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Second Edition Of NVIDIA & AIMinds Meetup In Bengaluru A Great Success

Second Edition Of NVIDIA & AIMinds Meetup In Bengaluru A Great Success

nvidia gpu rapids

As technology is evolving, it can clearly be seen that GPU is now one of the most important components of artificial intelligence and deep learning architecture. Both enterprises, as well as developers, are always searching for new and improved tools that will help them build and manage end-to-end solutions in data science and analytics. The NVIDIA accelerated stack which includes GPUs, DGX, CUDA architecture and also NGC software not only helps in reducing time to scientific discovery, but also helps in enabling a variety of compute-intensive industrial applications of GPUs beyond computer graphics.

This was one of the key points of discussion at the NVIDIA RAPIDS GPU-Accelerated Data Analytics and Machine Learning Workshop, successfully hosted by Analytics India Magazine and tech giant NVIDIA.

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The workshop was kick-started by Pawan Awasthi, Head of Enterprise Marketing, Asia South at NVIDIA. Awasthi, a gifted speaker, set the expectations of the crowd on a high level as he welcomed the participants and talked about the future of advancing science by accelerating their high-performance computing (HPC) applications on NVIDIA GPUs using specialized libraries, directives, and language-based programming models. He also hailed the increasing usage of GPU in data science-related industries to boost performances. Awasthi also touched upon engaging topics such as the future of GPU-based computing in context to the Indian industries and emerging tech sector. And at the end of his welcome address, he introduced the rest of the speakers.

nvidia gpu rapids

Keynote speaker Sundara Ramalingam Nagalingam, the Head of Deep Learning Practice at NVIDIA started the session with gusto, engaging the audiences with his insights into the current challenges in machine learning and data science. He also gave a RAPIDS technical overview and spoke in detail about the software architecture. Sundara also covered use cases and explained the concepts thoroughly, which was demonstrated by the numerous follow-up questions in the Q&A round.

Satyamoy Chatterjee, the Executive Vice President at Analyttica Data Labs was also the keynote speaker at the session. He spoke about using analytics and artificial intelligence in small and mid-sized financial companies.

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nvidia gpu rapids

Satyamoy also gave the example of a US-based financial company, which is in the business of extending credit to customers who are indexed high in terms of consumer credit risk. He demonstrated how by using advanced machine learning-based targeting, they were able to leverage the power of data.

The next session by Mitra Rath, the Senior Solutions Architect RAPIDS/ML at NVIDIA Graphics Pvt Ltd, was a hands-on session. This session covered RAPIDS end-to-end data science workflow and was a deep dive into the software architecture.

nvidia gpu rapids

The success of the workshop could also be seen in enthusiasm portrayed by the crowd, which was entirely made up of working professionals with mid to senior level experience.

There were many enthusiasts who had driven down from neighboring states like Andhra Pradesh and Kerala, among others. There were a few expatriates in the attendees as well, all the way from African countries.

Progress Igbinosa, who had specially attended the event to see how he could learn to utilize these machine learning techniques in his optometry business back home in Nigeria, said, “The professionals attending this event are great, the vibe in the office is wonderful. I got to learn so many new things, and meet so many new people. But the best thing I’m going to take away from the event is the ideas.”

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