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As a charitable Service based non-profit organization (NPO) educating and connecting the High Performance Computing user community to state of art technology for the purpose of Optimizing business processes and workforce advancement. Our technology focus includes AI, Cloud Computing, Data Science, Deep learning, Machine learning and visualization utilized in applications ranging from Manufacturing and Engineering, Financial services, Life Sciences, Energy, Academia and Government.

Lunch and Learn - June 2016 - Download Presentation! - SequenceL Overview and Customer Use Cases

27 Jun 2016 3:40 PM | SHPCP (Administrator)

The Society of HPC Professionals (SHPCP) -- invites you to attend:

A Lunch & Learn Round Table Discussion Meeting

SequenceL Overview and Customer Use Cases: A Better Way to Convert Your Algorithms into Robust, Massively Parallel Code 


The days of programming in a one-size-fits-all language are quickly becoming a thing of the past, especially for multicore and many-core systems. SequenceL is the right tool for the multicore and many-core programming job. SequenceL is a compact, powerful functional programming language and auto-parallelizing tool set that quickly and easily converts algorithms to robust, massively parallel code. SequenceL was designed to work in concert with existing programming languages, legacy code and libraries. SequenceL is additive to current design flows, tools, and training. It extends these investments with plug-ins for industry standard IDE’s (Eclipse, Visual Studio) and support for popular programming languages (C/C++, C#, Fortran, Java, Python, etc.). This lunch and learn session will begin with an overview of the SequenceL language, auto-parallelizing compiler, and runtime environment. It will include overviews of customer results including Seismic/RTM (ION Geophysical), CFD - Computational Fluid Dynamics (Southwest Research Institute), WirelessHART network graph generation (Emerson Process Management), and Video Processing (Lockheed Martin). We will then share some benchmarks of SequenceL vs. several other languages and approaches, including C++, OpenMP, TBB_GoBack, etc. 

Alex Habeger – Texas Multicore Technologies Performance Engineer Alex began working with massively parallel code in 2001 with the Department of Energy. Since then he has been involved in concurrent and parallel programming, ranging from embedded systems to large HPC simulations. Alex is proficient in OpenMP, Intel's Threading Building Blocks (TBB), handling raw threads, and how usage of each impacts memory and cache utilization. He holds a bachelors in Computer Science from University of Northern Iowa. 

Gary Martin– ION Geophysical, Director HPC and Software Engineering and 

Bill Menger –HPC Consultant for ION Geophysical will also be available for Q&A 









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