The Fifth Elephant 2019

Distributed/Parallel computing is at the heart of new technology. Every company, big or small want to make most of the technology available to them. One such niche technology is GPU computing. If used cautiously can save a lot of computing efforts and time across the applications. Business, with the boom in Machine learning/Deep learning techniques, are on the way to leverage this technology in their day to day work. Here, I present to you a real time application on how GPU can save computing efforts and reduce the computation time from 2 days to 20 seconds. Talk will cover the best case scenarios and use case for using the GPU for implementing recommendations at scale. The talk will start with the task overview, comparison between CPU and GPU and how and when to utilise GPU for the task in hand and other similar tasks.

Here’s the blog details, I wrote and the talk will be based on it
https://medium.com/walmartlabs/how-gpu-computing-literally-saved-me-at-work-fc1dc70f48b6

Outline

Distributed/Parallel computing is at the heart of new technology. Every company, big or small want to make most of the technology available to them. One such niche technology is GPU computing. If used cautiously can save a lot of computing efforts and time across the applications. Business, with the boom in Machine learning/Deep learning techniques, are on the way to leverage this technology in their day to day work. Here, I present to you a real time application on how GPU can save computing efforts and reduce the computation time from 2 days to 20 seconds. Talk will cover the best case scenarios and use case for using the GPU for implementing recommendations at scale. The talk will start with the task overview, comparison between CPU and GPU and how and when to utilise GPU for the task in hand and other similar tasks.

Here’s the blog details, I wrote and the talk will be based on it
https://medium.com/walmartlabs/how-gpu-computing-literally-saved-me-at-work-fc1dc70f48b6

Speaker bio

A seasoned Data Scientist having 3+ years of experience in ML field, with Computer Science background, spanning over various domains and problem-solving mindset. Excelled in various Machine learning and Optimization problems specific to Retail with key interests in Markdowns, Price-elasticity, Item-embeddings, Item-linkage and Price Investment. Enthusiastic about implementing Machine Learning models at scale and knowledge sharing via blogs, talks, and meetups, etc..
Love to explore new places and working out in leisure time.
Medium ~ https://medium.com/@mungoliabhishek81

Links

• https://medium.com/walmartlabs/how-gpu-computing-literally-saved-me-at-work-fc1dc70f48b6

Slides

https://www.slideshare.net/abhishekmungoli81/how-gpu-computing-literally-saved-me-at-work