Accelerating data-science by 50x -- Nvidia RAPIDS Workshop
mar. 30 octobre à 23:00
Introduction: RAPIDS, is an opensource tool for GPU accelerated data-science. Built using Nvidia general purpose compute on GPUs framework CUDA, this tool was launched on October 10th, 2018. What is this workshop about? Nvidia RAPIDS is a robust platform for GPU-accelerated data science: analytics, machine learning. One of the most anticipated updated for Rapids will feature support for data visualization. The libraries are open-source, built with the support of open-source contributors and available immediately at www.RAPIDS.ai. Initial benchmarks show game-changing speedups of upto 50x with RAPIDS running on Nvidia GPU powered systems, compared with CPU-only systems, reducing experiment iteration from hours to minutes. Rapids uses CUDA version 9.2 or higher. For this workshop we will be using CUDA 10. Released on September 19, 2018, Nvidia CUDA 10 is the latest release of CUDA. We will be running the code on Ubuntu 18.04 LTS instance. Ubuntu[masked] LTS (Bionic Beaver) is the latest long term support variant of Ubuntu linux. It will be supported for 5 years until April 2023. It is one of the favorite choice of linux distribution for deploying scalable deep-learning applications, both in research and in production settings. Read more about this distribution here: https://wiki.ubuntu.com/BionicBeaver/ReleaseNotes This session will cover the basics of Nvidia CUDA and use of CUDA to accelerate RAPIDS based python data-science applications. Nvidia CUDA is a parallel computing platform and programming model for general computing on graphical processing units (GPUs) from Nvidia. CUDA handles the GPU acceleration of tasks using tasks such as Tensorflow and RAPIDS. Important to know: This is a paid workshop. Access to Nvidia Tesla P100 GPU powered virtual machines (VMs) for hands-on deployments are only available for participants who purchased a ticket. Last minute purchase of tickets may not receive a VM due to allocation bottlenecks. Remember to buy the tickets at-least 24 hours before the event. The tickets are available for purchase here: https://www.moad.computer/store/p36/Healthcare_Analytics The goal of this workshop is to learn how to leverage GPUs to accelerate data-science applications using RAPIDS. Please bring a laptop to follow along the content effectively. Requirements: 1) Basics of shell scripting
2) Basics of python 3
3) Familiarity with tools like nano and screen in linux TLDR: Nvidia CUDA 10, end-to-end data-science application acceleration using RAPIDS.
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