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If you’re looking to sharpen your technical skills, get expert answers to specific questions, or dive into an entirely new area of development, you’ve come to the right place.

Sign up today for the latest overviews, insights, and how-to’s on today's central topics—AI, DC, HPC, IoT, and other essential acronyms—that you can use right away.

Wednesday, Dec 12, 2018 9:00 am PST

Under What Conditions will My Application give Reproducible Results?

When it comes to binary floating-point representation, Uncertainty rules. Need reproducible results, regardless of context? Hahaha … what? Oh. Turns out Intel® Software Dev Tools can make it happen. Especially its five FREE Performance Libraries. Go get them. Then tune in.

Users are often surprised when the same application run on the same data doesn’t give the same result. (WTH?) Welcome to floating-point arithmetic—an inexact and inherently uncertain approximation that’s great … except for when it isn’t. Like for critical functions that require exact reproducibility such as finance, quality assurance, and legal stuff.

This webinar addresses the dilemma and shows you how to build a serial application that delivers repeatable results …

  • When simply rerunning the same binary executable
  • For debug builds and release-optimized builds
  • When targeting or running on different processor types

In addition, learn the conditions under which reproducible results can be obtained for parallel applications making use of the Intel® Compiler with OpenMP* and key Intel® Performance Libraries: Intel® Math Kernel Library, Threading Building Blocks, and Intel® MPI.

Martyn Corden, Technical Consultant Engineer, Intel Corporation

Martyn Corden is a Technical Consulting Engineer in the Developer Products Division at Intel Corporation. He provides technical support for Intel® Fortran and C/C++ compilers for Windows*, Linux* and macOS*, with particular focus on HPC applications. Martyn came to Intel from the Supercomputer Computations Research Institute at Florida State University, where he had extensive experience with high-performance scientific applications. He has many years’ experience in writing, debugging, maintaining, porting and optimizing software for high-energy physics, including for several experiments at CERN in Geneva. Martyn holds a BA in Physics from Oxford University and a Ph.D. in High Energy Physics from the University of Birmingham.

Wednesday, Jan 9, 2019 9:00 am PST

Accelerating the Heterogeneous World with OpenCL*

OpenCL* offers huge benefits to a wide range of applications—big hitters are portability and efficient execution (including power usage). Is it easy to learn? No. Which is why Intel has a free SDK that makes it far easier.

OpenCL* (Open Computing Language) is a well-known and attractive standard for writing parallel programs that execute across a rich mix of heterogeneous platforms—for example, those that consist of CPUs, GPUs, FPGAs, programmable ASICs, and other hardware accelerators.

And unless you’ve been hunkered down in a wifi-deficient cave for the past year, you’re likely quite familiar that the need for OpenCL programs is growing. Fast.

Which is why you should register for this session.

In 55 minutes, you’ll learn the value of using OpenCL to take advantage of modern heterogeneous architectures, including:

  • Why OpenCL matters for achieving optimal performance and decreasing power consumption
  • How to get started with OpenCL
  • An overview of the Intel® SDK for OpenCL* Applications, and how this complete toolset can help you quickly build, debug, and analyze OpenCL kernel codes across Intel® CPUs and GPUs.

Be sure to download the FREE SDK now. Then sign up to attend the webinar.

Serge Lunev, Software Development Engineer, Intel Corporation

Serge is a software development tools architect who specializes in heterogeneous computing, and leads global engineering teams that focus on the tools and technologies driving next-generation software solutions. With Intel since 2004, Serge has over 20 years’ experience in software tools, including translators, compilers, IDEs and, most recently, OpenCL* development workflows.
Serge holds a Master’s of Science in Applied Mathematics from Moscow State University, and a PhD in Computer Science from Moscow Institute of Physics and Technology.

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