professor and University Distinguished Scholar; Founder and CEO (X-ScaleSolutions), X-ScaleSolutions and The Ohio State University
DD

Donglai Dai

Chief Engineer, X-ScaleSolutions
Dr. Donglai Dai is a Chief Engineer at X-ScaleSolutions and leads company’s R&D team. His current work focuses on developing scalable efficient communication libraries and performance analysis tools for distributed and parallel HPC and deep learning applications on HPC systems... Read More →



Tuesday September 15, 2020 3:30pm - 4:00pm CDT
Track 4
  AI  Software
  • See Session Slides yes

4:05pm CDT

AI at Scale in the Enterprise - Clarisse Taaffe Hedglin, IBM
As the adoption of AI technologies increases and matures, the focus will shift from exploration to time to market and productivity. Governing Enterprise data, scaling AI model development, providing a complete, collaborative platform and tools for rapid solution deployments are key focus areas for growing data scientist teams tasked to respond to business challenges. The drive for performance, productivity acceleration, smarter infrastructure resource utilization and management efficiencies can be seen in Enterprises across all industries and modernization initiatives. This talk will cover the challenges and innovations for AI at scale for the Enterprise focusing on the modernization of data analytics, the AI ladder and AI lifecycle, infrastructure considerations and conclude with Data and AI architecture use case scenarios.

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Speakers
avatar for Clarisse Hedglin

Clarisse Hedglin

Executive IT Architect, IBM
Clarisse Taaffe Hedglin is an Executive IT Architect in the IBM Gatage for for Systems with expertise on application performance and benchmarking. As a senior member of the Artificial Intelligence Center of Competency, she works with clients across many industries to shape their computing... Read More →



Tuesday September 15, 2020 4:05pm - 4:35pm CDT
Track 4
  Use Case  AI
  • See Session Slides yes

4:05pm CDT

Insights into New Manufacturing System Arena through IBM Open POWER System - Archisman Sen, Mitsubishi Fuso Truck and Bus Corporation, Japan
SUMMARY : In this presentation, we would talk about the potential that is available in the IBM Open POWER Systems and how it could be utilized to make a complete system for manufacturing setups. The idea is mostly to focus on the available resources that are available and harnessing the capabilities of each system from each domain to provide a customized solution for the specific requirement of the client. Focus Points: The key highlights of this presentation are as follows: 1. To explore why is digital manufacturing approach is here. 2. The probable and effective strategies bringing the change. 3. Why IBM Open POWER Systems can be the next big thing in the field of digital manufacturing processes? 5. We can take a look at the implementation plan in various stages. 6. Having a vision for the next line of actions for achieving this plan/project. Use Case Scenario: Let us take up a case where we would like to track the product quality through the entire Value Chain.

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Speakers
AS

Archisman Sen

Intern, Mitsubishi Fuso Truck and Bus Corporation, Japan
Graduated as a Mechanical Engg. and worked for 4 years with Renault Nissan in India and Japan, with roles of Sr. Engg for R&D in HVAC and Quality project, apart from having roles as manufacturing quality reviewer and Chassis component quality leader. This involved extensive interaction... Read More →



Tuesday September 15, 2020 4:05pm - 4:35pm CDT
Track 2B
  Use Case  AI
  • See Session Slides yes

4:05pm CDT

New Time!! COVID Detection - Deep Learning Solution on power 9 AI Box - Shivansh Shukla, IIT Patna
In addition to the immeasurable suffering and loss of life, the deadly coronavirus is already impacting the world economy, but there is a silver lining. COVID has sparked a wave of innovation. We, here at Object Automation Software Solutions Pvt Ltd tried to contribute by developing a Covid-19 detection/classification program from the x-ray scans, leveraging the state of the art VGG-16 convolutional model. We then built and tested this on our low-cost Power 9 Development Box for AI, Deep Learning & Machine Learning. This box provides the fastest, simplest way to deploy deep learning frameworks This Covid-19 detection/classification application can also be very easily developed on the PowerAI Vision tool, which automates the machine learning and deep learning workflow without any skills in deep learning technologies. It can then train and validate a model in a GUI interface to build customized solutions for image classification and object detection.

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Speakers
SS

Shivansh Shukla

Research Intern - Object Automation Software Solution Pvt. Ltd., IIT Patna
This is Shivansh Shukla pursuing B.Tech (UG) from the Indian Institute of Technology, Patna. I have worked on domains like cloud computing, deep learning, and software development. Some projects include the "Facial recognition attendance system" through siamese networks locally as... Read More →



Tuesday September 15, 2020 4:05pm - 4:35pm CDT
Track 3
  Use Case  AI
  • See Session Slides yes
 
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