SUMMARY

• Scratch purging policy on Niagara starts July 16.
• Niagara takes it place at the number 53 spot in the top500.
• Preliminary fall training and education schedule

Details can be found below and are also available on the SciNet education website courses.scinet.utoronto.ca and the SciNet wiki docs.scinet.utoronto.ca.

SYSTEM NEWS

• Scratch purging policy on Niagara starts July 16.
• Niagara takes it place at the number 53 spot in the top500.
• Burst Buffer, a fast storage tier between the general parallel file system and system memory, is sto;; available for groups with high I/O needs, upon request. See https://docs.scinet.utoronto.ca/index.php/Burst_Buffer

EVENTS COMING UP

Unless stated otherwise, all events listed below take place at the SciNet Teaching Room at our offices on the eleventh floor of the MaRS West Tower, suite 1140A (661 University Avenue, Toronto ON M5G 1M1).

Most events will be recorded and some are broadcast, but only some of the courses can be taken remotely for SciNet certificate credits, as indicated below.

Registration for SciNet courses is done by logging into https://support.scinet.utoronto.ca/education with your SciNet account.

More SciNet courses will be announced at the end of the summer.

• INTRO TO SCINET/NIAGARA Wednesday Sept 23, 2018, 10:00 am – 11:30 am SciNet Boardroom (suite 1140, 661 University Avenue, Toronto ON M5G 1M1).

  This is a class of approximately 60-90 minutes to introduce SciNet and the new supercomputer Niagara and teach you how to use Niagara.

  Participation counts towards the SciNet HPC Certificate.

  For more information and (free) registration, go to https://support.scinet.utoronto.ca/education/go.php/396/index.php

• COMPUTE ONTARIO SUMMER SCHOOL EAST June 11 – 15, University of Toronto, St. George Campus New College, University of Toronto, 40 Willcocks St., Toronto, M5S 1C6

  The Compute Ontario Summer School on Scientific and High Performance Computing is an annual educational event for graduate/undergraduate students, postdocs and researchers to learn and share knowledge and experience in high performance and technical computing on modern HPC platforms.

  As in previous years, the Summer School on High Performance Computing 2014 will have three installments:

  “West” May 28 – June 1 Western University, London “Central” June 11 – June 15 University of Toronto, Toronto “East” July 30 – August 3 Queen’s University, Kingston

  Registration for the school in London and Kingston is at https://www.sharcnet.ca/summerschool/2018, while registration for the summer school in Toronto is at https://support.scinet.utoronto.ca/education/go.php/368/index.php

  The Toronto summer school hosted by SciNet will have the following three streams: Stream 1: High Performance computing; Stream 2: Data Science; Stream 3: Biomedical. Instructors are from SciNet, SHARCNET, and CAMH.

  This event will not be held at the SciNet Offices, rather it will be at New College on the Downtown St. George Campus of the University of Toronto.

  Parts of this event count towards the SciNet Certificates.

  More details and registration can be found at https://support.scinet.utoronto.ca/education/go.php/368/index.php

• ADVANCED PARALLEL SCIENTIFIC COMPUTING Mondays and Wednesdays, 1 pm – 2pm Four weeks starting Sept 11. Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  In this course, we will be exploring advanced examples of parallel computing in scientific research. Topics include HPC tools, CUDA, molecular dynamics, Monte Carlo and random number generation, smoothed particle hydrodynamics, N-body simulations and computational fluid dynamics.

  The format of the course will be two lectures of one hour, for four consecutive weeks. The participants are expected to choose a project that involves analyzing and improving a parallel research code from one of the topic presented in the lectures, and to present their findings two weeks after the end of the course.

  The lectures of this course will be broadcast and recorded. Remote participation for credit may be possible upon request.

  Familiarity with parallel programming (MPI/OpenMP/CUDA) in a compiled language (C/C++/Fortran) is a prerequisite of this course.

  This class counts as 12 credit-hours towards the SciNet HPC Certificate. It can also be taken as a modular course by Physics grad students and as a mini course by Astrophysics students.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/317/index.php

• INTRODUCTION TO CLINICAL BIOSTATISTICS (MSC1090) Tuesdays and Thursday, 11 am – 12 noon Twelve weeks starting Sept 12.

  In this course data analysis techniques utilizing the R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing. The goal of this course is to prepare graduate students to perform scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data. Topics include: R programming, version control, automation, modular programming and scientific visualization.

  Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI. This course is part of the IMS graduate program and to be taught at the UofT St. George campus (i.e., not in the SciNet classroom).

  Unfortunately, this course is full, but we are exploring the possibility of giving it again in the Winter term.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/324/index.php

• INTRO TO SCINET Sept 13, 10:00 am – 11:30 am

  In about 90 minutes, you will learn how to use the SciNet systems. Experienced users may still pick up some valuable pointers.

  Participation counts towards the SciNet HPC Certificate.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/329/index.php

• SCINET USER GROUP MEETING Sept 13, 12:00 noon – 1:00 pm Boardroom (MaRS West Tower, 661 University Ave, Toronto, suite 1140)

  Pizza, user discussion, and a tech talk: “ChIP-Seq analysis of the Interactive Bromodomain 1 protein (Ibd1) in Tetrahymena thermophila”, by Alejandro Saettone (Ryerson University)

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/301/index.php

• INTRODUCTION TO NEURAL NETWORK PROGRAMMING Sept 25, 10:00 am – 3:00 pm Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  This workshop will introduce neural network programming concepts, theory, and techniques. The level of the material will be introductory, intended for those with no experience with neural networks. The programming language will be Python 2.7; experience with Python programming will be assumed. The Keras neural network framework, with a Theano back end, will be used for more-advanced programming; no experience with Keras or Theano will be expected. Students should come with the following Python packages installed on their laptops: numpy, matplotlib, scikit-learn, theano (version 0.9.0 or greater), keras.

  Participation counts towards the SciNet Data Science Certificate.

  You can also view this event’s broadcast, but this would not count towards the certificate.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/338/index.php

• INTRODUCTION TO THE LINUX SHELL Sept 27, 10:00 am – 12:00 noon Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  Learn the basics of how to use the unix shell in two hours. Very useful for new users of SciNet that have little or no experience with unix or linux.

  Participation counts towards the SciNet Scientific Computing Certificate.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/330/index.php

• ADVANCED NEURAL NETWORKS Mondays from 11:00 am to 12:00 noon Four weeks starting Oct 2. Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  This class will review advanced neural network programming theory and architectures. The level of the material will not be introductory, experience with neural networks will be assumed. This class is intended to continue the material covered in “Introduction to Neural Network Programming” (see above).

  Participation counts towards the SciNet Data Science Certificate.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/325/index.php

• INTRODUCTION TO PROGRAMMING Tuesdays and Thursdays, 1:00 pm – 2:00 pm Four weeks starting Oct 10. Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  New to programming? Learn the basics of programming using python in eight one-hour sessions over the course of four weeks. Sessions will consist of a mix of lectures and hands-on exercises.

  Participation counts towards the SciNet Scientific Computing Certificate.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/328/index.php

• ADVANCED SHELL PROGRAMMING Oct 25, 1:00 pm – 4:00 pm Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  Learn how to write bash script, use environment variables, how to control process, and much more. Requires some linux basic command line experience.

  Participation counts towards the SciNet Scientific Computing Certificate.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/331/index.php

• INTRO TO SCIENTIFIC COMPUTING WITH PYTHON Tuesdays and Thursdays, 1:00 pm – 2:00 pm Four weeks, starting Nov 7, 2017 Teaching Room 1140A (MaRS West Tower, 661 University Ave, Toronto)

  Learn about research computing even with little programming experience. Covers programming in python, best practices and visualization. Some experience with python is required. Four home work sets will be the basic of the evaluation.

  Participation counts towards the SciNet Scientific Computing Certificate.

  The lectures of this course will be broadcast and recorded. Remote participation for credit may be possible upon request.

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/327/index.php

• SCIENTIFIC COMPUTING FOR PHYSICISTS (PHY1610) Winter 2018

  This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, …).

  For sign up and more information, see https://support.scinet.utoronto.ca/education/go.php/326/index.php