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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, Oct 10, 2018 9:00 am PDT

Exascale in Sight: MPI Communication Layer Migration Benefits

It’s a mere billion billion calculations per second … and it’s the future of human-brain-equivalent processing power. Find out how Intel® MPI Library can help push your applications into the new frontier.

Deliver flexible, efficient, scalable cluster messaging with the Intel® MPI Library—which implements the high-performance MPI-3.1 standard on multiple fabrics (matching the exascale MPICH CH4 codebase used by Argonne National Labs).

CH4 is designed for low software overheads to better exploit next-generation hardware. This change enables new capabilities in your MPI programs, reduced latency, and new programming models such as multi-endpoint MPI, which saturates the fabric, reduces memory usage per MPI rank, and produces multi-threaded MPI performance comparable to single threaded options.

Join us to learn about this and more, including:

  • How Intel MPI Library lets you quickly change or upgrade to new interconnects without requiring changes to the application or user-level operating environment
  • Benefits for application performance and simplifying the user experience from the underlying code
  • How to develop applications that can run on multiple cluster interconnects chosen by the user at runtime

Download Intel MPI Library for free.

James Tullos, Technical Consulting Engineer, Intel Corporation

James joined Intel in 2012, and is a Technical Consulting Engineer supporting Intel® Software Development Products. He focuses on parallel performance, primarily in HPC and Cluster environments, training customers to get the most from Intel Software Tools. His background is in aerospace engineering, with previous work on propulsion system analysis programs. James has a BS in Aerospace Engineering from Mississippi State University, and a Master’s of Science in Aeronautical and Astronautical Engineering from Purdue University. In the mythical spare time, he also enjoys reading, video games, and “random whatever”.

Wednesday, Oct 31, 2018 9:00 am PDT

Speed-Up Python* Applications & Soar Core Computations

Calling all Data Scientists. Hear the one about Python* not being as fast as language "X"? Not anymore. Intel® Distribution for Python* delivers native-code-quick performance―right out of the box.

Python* is among the most popular programming languages due to its ease-of-use for cloud-based Web applications and out-of-the-box performance.


It also has a reputation for executing scripts slower than its native equivalents due to its single-threaded nature, which provides language flexibility at the cost of performance.

Intel® Distribution for Python* overcomes this challenge, offering optimized numeric, scientific, and machine learning packages to accelerate Python performance on a wide range of Intel® processors.

Sign up to learn how the Intel distribution helps Data Scientists enable high-performance computing in Python and Machine Learning applications, including:

  • An overview of the Python performance packages
  • Methods to speed up Python performance
  • Intel-optimized scikit-learn performance speedups
  • Deep-dives on Intel® Data Analytics Acceleration Library in Python (PyDAAL)
  • Demos with examples

You don’t have to wait for the webinar. Download Intel® Distribution for Python* now.

Preethi Venkatesh, Technical Consultant Engineer, Intel Corporation

Preethi joined Intel in 2017, and works with the Intel Software and Services Group, driving customer adoption of Intel® Distribution for Python* and Intel® Data Analytics Acceleration Library through training, article publications and open-source contributions, and has published multiple software tools white papers. Before joining Intel, she was a Business Data Analyst at Infosys Limited for four years. Preethi has a Bachelor’s Degree in Instrumentation Technology/Technician from Visvesvaraya Technological University, Belgaum, India, and a Master’s Degree in Information Systems on Data Science from the University of Texas at Arlington.

Wednesday, Nov 7, 2018 9:00 am PST

The 24/7 Code Analyst Dedicated to Revving Your Platform & Applications

Quickly analyze workload behavior across the entire system and pinpoint where to focus optimizations with Intel® VTune™ Amplifier’s Platform Profiler. Download the free technical preview.

Intel® VTune™ Amplifier’s Platform Profiler measures how well a workload uses the underlying architecture, providing reports on how you can optimize various platform components: the CPU, memory, disk, storage layout, and PCIe* and network interfaces. Its operating system and platform-level tools can identify performance bottlenecks and mitigate them, producing an optimal configuration and performance for big data and analytics workloads.

Join us for an overview of the Platform Profiler—including how it can help software developers and infrastructure architects accelerate applications—plus a discussion on other tools and technologies developers can benefit from. The webinar will focus on:

  • Specific Intel and open-source tools, their benefits, capabilities, and uses
  • Examples of how specific methodologies and tools are used for benchmarking
  • The importance of code performance analysis and the role it plays in optimizing applications
  • Answers to the most common questions about profiling data

Download the free technical preview release of Platform Profiler today.

Milind Damle, Senior Director, Big Data Technologies, Intel Corporation

Milind joined Intel in 2002, and is a Senior Director in the Intel Software and Services Group, responsible for the performance engineering team for big-data analytics. He leads a team responsible for performance analysis, tuning, optimization and benchmarking these workloads and applications on IA as well as competitive platforms. The team delivers new features into Apache Hadoop and Spark projects and works with internal teams and external customers (ISVs, OEMs, CSPs and academia) to deliver these optimizations for IA. He earned his Master’s in Computer Science and Engineering from the Indian Institute of Technology in Mumbai.

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