October 2015
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Using Hoffman2 Cluster

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Introduction to SAS

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Profiling – Code clinic session

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Parallel Computing using MPI

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Introduction to Stata

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Scientific Computing using PETSc

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Python for High Performance Computing – Part 1

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Introduction to SPSS

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Introduction to Cuda

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National Leadership Class Computing Resources and Opportunities for UCLA Researchers

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Python for High Performance Computing – Part 2

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Introduction to R

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This session is a general introduction to how to use UCLA Hoffman2 Cluster. The objective is to familiarize current and potential cluster users with the Hoffman2 Cluster, so they can make the best use of UCLA computational resources. The following topics will be covered: 1. How to access and login to the Hoffman2 Cluster, primarily in terminal/command-line mode. 2. Exploration of how to run various computational tasks on or from the Hoffman2 Cluster, illustrated by hands-on example transcripts. 3. A…

Find out more »SAS is a powerful statistical package that runs on many platforms, including Windows and Unix. This class is designed for people who are just getting started using SAS. The students in the class will have a hands-on experience using SAS for statistics, graphics, and data management. Non-UCLA researchers are allowed to sign up and attend. RSVP Here.

Find out more »The purpose of this session is to describe few basic profiling techniques and help researchers in gaining more insight into how well their application code runs on Hoffman2 or other computer systems. In particular the focus is on: Profiling techniques that are available on Hoffman2. Hands-on exercises using an example code – bring your own software. Prerequisite: User account on hoffman2 (apply here if you don’t have one) and your software on Hoffman2. Laptop requirements: Bring your own laptop to…

Find out more »MPI (message passing interface) is the de facto standard for distributed-memory parallel scientific computing. While the entire MPI API is quite extensive, this class will cover a number of important ones commonly used in practice. This class is useful for those who plan to start writing MPI code, and also for those who would like to know how MPI works in order to operate an existing MPI code. Sign up here.

Find out more »Stata is a powerful and yet easy-to-use statistical package that runs on Windows, Macintosh and Unix platforms. This class is designed for people who are just getting started using Stata. The students in the class will have a hands-on experience using Stata for statistics, graphics and data management. Non-UCLA researchers are allowed to sign up and attend. RSVP here.

Find out more »The PETSc library contains a number of reusable data structures and solvers for linear and nonlinear systems of equations that can greatly simplify the programming work of scientific computing. While it is possible to code everything “from scratch” using MPI and C/C++/Fortran, some may find code written reusing PETSc’s data structures are easier to maintain and extend in the long term. This class will first discuss a number of common scenarios in scientific computing (such as solving a partial differential…

Find out more »New location: 5628 Math Sciences Building New time: 2:30pm-5pm, October 19 Python, originally developed as a general purpose programming language, has gained its popularity in the scientific community in recently years owning to its elegant and easy- to-understand syntax and powerful libraries. Python fully supports both functional and object-oriented programming styles. This class will present a number useful features of Python in the context of scientific computing, and introduce a number of supporting packages, including numpy for array-based computations and…

Find out more »SPSS is a very easy-to-use statistical package that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just starting to use SPSS. The students in the class will have a hands-on experience using SPSS for doing statistics, graphics, and data management. Non-UCLA researchers are allowed to sign up and attend. RSVP here.

Find out more »Graphics Processing Units (or GPUs), an integral part of most of the computer systems, are well known for their potential for high performance numeric computations. Although few efforts have been made in the past to use these devices for general computing, the recent emergence of high level programming languages through CUDA has really made it possible to use GPUs without going through a steep learning curve. The objective of the class is to provide an introduction to CUDA. This session…

Find out more »The Department of Energy, National Science Foundation, and the National Aeronautical Space Agency support an ecosystem of “leadership class” computing facilities housing some of the world’s most advanced supercomputers and high-end visualization and data analysis resources. These facilities provide “free” computing cycles and storage to researchers from academia. Access to these resources is obtained through an application process that is based on the merit of the research objectives, and demonstration of the efficacy and parallel scalability of the software to…

Find out more »New time: 2-4pm, October 26 New Location: 5628 Math Sciences Building Python, originally developed as a general purpose programming language, has gained its popularity in the scientific community in recently years owning to its elegant and easy- to-understand syntax and powerful libraries. Python fully supports both functional and object-oriented programming styles. This class will present a number useful features of Python in the context of scientific computing, and introduce a number of supporting packages, including numpy for array-based computations and…

Find out more »R is a powerful statistical package that runs on Windows, Macintosh and Unix platforms. This class is designed for people who are just getting started using R. The students in the class will have a hands-on experience using R for statistics, graphics and data management. Non-UCLA researchers are allowed to sign up and attend. RSVP here.

Find out more »