Learn about MATLAB Engineers – not sales!

Slides:



Advertisements
Similar presentations
The Complete Technical Analysis and Development Environment An attractive alternative to MATLAB and GAUSS - Physics World.
Advertisements

Building a CFD Grid Over ThaiGrid Infrastructure Putchong Uthayopas, Ph.D Department of Computer Engineering, Faculty of Engineering, Kasetsart University,
Introduction to the CUDA Platform
MATLAB MATLAB is a high-level technical computing language and
Intel® performance analyze tools Nikita Panov Idrisov Renat.
1 DISTRIBUTION STATEMENT XXX– Unclassified, Unlimited Distribution Laser Propagation Modeling Making Large Scale Ultrashort Pulse Laser Simulations Possible.
MATLAB Presented By: Nathalie Tacconi Presented By: Nathalie Tacconi Originally Prepared By: Sheridan Saint-Michel Originally Prepared By: Sheridan Saint-Michel.
Parallel Programming Henri Bal Rob van Nieuwpoort Vrije Universiteit Amsterdam Faculty of Sciences.
10.1 © 2007 by Prentice Hall 10 Chapter Improving Decision Making and Managing Knowledge.
Numerical Grid Computations with the OPeNDAP Back End Server (BES)
Teaching with MATLAB - Tips and Tricks
Parallelization with the Matlab® Distributed Computing Server CBI cluster December 3, Matlab Parallelization with the Matlab Distributed.
October 26, 2006 Parallel Image Processing Programming and Architecture IST PhD Lunch Seminar Wouter Caarls Quantitative Imaging Group.
© 2004 The MathWorks, Inc. 1 MATLAB for C/C++ Programmers Support your C/C++ development using MATLAB’s prebuilt graphics functions and trusted numerics.
1 1 Hybrid Cloud Solutions (Private with Public Burst) Accelerate and Orchestrate Enterprise Applications.
Hans-Peter Plag October 2, 2014 Session 1 Introduction to the sessions Elements of Computer Literacy ? ?
© 2005 The MathWorks December 2 nd, 2005 MATLAB ® and HDF Accelerating Engineering Productivity and Scientific Discovery.
© 2008 The MathWorks, Inc. ® ® Parallel Computing with MATLAB ® Silvina Grad-Freilich Manager, Parallel Computing Marketing
Cloud Computing 1. Outline  Introduction  Evolution  Cloud architecture  Map reduce operation  Platform 2.
Parallel Processing CS453 Lecture 2.  The role of parallelism in accelerating computing speeds has been recognized for several decades.  Its role in.
Pooria Varahram received the Bachelor degree in Electrical, Electronics Engineering from the Khaje Nasir University, Tehran, Iran in Later, he received.
Compiler BE Panel IDC HPC User Forum April 2009 Don Kretsch Director, Sun Developer Tools Sun Microsystems.
Uncovering the Multicore Processor Bottlenecks Server Design Summit Shay Gal-On Director of Technology, EEMBC.
Parallel Computing with Matlab CBI Lab Parallel Computing Toolbox TM An Introduction Oct. 27, 2011 By: CBI Development Team.
1 Computer Programming (ECGD2102 ) Using MATLAB Instructor: Eng. Eman Al.Swaity Lecture (1): Introduction.
1 © 2012 The MathWorks, Inc. Parallel computing with MATLAB.
4.2.1 Programming Models Technology drivers – Node count, scale of parallelism within the node – Heterogeneity – Complex memory hierarchies – Failure rates.
Group I Renjith Deepesh Praveesh P Varun V Subramanian Halesh P K.
How to use Matlab Analysis and Visualization Software Paul Harris GCRC Research Skills Workshop May 24, 2002.
Alternative ProcessorsHPC User Forum Panel1 HPC User Forum Alternative Processor Panel Results 2008.
Interactive Supercomputing Update IDC HPC User’s Forum, September 2008.
BOĞAZİÇİ UNIVERSITY DEPARTMENT OF MANAGEMENT INFORMATION SYSTEMS MATLAB AS A DATA MINING ENVIRONMENT.
EGR 115 Introduction to Computing for Engineers Introduction to Computer Programming Wednesday 27 Aug 2014 EGR 115 Introduction to Computing for Engineers.
Scientific Programmes Committee Centre for Aerospace Systems Design & Engineering Amitay Isaacs Department of Aerospace Engineering Indian Institute of.
EGEE-III INFSO-RI Enabling Grids for E-sciencE EGEE and gLite are registered trademarks Enabling the use of e-Infrastructures with.
3/12/2013Computer Engg, IIT(BHU)1 PARALLEL COMPUTERS- 1.
Application for Morphological Image Processing Dan Campbell 12/13/06 University of Wisconsin – Madison Departments of Computer Engineering and Computer.
HPC University Requirements Analysis Team Training Analysis Summary Meeting at PSC September Mary Ann Leung, Ph.D.
Kriging for Estimation of Mineral Resources GISELA/EPIKH School Exequiel Sepúlveda Department of Mining Engineering, University of Chile, Chile ALGES Laboratory,
Introduction to Performance Tuning Chia-heng Tu PAS Lab Summer Workshop 2009 June 30,
Constructing a system with multiple computers or processors 1 ITCS 4/5145 Parallel Programming, UNC-Charlotte, B. Wilkinson. Jan 13, 2016.
MATLAB, Big Data, and HDF Server
High Performance Computing with R
What Do Computers Do? A computer system is
Deployment of Flows Loretta Auvil
Matlab.
SuperB and its computing requirements
Computer Application in Engineering Design
Programming Models for SimMillennium
Constructing a system with multiple computers or processors
Green IT CHAPTER 3: PROGRAMMATIC AND INSTITUTIONAL OPPORTUNITIES TO ENHANCE COMPUTER SCIENCE RESEARCH FOR SUSTAINABILITY.
NGS computation services: APIs and Parallel Jobs
NVIDIA Profiler’s Guide
Hadoop Clusters Tess Fulkerson.
Performance Analysis, Tools and Optimization
Anne Pratoomtong ECE734, Spring2002
Scientific Computing At Jefferson Lab
Development of the Nanoconfinement Science Gateway
Matlab as a Development Environment for FPGA Design
Summary Background Introduction in algorithms and applications
Parallel Computation of 2D Morse-Smale Complexes
Constructing a system with multiple computers or processors
Constructing a system with multiple computers or processors
Alternative Processor Panel Results 2008
Numerical Algorithms Quiz questions
Constructing a system with multiple computers or processors
Improving Decision Making and Managing Knowledge
Vrije Universiteit Amsterdam
Support for Adaptivity in ARMCI Using Migratable Objects
Grid and Cloud Computing Lecture 8
Presentation transcript:

Learn about MATLAB Engineers – not sales! Session 1: Registration 8:45 to 9:00 AM Presentation begins:  9:00 to 11:00 AM   Data Analysis and Visualization   Agenda: Learn how to visualize and analyze data, perform numerical computations, and develop algorithms. Live demonstrations and examples more effective in your coursework as well as in research. Students, faculties, and researchers who are new to MATLAB.   Highlights include: Accessing data from many sources Tools for iterative exploration, design, and problem solving Automating and capturing your work easily Sharing your results with others Building and deploying GUI-based applications     No prior MATLAB experience is needed. Experienced users learn tips and tricks Session 2: Registration 1:15 to 1:30 PM Presentation begins:  1:30 to 3:30 PM   Optimize and Accelerate Your Code   Agenda: Learn simple how to optimize your code to boost speed by orders of magnitude. Address pitfalls in code, explore the Profiler to find bottlenecks, and Parallel Computing Toolbox and Distributed Computing Server to solve computationally and data-intensive problems on GPUs, multicore computers and clusters.   Highlights include: Understanding vectorization and best coding practices in MATLAB Addressing bottlenecks in your programs Incorporating compiled languages, such as C, into your MATLAB applications Utilizing additional hardware, including multicore processors and GPUS, to improve performance  Scaling up to a computer cluster, grid environment or cloud Some prior experience is highly recommended for this session. Engineers – not sales! Tuesday 10/25/2016 – ITB Building Seating is limited – email ASAP ken.cleveland@mathworks.com with your choice of:       Session 1 only       Session 2 only       Both