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[farmshare-discuss] ICME and RC now offer programming and HPC short courses/workshops

Alex Chekholko chekh at stanford.edu
Thu Dec 6 12:44:46 PST 2012


----- Forwarded Message -----
Sent: Wednesday, December 5, 2012 7:02:52 PM
Subject: ICME and RC now offer programming and HPC short courses/workshops

Dear all,

ICME and the Research Computing (RC) group at Stanford are now working 
together to offer regular hands-on programming and HPC technology 
workshops throughout the academic year.

The initial offerings include quarterly MATLAB, Python, GPU computing 
and CUDA courses and workshops (see below). Both the MATLAB and Python 
courses are offered as 1-unit Stanford courses. All offerings are at the 
start of the quarter to allow for immediate use of the learned material.
Note that all courses will also be taped and offered online as a 
permanent resource.


Additional workshops covering MapReduce, R, MPI/OpenMP, introduction to 
Linux, and an Introduction to Computing Resources at Stanford are 
planned for later in the year.


** Please take a few seconds to let us know what other topics will be of 
interest to you, your students (if you are faculty) or to support your 
courses by filling out a super quick survey at 
http://www.surveymonkey.com/s/VVVTMQF



Cheers, Margot Gerritsen (ICME) Ruth Marinshaw (Research Computing)


******************************************************************************************************************* 



ICME/RC OFFERING FOR WINTER QUARTER 2012-2013 (all of these courses will 
also be offered in the Spring)

1. Introduction to Matlab (CME 192) : This 1 unit credit short course 
runs for the first three weeks of the quarter and is offered each 
quarter during the academic year. It is highly recommended for students 
with no prior programming experience who are expected to use MATLAB in 
math, science, or engineering courses. It will consist of interactive 
lectures and application-based assignments. The goal of the short course 
is to make students fluent in MATLAB and to provide familiarity with its 
wide array of features. The course covers an introduction of basic 
programming concepts, data structures, and control/flow; and an 
introduction to scientific computing in MATLAB, scripts, functions, 
visualization, simulation, efficient algorithm implementation, 
toolboxes, and more.
When and Where : 1/9/2013 – 1/23/2013, M/W 2:15 – 4:05 PM, 380-380X. 
Auditors are welcome to participate; should there be insufficient 
seating, priority will go to students registered for credit hours.

2. Introduction to Scientific Python (CME 193) : This 1 unit credit 
short course runs for the first three weeks of the quarter and is 
offered each quarter during the academic year. It is recommended for 
students who want to use Python in math, science, or engineering courses 
and for students who want to learn the basics of Python programming. The 
goal of the short course is to familiarize students with Python's tools 
for scientific computing. Lectures will be interactive with a focus on 
learning by example, and assignments will be application-driven. No 
prior programming experience is needed. Topics covered include control 
flow, basic data structures, File I/O, and an introduction to NumPy/SciPy.
When and Where: 1/7/2013 – 1/24/2013, Tu/Th 3:15 – 5:05 PM, Huang 
240-101. Auditors are welcome to participate; should there be 
insufficient seating, priority will go to students registered for credit 
hours.

3. GPU Computing 101 : This workshop, led by Jonathan Bentz of NVIDIA, 
will address topics such as why accelerated computing with GPUs is 
important to sustaining and advancing the state of the art in scientific 
and research computing, both in terms of performance and energy 
efficiency. The workshop will survey the broad range of GPU accelerated 
applications across all domains of scientific research and engineering. 
Participants will learn how to program GPUs via the use of libraries, 
OpenACC compiler directives, and CUDA programming. The workshop will 
incorporate hands-on exercises so that the participants can become more 
familiar with GPU programming techniques. This workshop is especially 
recommended for: 1) domain scientists to realize the power of GPU 
computing by taking advantage of the GPU enabled applications, 2) HPC/IT 
staff who want to enable scientists and developers with parallelizing 
compilers and 3) developers who want hands-on experience how to program 
GPUs in any of their native languages (C, Fortran, Python etc.)
When and where : Offered in conjunction with IT Services’ Friday Tech 
Briefings, this workshop will be held on Friday, January 11, 1-5 pm, in 
Turing Auditorium. Attendees who want to follow along with the hands-on 
exercises should bring a laptop with an SSH client installed and 
configured.

4. CUDA: Offered as a follow-on to the GPU Computing 101 session, this 
workshop, led by an NVIDIA developer, The workshop will incorporate 
hands-on exercises so that the participants can become more familiar 
with GPU programming techniques.
When and where : Offered in conjunction with IT Services’ Friday Tech 
Briefings, this workshop will be held on Friday, January 18, 1-5 pm, in 
Turing Auditorium. Attendees who want to follow along with the hands-on 
exercises should bring a laptop with an SSH client installed and 
configured.
-- 
Margot Gerritsen

Director, Institute for Computational & Mathematical Engineering 
Stanford University margot.gerritsen at stanford.edu



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