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Best Practices for Speed in Deep Learning Applications on Intel Architecture

July 3, 2018

You have set up a deep learning model that you are planning to train on an Intel architecture processor. In order to be productive, you have to minimize the training time. You run the application and see that it takes N seconds for a single training epoch. How do you know if it is good? If improvement is possible, what can you do to improve the training time? Are there tools to identify a tuning strategy? Intel software development tools can answer these questions to maximize your productivity in deep learning on Intel architecture. At the Intel AI DevCon 2018 in San Francisco, Alaa Eltablawy (Colfax) presented a workshop that demonstrates how this works. For the workshop, attendees received access to the Intel® AI DevCloud, where they could experiment with the optimization of a TensorFlow-based application for image segmentation. The instructor demonstrated the performance analysis results obtained with Intel® VTune Amplifier and Application Performance Snapshot and explained how this analysis consistently guides you to the use of known “performance tuning knobs” in [...]

HOW Series “Deep Dive”: Webinars on Performance Optimization – 2017 Edition

June 30, 2017

Register Why Attend Roadmap Instructor Prerequisites Cluster Materials Book In a Nutshell HOW Series “Deep Dive” is a free Web-based training on parallel programming and performance optimization on Intel architecture. The workshop includes 20 hours of instruction and code for hands-on exercises. This training is free to everyone thanks to Intel’s sponsorship. You can access the video recordings of lectures, slides of presentations and code of practical exercises on this page using a free Colfax Research account. To run the hands-on exercises, you will need a multi-core Intel architecture processor and the Intel C++ Compiler. You can get this compiler for 30 days at no cost using an evaluation license for Intel Parallel Studio [...]

MC² 004: Signal Processing in a Physics Experiment

May 30, 2017

Interested in this webinar? See more webinars like this. Speaker Prof. Jeffrey S. Dunham, Professor of Physics, Middlebury College Prof. Jeffrey S. Dunham has taught physics for 34 years at Middlebury College in Middlebury, Vermont, where he is now William R. Kenan Jr. Professor of Natural Sciences. He currently conducts experimental research in nonlinear dynamics. He is using HPC techniques at the workstation level to analyze large data sets from experiments that can be performed in a small-college laboratory. He received the Bachelor of Science degree in physics from the University of Washington in 1975 and the Ph.D. in physics from Stanford University in 1981. Presentation Savitzky-Golay Filter Algorithm for Large One-Dimensional Data Sets A chaotic pendulum experiment in our laboratory performs about 275 million digitized angle measurements in a 24-hour day. A Poincaré plot of the raw data shows significant and unacceptable discretization effects from the optical rotary encoder used to measure angle. The raw data is therefore passed through a Savitzky-Golay (SG) filter [...]

MC² 005: Biological Development Modeling

May 30, 2017

Interested in this webinar? See more webinars like this. Speaker Pablo González de Aledo Marugán, Postdoctoral Research Assistant, Imperial College of London Pablo González de Aledo studied telecommunications engineering at thec University of Cantabria, Santander, Spain, and finished his studies at the Network-on-Chip team in ST-Microelectronics Grenoble, France. After working in the modeling and simulation of high-performance, multi-core and heterogeneous platforms for some European projects he became interested in the theory behind formal methods and worst-case-execution-time and moved to the Department of Computing at Macquarie University, Sydney, Australia, to complement his Ph. D. studies. He is now a Postdoctoral Research Assistant at Imperial College of London. Presentation An optimization approach for the computational modeling of biological development Current research in the field of computational biology often involves simulations on high-performance computer clusters. It is crucial that the code of such simulations is very efficient and correctly reflects the model [...]

Webinar: Demystifying Vectorization

May 18, 2017

Free Webinar Abstract Have you heard of code vectorization, but not sure how it applies to your work? Rest assured, you are in a good company. Furthermore, even seasoned computing professionals have a good excuse for not being familiar with this concept! That said, now is a great time to learn about writing vectorized code. That is because in modern Intel processors, vector instructions may speed up arithmetic instructions by up to a factor of 16. However, you must design computational code in a way that makes vector processing possible. In this 1-hour webinar I will explain what to expect from vectorization, and how to make sure that your code has it: Manual and compiler-assisted vectorization Assessing your success with vectorization Loop was vectorized – what’s next? Speaker Andrey Vladimirov, Head of HPC Research, Colfax International Dr. Andrey Vladimirov’s primary research interest is the application of modern computing technologies to computationally demanding scientific problems. Prior to joining Colfax, Andrey was involved in theoretical astrophysics [...]

MC² 003: Plasma Simulation with Particle-in-Cell Code

April 17, 2017

Interested in this webinar? See more webinars like this. Speaker Dr. Anastasia Perepelkina, Researcher, Keldysh Institute of Applied Mathematics Dr. Anastasia Perepelkina is a researcher at the Keldysh Institute of Applied Mathematics in Moscow, Russia. Plasma particle-in-cell simulation has been her main scientific interest since the master’s program at the NRNU MEPhI and it is the topic of her PhD thesis. She is a member of the laboratory with a long history of the development of plasma simulation methods, efficient algorithms, and applications. Beyond that, she has worked on the implementation of high-order schemes in high-performance codes for stencil simulation in optics and seismology, and on the application of the resulting code. Presentation Particle-in-cell Code with LRnLA Algorithms, Performance Tests on KNL CFHall is a plasma simulation code based on a particle-in-cell method. It uses the finite difference method on a rectangular mesh for Maxwell equations, and couples it to superparticle traversal the mesh in a self-consistent approach. The uniqueness of CFHall [...]

MC² 002: CoMD, Molecular Dynamics Proxy Application

March 3, 2017

Interested in this webinar? See more webinars like this. Speaker Dr. Adedoyin Adetokunbo “Toks”, Staff Scientist Los Alamos National Laboratory Dr. Adedoyin Adetokunbo (“Toks”) is currently a Staff Scientist at Los Alamos National Laboratory (LANL). He currently serves as a member of the Future Application and Architectures (FAA) and Application Performance Team (APT). Previously worked as a postdoctoral fellow at University of Notre Dame’s Mechanical Engineering department. He served as a lead in constitutive modeling of complex heterogeneous materials. A native of Nigeria, Toks arrived in Mississippi in the year 2000, and acquired his Bachelor’s in Applied Mathematics and Mechanical Engineering. In addition, he received his Master’s degrees in field of Computational Fluid Dynamics with an emphasis in turbulence modeling in real and spectral space. He then completed his Ph.D. in Computational Engineering with a focus on modeling and simulating phase transformation in polycrystalline materials. Presentation A case study on software [...]

MC² 001: Smooth Particle Hydrodynamics Optimization

February 11, 2017

Interested in this webinar? See more webinars like this. Speaker Dr. Fabio Baruffa, Sr. HPC Application Specialist Leibniz Supercomputing Centre Since 2016, Dr. Fabio Baruffa is Senior HPC Application Specialist at Leibniz Supercomputing Centre (LRZ) in Munich. He is a member of the Intel Parallel Computing Center (IPCC) at LRZ, focusing on code modernization and porting of scientific applications. Prior to LRZ, he has worked as HPC researcher at Max-Planck Computing and Data Facility (MPCDF), Jülich Research Center and Cineca Supercomputing involved in HPC software development and analysis of scientific codes. His main research interests are in the area of computational methods and optimizations for HPC systems. He holds a PhD in Physics from University of Regensburg for his research in the area of spintronics device and quantum computing. Presentation Performance Optimization of SPH Algorithms for Multi/Many-Core Architectures In the framework of the Intel Parallel Computing Centre at the Research Campus Garching in Munich, our group at LRZ presents recent results on performance [...]

MC² Series: Modern Code Contributed Talks

February 10, 2017

In Modern Code Contributed Talks, or MC² Series, experts in computational disciplines share their experience. Register for these ongoing webinars to learn the performance optimization methods used in real-life applications. Would you like to contribute a talk? Contact us. Scholarship is available in the form of access to a diverse collection of powerful computing [...]

Regional Trainings Begin for 2017

February 8, 2017

We are resuming our regional hands-on training on parallel programming and optimization at major universities across the United States. This year, in addition to teaching performance tuning on Intel Architecture, our program will include Hands-on exercises on our new Colfax Cluster with Intel Xeon Phi processors x200 and Information about machine learning on Intel Architecture Our first stop is Yale University on February 22-23. For future events, watch our Regional Training [...]
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