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Miss a session? No problem. All past sessions can be accessed on-demand for your convenience. (All webinars are available 2 days after they air live.)

Wednesday, March 10, 2021 9:00 am PST
#oneAPI

[NEW DATE] Be a Cluster Champion! Tune Your Way to MPI Performance.

If you want to improve your MPI application performance, this webinar is for you. Find out how a cross-architecture, multi-fabric, message-passing library can help your apps perform better on HPC clusters.

Message Passing Interface (MPI) is a powerful library standard that allows for the parallel execution of applications across multiple processors on a system while allowing users to run their applications across multiple nodes.

In this webinar, Intel technical engineers Cory Levels and James Tullos will introduce you to the Intel® MPI Library including:

  • How to adjust fabric settings and set MPI tuning to maximize cluster application performance
  • A demonstration of the library’s latest optimization features
  • Xe accelerator support and pinning offloaded code to GPU cores

Download the software
Get the Intel® MPI Library as part of the Intel® oneAPI HPC Toolkit, a collection of optimized tools for high-performance computing.

Resources

  • Sign up for an Intel® DevCloud for oneAPI account—a free development sandbox with access to the latest Intel® hardware and oneAPI software.
  • Explore oneAPI, including developer opportunities and benefits
  • Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each bi-weekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Available wherever you get your podcasts.

 

Cory Levels, Technical Consulting Engineer, Intel Corporation

Cory Levels is a Technical Consulting Engineer responsible for supporting Intel Software Development Tools, with a special focus on the performance analysis tools Intel® VTune™ Profiler and Intel® Advisor. She recently transitioned to the Technical Consulting Engineering Team after completing a six month rotational program through Intel. She has a background in development and was previously on a debug team supporting Intel’s oneAPI efforts.

Cory holds a Bachelor’s in Computer Engineering from Southern Illinois University Edwardsville with minors in Computer Science and Mechanical Engineering. In her spare time she enjoys hiking, playing soccer and volleyball.

James Tullos, Technical Consulting Engineer, Intel Corporation

James Tullos is a Technical Consulting Engineer responsible for all things “customer technical support and training” on application performance using Intel Intel® Software Development Tools. He focuses on parallel performance in HPC and cluster environments, with specific knowledge around distributed memory computing using the Message Passing Interface (MPI).

James enjoys sharing his knowledge and is a regular presence at technical trade shows, workshops, and conferences. Prior to joining Intel, he worked in the aerospace engineering field focused on propulsion system analysis programs.

James holds an MS in Aeronautical and Astronautical Engineering from Purdue University, and a BS in Aerospace Engineering from Mississippi State University.

Mike W. Lee, Senior Product Marketing Engineer, Intel Corporation

Mike Lee is a Senior Product Marketing Engineer at Intel. He leads efforts in marketing Intel’s software development tools—compilers, analysis tools, and performance libraries—focused on the technical, enterprise, and cloud computing segments. Prior to joining Intel in 2011, Mike held a variety of roles spanning consumer electronics and industrial/scientific instrumentation design at the integrated circuit level, board level and software system design level. Mike holds a Masters of Science in Electrical Engineering (SMEE) from Massachusetts Institute of Technology.

Wednesday, March 17, 2021 9:00 am PDT
#oneAPI

How Tangent Studios Creates Production-Quality Rendering

With all of the different types of renderers available, choosing the best one for your visual application needs can be difficult. Find out why Tangent Animation chose Intel tools for the job … and liked them so much, they incorporated them into Blender.

When choosing the right rendering engine there is a lot to consider, including what type it is—3D, 2D, realtime, non-realtime, custom—and the technology, algorithms, and features it offers.

In this session, Tangent Animation talks about one of them: the Intel® oneAPI Rendering Toolkit, which this studio of animation and film production pros has been using for some of its creative storytelling, including the animated sci-fi feature Next Gen, streaming on Netflix.

Join Tangent Sr. Software Engineer Stefan Werner and Intel Sr. Director of Rendering and Visualization Jim Jeffers to learn about:

  • How the studio is taking full advantage of Intel® oneAPI tools to create a production-quality solution for its projects 
  • How it is incorporating three Render Kit tools—Intel® Embree, Intel® Open Image Denoise, and Intel® Open Volume Kernel Library—into Blender
  • Tangent Lab’s latest studio asset management service, LoUPE—a fresh take on a cloud-based animation production pipeline created for artists, by artists
  • What’s comihttps://www.tangent-labs.com/ng next for the studio

Download the software
Get the Intel® oneAPI Rendering Toolkit which includes seven rendering and ray tracing libraries—including those discussed in this session—for creating high-performance, hi-fidelity visual experiences.

Watch these videos

Additional Resources

  • Sign up for an Intel® DevCloud for oneAPI account—a free development sandbox with access to the latest Intel® hardware and oneAPI software.
  • Explore oneAPI, including developer opportunities and benefits
  • Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each bi-weekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Available wherever you get your podcasts.
Jim Jeffers, Senior Director, Intel Advanced Rendering and Visualization Team

Jim Jeffers is a Sr. Principal Engineer whose expertise spans high-performance computing, software visualization, graphics, TV and video, and data communications.

Currently serving as Sr. Director of Intel Advanced Rendering and Visualization, he and his team design and develop the open source rendering library Intel® Rendering Framework used to create animated movies, special effects, automobile design, and scientific visualization. To hone the library’s capabilities, they’ve worked with top companies such as Disney and DreamWorks, and scientists including Stephen Hawking.

Jim joined Intel in 2008 and participated in the development of manycore parallel computing and the Intel® Xeon Phi™ product family. Among his many accomplishments, he has co-authored four books on manycore parallel programming and helped develop the Tech Emmy-winning virtual “First Down Line” technology used on live American football TV broadcasts.

Jim earned a Bachelor’s Degree in Computer Science from La Salle University in Philadelphia, PA, USA.

Stefan Werner, Senior Software Engineer, Tangent Animation

A 3D graphics software developer over a decade of writing high-performance, cross-platform code in C++, Stefan is experienced in implementing state-of-the-art rendering in digital content creation (DCC) applications. As a core developer of Poser, a 3D animation and rendering software, his scope spanned UI design to assembly-level optimization. As main developer of the render engine, he implemented features such as irradiance caching, subsurface scattering, texture caching and physically-based shading, improving performance and robustness so that the render engine could be used by anyone from hobbyists to studios.

Wednesday, March 24, 2021 9:00 am PDT
#DataScience

Using Low-Precision Optimizations for High-Performance DL Inference Applications

Deep learning training and inference are computational heavyweights for research and for AI generally. But with that potency comes computational complexity and challenges with accuracy and performance. Find out how to overcome them in this session.

With advances in hardware acceleration and support for low precision, Deep Learning inference delivers higher throughput and lower latency. However, Data Scientists and AI developers often need to make a trade-off between accuracy and performance. There are also the deployment challenges due to high computational complexity of inference quantization. This webinar talks about the techniques and strategies such as automatic accuracy-driven tuning for post-training quantization and quantization aware training to overcome these challenges.

Join us to learn about Intel’s new low precision optimization tool and how it helped CERN OpenLab to reduce inference time while maintaining the same level of accuracy on convolutional Generative Adversarial Networks (GAN). The webinar will give insights about how to handle strict precision constraints that are inevitable while applying low precision computing to generative models.

Sofia Vallecorsa, AI and Quantum Researcher at CERN openlab

Sofia Vallecorsa is an accomplished physicist who specializes in scientific computing with commanding expertise in ML/DL architectures, frameworks, and methods for distributed training and hyper-parameters optimization. Joining CERN in 2015, she is responsible for several projects in MLDL, quantum computing and quantum machine learning, and also supervises masters and doctoral thesis students in these same fields. Sofia holds a PhD in High Energy Physics from University of Geneva.

Feng Tian, Machine Learning Engineer, Intel Corporation

Feng is a senior deep learning engineer in machine learning performance team with IAGS(Intel Architecture, Graphic and Software) group. He leads the development of Intel Low Precision Optimization Tool and contributes on intel optimized deep learning frameworks, such as TensorFlow and PyTorch. He has 14 years of experience working on software optimization and low level driver development on IA platform.

Wednesday, March 31, 2021 9:00 am PDT
#oneAPI

Visualize and Tune Heterogeneous Programs

Heterogeneous application development requires an understanding of how your algorithms map to each device. This session showcases a streamlined way to gain insights and efficiencies into your code’s parallel constructs using DPC++.

Heterogeneous application development has introduced new challenges for experienced and novice developers alike. In particular, the need to understand how your programming language maps algorithms to each device.

This webinar focuses on how to gain that understanding for cross-architecture applications written in Data Parallel C++ (DPC+). Specifically, it showcases how Flow Graph Analyzer, a feature of Intel® Advisor, provides insights into efficiencies of DPC++ data parallel constructs that help you improve algorithm performance.

Join Intel software specialists Anoop Madhusoodhanan Prabha and Kevin O’Leary to learn about:

  • The asynchronous task graph of your DPC++ algorithms and its similarities with other commonly used heterogeneous programming models
  • How to identify performance penalties using diagnostics reported on simple language use
  • How to determine scheduling inefficiencies—which kernels can be executed independently or if the kernels are being scheduled as intended
  • Flow Graph Analyzer reports and recommendations that can help improve the performance of data parallel algorithms

Includes demonstrations and code walkthroughs.

Get the software

  • Download Intel® Advisor as part of the Intel® oneAPI Base Toolkit, a core set tools and libraries for developing high-performance, data-centric applications across diverse architectures.
  • Already have the Base Kit … or want Intel Advisor as a standalone product? Get it here.

Resources

  • Sign up for an Intel® DevCloud for oneAPI account—a free development sandbox with access to the latest Intel® hardware and oneAPI software.
  • Explore oneAPI, including developer opportunities and benefits
  • Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each bi-weekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Available wherever you get your podcasts.

 

Anoop Madhusoodhanan Prabha, Software Engineer, Intel Corporation

Anoop Madhusoodhanan Prabha is a Software Engineer in Intel’s Software and Services Group. He currently works as a Technical Consulting Engineer on the C/C++ compiler support team. He joined Intel in 2009. Since he joined Intel, he has worked on optimizing various customer applications by enabling multi-threading, vectorization and other micro architectural tunings. He has experience working with OpenMP, Cilk™ Plus, Intel® TBB, CUDA etc. His current interest are in Processor and GPU architecture, heterogeneous computing and high performance computing. He has an M.S. degree in Electrical Engineering from State University of New York at Buffalo, US. His e-mail is anoop.madhusoodhanan.prabha@intel.com

Kevin O’Leary, Senior Software Developer and Lead Technical Consulting Engineer, Intel Corporation

Kevin O’Leary is a Senior Software Developer and Lead Technical Consulting Engineer whose expertise includes compilers, debuggers, and software performance tools. He’s currently responsible for performance optimization using Intel® Advisor and Intel® VTune™ Profiler and was a key developer of the Intel® Parallel Studio XE development suite. Prior to joining Intel, Kevin spent many years as a debugger engineer for IBM/Rational Software.

Kevin holds a Bachelor’s in Computer Science from University of Massachusetts and a Master’s in Computer Science from Oregon Health and Science University.

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