Online Seminars

Recordings of most of our webinars can be found on SHARCNET youtube channel, http://youtube.sharcnet.ca .

General Interest Webinars

2021

• 2021/02/24 - Generating interactive visualizations with Plotly on Graham, James Desjardins, Abstract, slides
• 2021/02/10 - Using multiple GPUs for Machine Learning, Isaac Ye, Abstract, slides
• 2021/02/03 - Computing in arbitrary precision, Ge Baolai, Abstract, slides
• 2021/01/13 - Programming GPUs with Fortran, Pawel Pomorski, Abstract, slides

2020

• 2020/12/16 - Accelerate Python Analytics on GPUs with RAPIDS, Jinhui Qin, Abstract, slides
• 2020/12/02 - Practical Singularity, Paul Preney, Abstract, slides
• 2020/11/18 - NixOS: The second largest and the most up-to-date Linux distribution, Tyson Whitehead, Abstract, slides
• 2020/11/04 - Julia: Parallel computing revisited, Ge Baolai, Abstract, slides
• 2020/10/21 - Introduction to Git, Ed Armstrong, Abstract, slides
• 2020/10/14 - Preparing for RAC 2021 applications, Ge Baolai, Abstract, slides
• 2020/10/07 - Introduction to HPC Programming Language Chapel: Parallel Approaches, Jemmy Hu, Abstract, slides
• 2020/09/23 - Is my neural network too big to fit into GPU?, Weiguang Guan, Abstract, slides, Code
• 2020/09/09 - Options for Solving Jobs with Many Tasks, Doug Roberts, Abstract, slides
• 2020/08/12 - Bioinformatics in the terminal: Tips and tricks to make your life easier, Jose Sergio Hleap, Abstract, slides
• 2020/07/29 - How to Use C++ Parallel Algorithms in a Distributed Memory Setup (i.e. MPI), Armin Sobhani, Abstract, slides
• 2020/07/15 - Visualizing job usage on the Compute Canada systems with the ViewClust Python package, James Desjardins, Abstract, slides
• 2020/07/08 - Cython: A First Look, Tyler Collins, Abstract, slides
• 2020/04/27 - Collaborative Groups in CUDA, Pawel Pomorski, Abstract, slides
• 2020/04/08 - Using SSHFS to make CC storage more accessible, Mark Hahn, Abstract
• 2020/03/11 - Julia: A third perspective - parallel computing explained, Ge Baolai, Abstract, slides
• 2020/02/26 - How to run AI programs in Graham, Isaac Ye, Abstract, slides
• 2020/02/12 - New User Seminar, Part II, Sergey Mashchenko, Abstract, slides
• 2020/01/29 - Singularity 3.5, Paul Preney, Abstract, slides

2019

• 2019/12/18 - HPC Programming Language Chapel: Base Language Overview, Jemmy Hu, Abstract, slides
• 2019/12/04 - Docker, Ed Armstrong, Abstract
• 2019/11/27 - Julia: A second perspective, Ge Baolai, Abstract
• 2019/11/06 - Using Multiple GPUs in Tensorflow, Weiguang Guan, Abstract, slides
• 2019/10/23 - Leveraging Compiler Optimization Reports, Doug Roberts, Abstract
• 2019/10/09 - Introduction to scalable computing with Dask in Python, Jinhui Qin, Abstract
• 2019/09/26 - Using reduced numerical precision on Pascal, Volta and Turing GPUs, Pawel Pomorski, Abstract
• 2019/06/05 - Julia - A first perspective, Ed Armstrong, Abstract
• 2019/05/22 - New developments in OpenMP, Jemmy Hu, Abstract, slides
• 2019/05/08 - Pull your own data into ParaView, Weiguang Guan, Abstract
• 2019/04/24 - PRE and POST production on Graham, James Desjardins, Abstract
• 2019/04/10 - Exploring Octave package dataframe, Ge Baolai, Abstract, slides
• 2019/03/27 - Introduction to parallel programming with MPI and Python, Pawel Pomorski, Abstract, slides
• 2019/02/27 - Dipping into C++17 Parallel Algorithms with Intel's Parallel STL, Armin Sobhani, Abstract, slides, examples
• 2019/02/13 - What Happened To My Job?, Mark Hahn, Abstract
• 2019/01/30 - Best practices on Graham, Isaac Ye, Abstract* 2019/01/30 - Best practices on Graham, Isaac Ye, Abstract
• 2019/01/16 - The Monad Understanding Hurdle, Tyson Whitehead, Abstract

2018

• 2018/12/19 - Code profiling on Graham, Sergey Mashchenko, Abstract, slides
• 2018/12/05 - Using Pseudorandom Number Sequences in C++, Paul Preney, Abstract, slides
• 2018/11/21 - MySQL Part 2: Relations and Joins, Edward Armstrong, Abstract, slides
• 2018/11/07 - Using MATLAB effectively on Graham and Cedar, Jemmy Hu, Abstract, slides
• 2018/10/24 - Stock Prediction Using Recurrent Neural Network, Weiguang Guan, Abstract, slides
• 2018/10/10 - Understand (and potentially reduce) job wait times, James Desjardins, Abstract, slides
• 2018/09/26 - The Benefits of GLOST for Many Jobs, Doug Roberts, Abstract
• 2018/09/12 - Concurrent File I/O by Multiple Processes, Ge Baolai, Abstract, slides
• 2018/08/15 - Harnessing the Power of Heterogeneous Computing using Boost.Compute + OpenCL, Armin Sobhani, Abstract, slides
• 2018/08/01 - Introduction to MySQL on Graham, Ed Armstrong, Abstract, slides
• 2018/07/04 - Debugging on Graham with DDT, Sergey Mashchenko, Abstract, slides
• 2018/06/20 - Fundamentals of working at the command line at Graham, Isaac Ye, Abstract, slides

2018/05/09 - Summer School preview, Tyson Whitehead

From May 28th to June 1st SHARCNET will run its annual Summer School on Advanced Research Computing, this time at Western University. This summer school will be our largest yet: for the first time we will have three separate full streams, with SHARCNET staff providing instructions on 13 different courses ranging from traditional HPC topics (2-days in-depth courses on MPI and CUDA) to courses on machine learning, singularity and cloud computing. Each course is 1-2 days long, with plenty of hands on time. This webinar will briefly describe the courses which will be offered at the Summer School. slides

• 2018/04/25 - All about job wait times in the Graham queue, James Desjardins, Abstract, slides
• 2018/04/11 - Improving your Python programs with NumPy and SciPy, Pawel Pomorski, Abstract, slides
• 2018/03/28 - Using Computational Chemistry software effectively on Graham, Jemmy Hu, Abstract, slides
• 2018/03/14 - Using SSH for Good, not Evil, Mark Hahn, Abstract, slides
• 2018/02/28 - Visual Studio Code – Your Next Coding Companion for Advanced Research Computing, Armin Sobhani, Abstract, slides
• 2018/02/14 - Singularity, Paul Preney, Abstract, slides
• 2018/01/31 - Deploying a Full Stack Web Solution on the Cloud for Cluster Access, Ed Armstrong, Abstract, slides
• 2018/01/17 - Intro to Intel Performance Tools, Doug Roberts, Abstract, slides

2017

• 2017/12/06 - Introduction to Eclipse for debugging – Part I, Ge Baolai, Abstract
• 2017/11/22 - Serial farming on Graham, Sergey Mashchenko, Abstract, slides
• 2017/11/08 - Introduction to LINUX/SHELL programming in SHARCNET, Isaac Ye, Abstract, slides
• 2017/10/25 - Machine Learning using Jupyter Notebooks on Graham, Jose Nandez, Abstract, slides, demo code
• 2017/10/11 - Linear Algebra on GPU, Pawel Pomorski, Abstract, slides
• 2017/09/27 - Introduction to SHARCNET Cloud, Mohamed Elsakhawy, Abstract, slides
• 2017/09/20 - Training Neural Networks with hundreds of GPUs on Graham and Cedar, Fei Mao, Abstract, slides
• 2017/09/13 - Partitions and scheduling, running jobs effectively on Graham and Cedar, Kamil Marcinkowski, Abstract, slides
• 2017/08/16 - Packaging with Nix, Tyson Whitehead, Abstract, slides
• 2017/08/02 - Intel MPI Library Cluster Edition on Graham, Doug Roberts, Abstract, slides
• 2017/07/19 - How jobs are scheduled to run on Graham and Cedar, James Desjardins, Abstract, slides
• 2017/07/05 - Train models to recognize hand-written digits using Tensorflow, Weiguang Guan, Abstract, slides, code and data
• 2017/06/21 - What’s new and exciting about Graham’s GPUs, Sergey Mashchenko, Abstract, slides
• 2017/05/10 - OpenMP 4.x: New features and Protocols, Jemmy Hu, Abstract, slides
• 2017/04/26 - Automating Software Build Process using CMake – Part II, Armin Sobhani, Abstract
• 2017/04/19 - Modern Fortran: Concurrency and Parallelism, Ge Baolai, Abstract, slides
• 2017/03/15 - High Performance Computing with Python, Pawel Pomorski, Abstract, slides
• 2017/03/01 - Machine Learning with Spark at SHARCNET, Jose Nandez, Abstract, slides
• 2017/02/15 - Git and SHARCNET (part 2), Tyson Whitehead, Abstract
• 2017/02/01 - Deep Learning on SHARCNET: Best Practices, Fei Mao, Abstract, slides
• 2017/01/18 - Navigating the Research Computing Resource Renewals Coming in 2017, James Desjardins, Abstract, slides
• 2017/01/04 - Introduction to ParaView, Weiguang Guan, Abstract, slides

2016

• 2016/12/07 - Defensive Programming : Best Practices, Ed Armstrong, Abstract, slides
• 2016/11/09 - Debugging CUDA programs, Sergey Mashchenko, Abstract, slides
• 2016/10/26 - Introduction to Python, Isaac Ye, Abstract, slides
• 2016/10/12 - What Happened to My Job? Cluster Scheduling In Detail, Mark Hahn, Abstract, slides
• 2016/09/28 - Introduction to The Unix Shell – Automating Your Work, Ge Baolai, Abstract, slides
• 2016/09/14 - Automating Software Build Process using CMake, Armin Sobhani, Abstract, slides
• 2016/08/17 - Introduction to Jupyter, Paul Preney, Abstract, slides
• 2016/08/03 - Introduction to MPI – Part III, Pawel Pomorski, Abstract, slides
• 2016/07/20 - Hybrid MPI and OpenMP Parallel Programming, Jemmy Hu, Abstract, slides
• 2016/06/08 - Introduction to Apache Spark on SHARCNET, Jose Nandez, Abstract, slides
• 2016/05/11 - Git and SHARCNET, Tyson Whitehead, Abstract
• 2016/04/27 - Deep Learning at SHARCNET: Tools you can use, Fei Mao, Abstract, slides
• 2016/04/13 - Quick tips for getting the most out of SHARCNET, James Desjardins, Abstract, slides
• 2016/03/30 - How to get started with OpenFOAM at SHARCNET, Isaac Ye, Abstract, slides
• 2016/03/16 - Debugging OpenMP programs, Sergey Mashchenko, Abstract, slides, code examples
• 2016/03/02 - Raphaël – a vector graphics library for web development, Weiguang Guan, Abstract, slides
• 2016/02/17 - Parallel and high performance computing with R, Ge Baolai, Abstract, slides
• 2016/02/03 - UNIX shell expansion: proper use and advanced forms, Tyson Whitehead, Abstract, slides
• 2016/01/20 - Introduction to OpenMP Parallel Programming, Jemmy Hu, Abstract, slides
• 2016/01/06 - Automating Software Build Process using CMake, Armin Sobhani, Abstract, slides

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. slides

• 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. slides

• 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
Recently SHARCNET acquired a powerful MPI profiler made by Allinea - MAP. It now comes bundled up with their other popular product, parallel debugger DDT, and is installed on our cluster orca. This tutorial will give a brief overview of the software, with a live demonstration of the profiling a realistic MPI code. slides

• 2014/01/27 - New User Seminar 2014-Jan-27, Baolai Ge
• 2014/01/15 - Webinar 2015 Using parallel I/O in SHARCNET, Alex Razoumov, slides

2013

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. Slides as PDF file

• 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

New User Seminars

• New User Seminar; PDF file (may not be up to date)
• Introduction to Compute Canada (a faculty edition); PDF file