From Documentation
- New! SHARCNET youtube channel: http://youtube.sharcnet.ca . We are in the process of editing our webinar recordings and uploading them to youtube. All new webinars recordings will go straight to youtube. We will update the links below accordingly.
Contents
Recordings
2016
2015
- 2015/12/09 - Parallel Design Patterns, Edward Armstrong, Abstract, slides
- 2015/11/25 - Introduction to MPI – Part II, Pawel Pomorski, Abstract, slides
- 2015/11/11 - Introduction to MPI – Part I, Paul Preney, Abstract, slides
- 2015/10/28 - Fundamentals of working at the command line at SHARCNET, Hugh Merz, Abstract, slides
- 2015/10/14 - CUDA Profiling and Tuning, Fei Mao, Abstract, slides
- 2015/09/30 - Profiling function vectorization in Matlab/Octave, James Desjardins, Abstract
- 2015/09/16 - Scientific Visualization with ParaView, Weiguang Guan, Abstract, slides
- 2015/08/19 - Introduction to Parallel I/O, Isaac Ye, Abstract, slides
- 2015/08/05 - Parallel programming without MPI – Using coarrays in Fortran, Ge Baolai, Abstract, slides
- 2015/07/22 - Debugging and profiling of MPI programs, Sergey Mashchenko, Abstract, slides, code examples
- 2015/07/08 - Hybrid MPI and OpenMP Parallel Programming, Jemmy Hu, Abstract, slides
- 2015/06/24 - Programming with Wt - a C++ library for developing stateful and highly interactive web applications, Armin Sohani, Abstract, slides
- 2015/06/10 - Get the most out of SharcNET, Mark Hahn, Abstract, slides
- 2015/05/14 - Exploring a new approach to package management, Tyson Whitehead, Abstract, slides
2015/04/29 - High Performance Computing with Python, Pawel Pomorski |
---|
Python has numerous advantages over traditional compiled languages like C and Fortran, and it is seeing increasing adoption among the scientific community. However, despite its advantages, there are challenges associated with using Python in a High Performance Computing (HPC) environment. First, a “vanilla” Python program is generally slower than an analogous compiled language program. Also, Python is relatively new to the HPC field, and many scientific programmers may not be aware of its parallel computing capabilities. This talk will discuss various strategies to make a serial Python code faster, for example using libraries like NumPy, or tools like Cython which compile Python code. The talk will also discuss the available tools for running Python in parallel, focusing on the mpi4py module which implements MPI (Message Passing Interface) in Python. |
- 2015/04/15 - An Update on MATLAB at SHARCNET, Jemmy Hu, Abstract, slides
- 2015/04/01 - A brief look at numerical libraries: The tools you can use, Ge Baolai, Abstract, slides
- 2015/03/18 - Programming, best practices, Ed Armstrong, Abstract, slides
- 2015/03/04 - The Relevance of OpenCL to HPC, Paul Preney, Abstract, slides
- 2015/02/18 - Serial and parallel farming from A to Z, Sergey Mashchenko, Abstract, slides
- 2015/02/04 - Deep Learning on SHARCNET: From CPU to GPU cluster, Fei Mao, Abstract, slides
- 2015/01/21 - New User Seminar - Part 2, Hugh Merz, Abstract, slides
- 2015/01/07 - SHARCNet file management, James Desjardins, Abstract, slides
2014
- 2014/12/10 - Programming with VTK - a high-level visualization library, Weiguang Guan, Abstract, slides
- 2014/11/26 - The SHARCNET Desktop, Tyson Whitehead, Abstract, slides
2014/11/12 - Linear Algebra on GPU, Pawel Pomorski |
---|
This seminar will provide an overview of how one can efficiently solve linear algebra problems using GPGPU (General Purpose Graphics Processing Unit) hardware and the associated CUDA software framework. The basic issues involved in developing efficient code for this type of computation will be discussed, followed by a demonstration of how to use three popular libraries relevant to the problem: CUBLAS, CULA and MAGMA. |
- 2014/10/29 - Is the Intel Xeon Phi right for me?, Fei Mao, Abstract, slides
- 2014/10/15 - CUDA Basics and how to, Isaac Ye, Abstract, slides
- 2014/10/01 - An Introduction to Java Threads, Ed Armstrong, Abstract, slides
- 2014/09/17 - Advanced Message Passing in MPI: Using MPI Datatypes with Opaque C++ Types, Paul Preney, Abstract, slides
- 2014/06/18 - Debugging at SHARCNET, Hugh Merz, Abstract, slides
- 2014/05/21 - Running MATLAB in SHARCNET, Jemmy Hu, Abstract, slides
- 2014/04/16 - My code doesn’t crash -- why should I still use Valgrind?, Tyson Whitehead, Abstract, slides
- 2014/03/19 - Managing your files effectively at SHARCNET with SVN, Baolai Ge, Abstract, slides
- 2014/02/19 - Profiling MPI codes with Allinea's MAP, Sergey Mashchenko, Abstract, slides
- 2014/01/27 - New User Seminar 2014-Jan-27, Baolai Ge
- 2014/01/15 - Using parallel I/O in SHARCNET, Alex Razoumov, Abstract, slides
2013/12/18 - Why Would I Use GPUs?, Pawel Pomorski |
---|
GPUs (Graphics Processing Units) can provide a significant speedup for certain types of scientific computations. This talk will discuss which programs can benefit from this speedup, and how in certain cases it can be obtained without much effort using already existing packages and libraries. Simulation packages already accelerated for the GPU will be discussed, with focus on NAMD molecular dynamics package as a useful example. The use of GPU-enabled numerical libraries useful for common problems will be discussed. The use of these techniques will be demonstrated with example runs on SHARCNET’s new GPU cluster. While not the focus of this talk, a brief overview of available programming approaches for GPUs will be also provided. |
2013
- 2013/11/20 - Introduction to Linux, Isaac Ye, Abstract, slides
- 2013/05/01 - Quick-n-dirty Ways to Run Serial Code Faster, in Parallel, Sergey Mashchenko, slides
- 2013/02/27 - SHARCNET Software Support Updates, Jemmy Hu
- 2013/01/23 - Bash Shell Scripting: Making Linux Work for You, Isaac Ye, slides
2012
- 2012/11/21 - New User Seminar - Part Deux, Hugh Merz, slides
- 2012/10/24 - An Introduction to Valgrind, Tyson Whitehead
- 2012/09/26 - Why Would I Use GPUs?, Pawel Pomorski
- 2012/04/04 - Optimizing Tools for Development and Execution of Programs, Nick Chepurniy
2011
- 2011/11/23 - Backing Up Source Files and Documents with Subversion, Baolai Ge
- 2011/11/02 - Visualizing Data with Paraview, Alex Razoumov
- 2011/10/12 - MATLAB Parallel Computing Toolbox on SHARCNET, Jemmy Hu
- 2011/09/21 - Linear Algebra on the GPU, Pawel Pomorski
Summer School 2012 Pre-school Talks (recordings)
- Introduction to the SHARCNET Environment - slides
- This talk provides a brief literacy-based overview of SHARCNET: available hardware and software resources, our web portal, where to look for help, how to log in to systems, compile code, run, submit and manage your jobs and finally a quick summary of our visualization tools.
- Introduction to Linux - slides
- This seminar serves as an introduction to Linux, the UNIX-like operating system that runs on all SHARCNET systems, intended for users who have little or no experience with UNIX or Linux. We will consider essential materials related to coping with the Linux command-line environment, necessary for successful use of the SHARCNET envrionment, including basic commands for file/directory management, text editors, etc.
- Appraising Your Programming Skills - slides
- Much of the Summer School programme is focused on programming. While we always take steps to inform attendees that we are primarily covering the parallel side of the programming equation, and thus assume some experience writing serial code, we have found some people underestimate what is meant by "some level of serial programming experience" which can present barriers. This talk will survey basic language concepts that are considered "essential" to serial programming, and thus will underpin any expansion into parallelism (e.g. file handling, pointers and memory management, etc.). The hope is this will provide someone with a better understanding of their strengths and weaknesses while there is still a little time to brush up before the summer school commences.
- HPC Architecture Overview - slides
- High performance computing (HPC) is an umbrella term that covers a variety of standard approaches. It is not a magic bullet that can take any program and make it 10x times faster. Not all HPC hardware solutions are applicable to a given problem, and not all problems are susceptible to an arbitrary HPC solution. Learn what the standard approaches are and what their strengths and weaknesses are.
See Also
- New User Seminar (slides)