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The Mathitis Society, India
Deep Learning using Cuda
This workshop will discuss why the parallel programming landscape is needed, summarize the OpenMP approach to multi-threading, and illustrate how it can be used to introduce parallelism.
About This Course
In the recent years the overall processing power is increasing, thanks to the new model of chip manufacturing. This model increases the overall processing power by adding additional processing cores to the microprocessor package. The processors will gradually come in heterogeneous configurations such as combination of high and low power cores, GPU’s etc. These are being termed as many core architecture. Currently, only a very small proportion of developers have expertise in parallel programming. For computer science faculty this also requires a radical shift in the way computer science subjects are taught. Even though high performance computing area has programmers working in parallel applications for years, very few people have got the understanding of issues involved in developing
multicore applications. What is very important is to begin the transition to “thinking in parallel” immediately, whether or not the mechanisms for doing so are ideal. This workshop will discuss why parallel programming landscape is needed, summarize the OpenMP approach to multi-threading, and illustrate how it can be used to introduce parallelism.
The Graphics Processing Unit or GPU is nowadays a mainstream component in Scientific Computing and Data Analytics. For relatively little money one can have supercomputer performance. However, some extra work has to be done to make an ordinary sequential program suitable for use on the GPU. One of the most important tools for using GPUs is currently “CUDA” (Compute Unified Device Architecture). This is basically an extension to the C programming language, which can be used to program the GPU in an easy way.
Duration: 2 day
This workshop will discuss why the parallel programming landscape is needed, summarize the OpenMP approach to multi-threading, and illustrate how it can be used to introduce parallelism. Similar mechanisms using GPU’s will also be discussed for Scientific Computing and Data Analytics.
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Course Modules and details of the program. will be mailed after registering into the course.
Session 1: Introduction and Basics
- Why Parallel Computing? Need for parallel Computing
- Multi-Core processors – Architecture and Design
- Introduction to Threads, Thread Basics and Basic concepts of parallel programming
- OpenMP- A Standard for Directive based Parallel Programming
- Hands on / Demonstration of various programs on multicore machines
Session 2: GPU Programming
- GPU’s for parallel Computing
- GPU’s Programming Model
- Hands on /Demonstration of various programs on GPU
- SDK, Toolkit and Installation of environemnt for GPU
- Working with various Libraries
- Demonstration of GPU and Tools with Sample Programs and OpenACC.
Session 3: Introduction to Deep Learning
- Intro to Deep Learning
- Intro to Deep learning using various S/w’s on GPU
- Demos using DIGITS
- A basic understanding of C programming Language or Java or Python.
- Interest in iterative solvers and similar workloads.
- Participants are required to bring their own laptops with Wi-Fi connectivity and chargers.
What is MCognition ?
The MCognition Initiative is one of the flagship platforms of TMS, wherein we work with the world’s leading companies to design and implement courses. These are tailor-made courses for students of various age-groups which incorporates a robust practical component and follows an intense corporate training method of teaching.
What is the refund policy ?
A full refund, will be given until 1 week prior to the course. Beyond this deadline, no refund will be entertained for the course.
How long is the course ?
The course length is 64 hours spread over 10 days.
Who will be teaching the course ?
Google Certified Trainers are in-charge of teaching the course. More commonly called Corporate Trainers, these are industry specialists and professionals, generally working with training employees in various companies.
Are there any pre-requisites ?
There are no pre-requisites to the course. The fundamentals are included in the program.
What is the conditional internship letter ?
At the end of the training program, a problem statement is given to the students to work upon for 2 weeks, following which their submissions will be evaluated and a letter of internship for 1 month would be awarded to the students. It is purely optional for the student to take this up.