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India Time zone Webinars:
Learn more about CUDA and latest features through these webinars now scheduled in India Time zone.

Upcoming Webinars

This series starts with basics of CUDA. It also includes details of our latest announcement on Directive based programming for CUDA (OpenACC) and CUDA 5.0 features and enhancements. Get insider hints and tips on best use of these powerful aids. Get your queries resolved from NVIDIA Developer Technology Engineering team and NVIDIA staff online to answer questions.

All dates and time reference are for Calcutta, India. Please follow the links to register for the webinars. The webinar system will send emails confirming and also reminding you of your registration.

  • Introduction to GPU Computing & CUDA Architecture
    (21st Sep 2012, 10 am – 11 am IST)
    This Webinar will cover basics of GPGPU computing and CUDA Programming
  • Programming GPUs with OpenACC
    (28th Sep 2012, 10 am – 11 am IST)
    OpenACC is a programming standard for parallel computing on accelerators (including GPUs) using directives. It is designed to harness the transformative power of heterogeneous computing systems easily and quickly. In this tutorial you will learn how to add simple compiler hints to your code to expose parallelism to the compiler, allowing it to map computation onto an accelerator. OpenACC directives allow developers to make simple and portable code changes, enabling an easier migration to accelerated computing. This tutorial that will take you from an overview through how to optimize your code. It will provide an overview of OpenACC programming in which you will learn about applying basic OpenACC directives to your code, with examples, and how to write OpenACC code that interoperates with GPU-accelerated libraries and CUDA code.
  • Introducing CUDA 5: New Features and Benefits
    (5th Oct 2012, 10 am – 11 am IST)
    Now applicable to a broader set of algorithms, CUDA 5 empowers developers with advanced features including separate compilation and GPU object linking that allow developers to call library functions directly from GPU code. Developers can also now take advantage of powerful new tools such as NVIDIA® Nsight™ Eclipse Edition integrated development environment. With CUDA 5, accelerating your code is now easier than ever.
  • Nsight Eclipse Edition: High Productivity IDE for CUDA Development on Linux & MacOS
    (12th Oct 2012, 10 am – 11 am IST)
    The New Nsight, Eclipse Edition helps you explore the power of GPU computing with the productivity of Eclipse with an integrated, graphical development environment on Linux and Mac.
    • Develop, debug, and profile your GPU application all within a familiar Eclipse-based IDE
    • Integrated CUDA samples makes it quick and easy to get started
    • Integrated expert analysis system provides automated performance analysis and step-by-step guidance to fix performance bottlenecks in the code
    • Easily port CPU loops to CUDA kernels with automatic code refactoring
    • Semantic highlighting of CUDA code makes it easy to differentiate GPU Code from CPU code
    • Generate code faster with CUDA aware auto code completion and inline help.
Previous Webinars

This series covered the latest announcement made in GTC Conference 2012 which was held in San Jose from 14th -17th May 2012. Get insight into new Kepler Architecture by NVIDIA, latest CUDA 5 release features and how easily applications can be ported to GPU using OpenACC in this series.

  • Programming GPUs with OpenACC - Part1
    (Thursday, June 28, 2012, 10-11:30 am)
    OpenACC is a programming standard for parallel computing on accelerators (including GPUs) using directives. It is designed to harness the transformative power of heterogeneous computing systems easily and quickly. In this tutorial you will learn how to add simple compiler hints to your code to expose parallelism to the compiler, allowing it to map computation onto an accelerator. OpenACC directives allow developers to make simple and portable code changes, enabling an easier migration to accelerated computing. This is part 1 of a 3-part tutorial that will take you from an overview through how to optimize your code. Part 1 will provide an overview of OpenACC programming in which you will learn about applying basic OpenACC directives to your code, with examples, and how to write OpenACC code that interoperates with GPU-accelerated libraries and CUDA code.
    Link to Recorded Session >
  • Programming GPUs with OpenACC - Part2
    (Thursday, July 5, 2012, 10-11:30 am)
    OpenACC is a programming standard for parallel computing on accelerators (including GPUs) using directives. It is designed to harness the transformative power of heterogeneous computing systems easily and quickly. In this tutorial you will learn how to add simple compiler hints to your code to expose parallelism to the compiler, allowing it to map computation onto an accelerator. OpenACC directives allow developers to make simple and portable code changes, enabling an easier migration to accelerated computing. This is part 2 of a 3-part tutorial that will take you from an overview through how to optimize your code. Part 2 will cover how GPUs execute parallel programs, and apply this understanding to optimizing OpenACC examples to gain larger speedups and accelerate applications with various types of parallelism. You will also learn how to use NVIDIA profiling tools to target your optimizations.
    Link to Recorded Session >
  • Programming GPUs with OpenACC - Part3
    (Friday, July 6, 2012, 10-11:30 am)
    OpenACC is a programming standard for parallel computing on accelerators (including GPUs) using directives. It is designed to harness the transformative power of heterogeneous computing systems easily and quickly. In this tutorial you will learn how to add simple compiler hints to your code to expose parallelism to the compiler, allowing it to map computation onto an accelerator. OpenACC directives allow developers to make simple and portable code changes, enabling an easier migration to accelerated computing. This is part 2 of a 3-part tutorial that will take you from an overview through how to optimize your code. Part 2 will cover how GPUs execute parallel programs, and apply this understanding to optimizing OpenACC examples to gain larger speedups and accelerate applications with various types of parallelism. You will also learn how to use NVIDIA profiling tools to target your optimizations.
    Link to Recorded Session >
  • CUDA 5 and beyond
    (Friday, July 13, 2012, 10 - 11:30 am)
    CUDA, NVIDIA's platform for parallel computing, has grown rapidly in the past 5 years. The performance and efficiency of software built on CUDA, combined with a thriving ecosystem of programming languages, libraries, tools, training, and service providers, have helped make GPU computing a leading HPC technology.

    CUDA 5 and the Kepler GPU architecture don't just increase application performance; they enable a more powerful parallel programming model that expands the possibilities of GPU computing, and language features that improve programmer productivity.

    In this talk you will hear about these revolutionary features and get insight into the philosophy driving the development of new CUDA hardware and software. You will learn about NVIDIA's vision for CUDA and the challenges for the future of parallel software development.
    Link to Recorded Session >
  • Inside Kepler
    (Friday, July 20, 2012, 10–11:30 am)
    In this talk, individuals from the GPU architecture and CUDA software groups will dive into the features of the compute architecture for Kepler, NVIDIA's new transistor GPU. From the reorganized processing cores with new instructions and processing capabilities, to an improved memory system with faster atomic processing and low-overhead ECC, we will explore how the Kepler GPU achieves world leading performance and efficiency, and how it enables wholly new types of parallel problems to be solved.
    Link to Recorded Session >

GPU Computing Tutorial Webinar Series

This series covered the basics of data parallel computing on GPUs leveraging NVIDIA's CUDA architecture. Tutorials covered many topics including C for CUDA, PGI Fortran extensions, Directive based programming to get speedups with little effort and latest CUDA release features, presented by NVIDIA Developer Technology Engineering team and NVIDIA staff online to answer questions.

Email us:
Please feel free to email us at CUDA-Technology-IN[at]nvidia.com for your suggestions or if you want to have repeat webcast of any webinar.



 
 
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