Computational Science Education Publications by SciNet

January 16, 2019 in blog, blog-general, for_educators, for_press, for_researchers, frontpage, news, Uncategorized

This year starts with the publication of three papers by SciNet analysts in the Journal of Computational Science Education that are a reflection of SciNet’s ten years of training and educating academic researchers in the practical and scalable use of high performance computing.

  1. Bridging the Educational Gap between Emerging and Established Scientific Computing Disciplines
    Marcelo Ponce, Erik Spence, Ramses van Zon, and Daniel Gruner, Journal of Computational Science Education Vol 10 (1) 4-11 (2019)

    In this paper, we describe our experience in developing curriculum courses aimed at graduate students in emerging computational fields, including biology and medical science. We focus primarily on computational data analysis and statistical analysis, while at the same time teaching students best practices in coding and software development. Our approach combines a theoretical background and practical applications of concepts. The outcomes and feedback we have obtained so far have revealed several issues: students in these particular areas lack instruction like this although they would tremendously benefit from it; we have detected several weaknesses in the formation of students, in particular in the statistical foundations but also in analytical thinking skills. We present here the tools, techniques and methodology we employ while teaching and developing this type of courses. We also show several outcomes from this initiative, including potential pathways for fruitful multi- disciplinary collaboration.

  2. Scientific Computing, High-Performance Computing and Data Science in Higher Education
    Marcelo Ponce, Erik Spence, Ramses van Zon, and Daniel Gruner, Journal of Computational Science Education Vol 10 (1), 24-31 (2019)

    We present an overview of current academic curricula for Scientific Computing, High-Performance Computing and Data Science. After a survey of current academic and non-academic programs across the globe, we focus on Canadian programs and specifically on the education program of the SciNet HPC Consortium, using its detailed enrollment and course statistics for the past six to seven years. Not only do these data display a steady and rapid increase in the demand for research-computing instruction, they also show a clear shift from traditional (high performance) computing to data- oriented methods. It is argued that this growing demand warrants specialized research computing degrees.

  3. Trends in Scientific Computing Training Delivered by a High-Performance Computing Center
    Ramses van Zon, Marcelo Ponce, Erik Spence, and Daniel Gruner, Journal of Computational Science Education Vol 10 (1), 53-60 (2019)

    We analyze the changes in the training and educational efforts of the SciNet HPC Consortium, a Canadian academic High Performance Computing center, in the areas of Scientific Computing and High-Performance Computing, over the last six years. Initially, SciNet offered isolated training events on how to use HPC systems and write parallel code, but the training program now consists of a broad range of workshops and courses that users can take toward certificates in scientific computing, data science, or high-performance computing. Using data on enrollment, attendence, and certificate numbers from SciNet’s education website, used by almost 1800 users so far, we extract trends on the growth, demand, and breadth of SciNet’s training program. Among the results are a steady overall growth, a sharp and steady increase in the demand for data science training, and a wider participation of ‘non-traditional’ computing disciplines, which has motivated an increasingly broad spectrum of training offerings. Of interest is also that many of the training initiatives have evolved into courses that can be taken as part of the graduate curriculum at the University of Toronto.

We also recently gave a webinar on these topics.

Other publications by SciNet people can be found at here.

SciNet’s webinar on “Trends and Strategies in Advanced Research Computing Education”

January 16, 2019 in for_educators, for_press, in_the_news, news

SciNet was invited to present our latest findings (see about “Trends and Strategies in Advanced Research Computing Education” in a SIGHPC Education webinar.

This webinar was based on our recent publications:

Trends in Demand, Growth, and Breadth in Scientific Computing Training Delivered by a High-Performance Computing Center,
Journal of Computational Science Education vol 10(1) (2019).
R.Van Zon, M.Ponce, E.Spence and D.Gruner
Presented at the Fifth Workshop on Best Practices for Enhancing HPC Training and Education (BPHTE18) @ SC18
Bridging the Educational Gap between Emerging and Established Scientific Computing Disciplines,
Journal of Computational Science Education, vol 10(1) (2019).
M.Ponce, E.Spence, R.Van Zon and D.Gruner
Presented at the Workshop on Strategies for Enhancing HPC Education and Training (SEHET18) @ PEARC18

Scientific Computing, High-Performance Computing and Data Science in Higher Education,
Journal of Computational Science Education, vol 10(1) (2019).
arXiv version (2016).
M.Ponce, E.Spence, D.Gruner and R.Van Zon
Presented at the Workshop on Strategies for Enhancing HPC Education and Training (SEHET18) @ PEARC18

2019 International Summer School on HPC Challenges in Computational Sciences, Japan, July 7-12

December 7, 2018 in blog, for_educators, for_press, for_researchers, for_users, frontpage, news

Graduate students and postdoctoral scholars from institutions in Canada, Europe, Japan and the United States are invited to apply for the tenth International Summer School on HPC Challenges in Computational Sciences, to be held from July 7 to 12, 2019, at the campus of the RIKEN Center for Computational Science (R-CCS) in Kobe, Japan.

Applications are due Feb 4, 2019. The summer school is organized by the Extreme Science and Engineering Discovery Environment (XSEDE), the Partnership for Advanced Computing in Europe (PRACE), the R-CCS, and the SciNet HPC Consortium.

Leading computational scientists and HPC technologists from the U.S., Japan, Europe and Canada will offer instructions on a variety of topics as well as dedicated mentoring. Topics include:

  • HPC challenges by discipline
  • HPC programming proficiency
  • Performance analysis & profiling
  • Scientific visualization
  • Big Data Analytics
  • Machine Learning
  • Canadian, EU, Japanese and U.S. HPC-infrastructures

The expense-paid program will benefit scholars from Canadian, European, Japanese and U.S. institutions who use advanced computing in their research. The ideal candidate will have many of the following qualities, however this list is not meant to be a “checklist” for applicants to meet all criteria:

  • Familiar with HPC, not necessarily an HPC expert, but rather a scholar who could benefit from including advanced computing tools and methods into their existing computational work
  • A graduate student with a strong research plan or a postdoctoral fellow in the early stages of their research careers
  • Regular practice with parallel programming (i.e., student utilizes parallel programming generally on a monthly basis or more)
  • May have a science or engineering background, however, applicants from other disciplines are welcome, provided their research activities include computational work.

Students from underrepresented groups in computing are highly encouraged to apply (i.e., women, racial/ethnic minorities, persons with disabilities, etc.). If you have any questions regarding your eligibility or how this program may benefit you or your research group, please do not hesitate to contact the individual associated with your region below.

Interested students should apply by February 4, 2019. School fees, meals and housing will be covered for all accepted applicants, as well as intercontinental flight costs.
Further information and application:


SciNet HPC Consortium
Ramses van Zon
SciNet, Univ. of Toronto, Canada
Email: rzon at

Hermann Lederer
Max Planck Computing and Data Facility, Germany
Email: lederer at

Simon Wong
ICHEC, Ireland
Email: simon.wong at

Toshiyuki Imamura
Email: Imamura.toshiyuki at

Jay Alameda
NCSA, University of Illinois at Urbana-Champaign, United States
Email: alameda at

SciNet Receives HPCwire Award

December 6, 2018 in blog, for_press, for_researchers, for_users, frontpage, in_the_news, news, Road_to_Niagara, success_story

We are very proud that SciNet has received the 2018 HPCwire Editor’s Award for Best Use of HPC in Physical Sciences. The award was announced at the 2018 International Conference for High Performance Computing, Networking, Storage and Analysis (SC18), in Dallas, Texas.

SciNet used Lenovo and Mellanox technologies on the new Niagara cluster to create spatial resolution models of the Pacific Ocean, helping to validate ocean waves movement and to assist in global warming calculations. These calculations were performed by a team of scientists involving University of Toronto’s Prof. W. Richard Peltier, University of Michigan oceanographer Prof. Brian Arbic, and NASA JPL’s Dr. Dimitris Menemenlis. More on this calculation can be found here.

This calculation was part of the “early science” program of the Niagara supercomputer at the SciNet HPC Consortion. In this short period in March of 2018, a number of scientists were given the opportunity to perform “heroic” calculations. These large scale calculation were essential to test, to tune and to get Niagara ready for use as a Canada’s fastest national academic supercomputer.

SciNet concludes its biggest-ever training week in scientific, high performance, and data science computing

June 19, 2018 in blog-general, for_educators, for_press, for_researchers, for_users, frontpage, news, success_story

When summer arrives, it means the return of Ontario’s Summer School on Scientific and High Performance Computing. This annual set of educational events bring together graduate students, undergraduate students, postdocs and researchers and gives them an opportunity to learn and share knowledge and experience in technical computing, data science and biomedical computing on modern high-performance computing platforms.

The summer school has been given at three locations for the last seven years and is a collaborative effort of the three High-Performance Consortia in Ontario: SHARCNET, CAC, and SciNet. This year, the first was from May 28 to June 1 in London, while the second one was hosted by SciNet on the St. George campus of the University of Toronto from June 11 to 15, and the third will take place in Kingston from July 30 to August 3.

HPC Python session at the 2018 summer school

High Performance Computing with Python (“Parallel Python”) Session at the 2018 Ontario HPC Summer School in Toronto

The format of the school is that of a five-day intensive workshop with mixed lectures and hands-on sessions on a number of selected topics. The topics slightly vary by location, but may include shared memory programming, distributed memory programming and general purpose graphics processing unit programming, and Python, R, machine learning, neural networks, visualization, debugging, bioinformatics and bioimaging. To make all these topics fit in one week, the lectures are organized in different streams. In Toronto, there was a high performance computing stream, a data science stream, and a biomedical stream, given by instructors from SciNet, SHARCNET, and CAMH.

group photo HPC Summer School in Toronto

Group Photo of the 2018 Ontario HPC Summer School in Toronto

This year was SciNet’s biggest summer school yet. For the first time, there were more than two hundred participants, from widely varying academic background like Business Administration, Dentistry, Biology, Medicine, Economics, Health Sciences, Phyics, Chemistry, Engineering, and Astronomy. Those who attended at least three days received a certificate of attendance.

To get a sense of the tremendous growth of this event, consider that in 2012, one of the first years of the summer school, in Toronto, we had 35 participants in the summer school, issued 20 certificates, and a total of 400 contact-hours were delivered by a handful of instructors. In 2018, these numbers are 7 to 10 times larger: there were 211 participants, 135 certificates were issues, and 3800 contact-hours were delivered by 17 instructors. If that is not a clear enough indication of the demand for this kind of training, consider this: within one day of opening the registration, there were over 100 registrations, and just one week later, the 200 registration mark was crossed. There were people on the waiting list, although we made an effort to try and accommodate most people in the end.

The school is offered for free, but without support for travel, lodging or meals. It is therefore not surprising that most participants are from the Toronto area, but there was a sizeable number of attendants from outside Toronto (60), from outside of Ontario (15) and even from outside Canada (5).

The participants seem to really appreciate the event, as borne out by the preliminary results from the post-event survey. From the survey, we got suggestions for improvements for the future, such as (even) more hands-on and better explanation of prerequisites and software for the sessions. Nonetheless, 94% of the respondents was very satisfied with the summer school, and thought the overall value of the summer school was high. 92% would recommend the event to their peers. Interestingly, the answers to the question “What was the most important thing you learned or did during the summer school?” varied a lot, indicating, perhaps, that the broad range of offered topics allowed participants to pick what suits them best.

Organizing the school was a tremendous experience, made possible by 8 instructors and staff members from SciNet, 9 from CAMH, and 2 from SHARCNET. The University of Toronto provided the space for the session, while Compute Ontario sponsored the coffee-and-cookie breaks.

If you missed it this time, look for the announcement next spring of the 2019 Ontario Summer School on High Performance Computing.

Launch of the Niagara Supercomputer at SciNet

March 5, 2018 in for_educators, for_press, for_researchers, for_users, frontpage, in_the_news, news, Road_to_Niagara

The Niagara supercomputer was officially launched on March 5th, 2018. We were honoured by the presence and remarks of Reza Moridi (Ontario Minister of Research, Innovation and Science), Nizar Ladak (Compute Ontario President and CEO), Dr. Roseann O’Reilly Runte (CFI President and CEO), Prof. Vivek Goel (Vice-president of Research and Innovation at the University of Toronto), and Prof. W. Richard Peltier (Scientific Director of SciNet).

SciNet’s CTO Daniel Gruner gave an overview of the new system:

Niagara is located at University of Toronto and operated by the university’s high-performance computing centre SciNet, but the system is open to all Canadian university researchers.

Niagara is the fastest computer system in the country and is able to run a single job across all 60,000 cores thanks to a high-performance network which interconnects all the nodes. For more information on the configuration, see here.

A time-lapse of the building of Niagara is available (part of SciNet’s YouTube channel):

This system is jointly funded by the Canada Foundation for Innovation, the Government of Ontario, and the University of Toronto.

Road to Niagara 3: Hardware setup

March 5, 2018 in blog-technical, for_press, for_researchers, for_users, news, Road_to_Niagara, Uncategorized

This is the fourth of a series of posts on the transition to SciNet’s new supercomputer called “Niagara”, which will replace the General Purpose Cluster (GPC) and Tightly Coupled Cluster (TCS). The transition to Niagara will take place in the fall of 2017, and the system is planned to be available to users in early 2018.

The University of Toronto has awarded the contract for Niagara to Lenovo, and some of the details of the hardware specifications of the Niagara system have been released:

The system will have the following hardware components:

  • 1,500 nodes.
  • Each node will have 40 Intel Skylake cores (making a total of 60,000 cores) at 2.4 GHz.
  • Each node will have 200 GB (188 GiB)of DDR4 memory.
  • The interconnect between the nodes will be Mellanox EDR Infiniband in a Dragonfly+ topology.
  • A ~9PB usable shared parallel filesystem (GPFS) will be mounted on all nodes.
  • A 256TB Excelero burst buffer (NVMe fabric, up to 160 GB/s) will be available for fast I/O.
  • Peak theoretical speed: 4.61 PetaFLOPS

Niagara is estimated to be installed and operational towards in March 2018, and ready for users not too long after.

Even before official ready-date, there will a period in which select users can try out and port their codes to Niagara.

After the friendly-user period, all current users of the GPC (and former users of the TCS) will get access to Niagara.

The large core count, ample memory per core, and fast interconnect support Niagara’s intended purpose to enable large parallel compute jobs of 512 cores or more.

The software setup will also be tailored to large parallel computations. Nonetheless, there will still be a fair amount of backfill opportunity for smaller jobs.

The setup of Niagara is intended to be similar in spirit to the GPC, but different in form: scheduling per node, a home, scratch and possibly project directory defined in environment variables, a module system, and access to our team of analyst to help you get your codes running, and running well.

New Courses and New Initiatives for this Coming Semester

September 2, 2017 in for_educators, for_press, frontpage, news, Uncategorized

Excited about the beginning of a new academic year?

We, at SciNet, certainly are!

SciNet has created several new courses for this coming fall semester and we are really excited about that!
Take a look at our education website to learn about all the courses and workshops that we will be offering.

In addition to the traditional courses on Scientific Computing, we have also added courses on Computational BioStatistics, Machine Learning and Neural Networks, and basic level introductory courses for students without any previous background on computing or programming!

Additionally, several members of our team have obtained Graduate restricted appointed positions at the Institute of Medical Sciences and the Physics Department!

The number of SciNet courses that are listed as U of T graduate courses continues to increase (no small feat for a non-teaching unit like SciNet). Our full-term graduate courses in 2017/2018 are

Finally, starting this September we want to officially launch our “Research Initiative Program”!

This is a collaborative program, aimed to partner with research groups across the University, in order to boost and empower research.

Of course, research support is something that we have been doing since the beginning of SciNet, by providing technical support and the infrastructure to researchers for tackling their computational needs.
This program will go beyond that, by allowing researchers to explicitly partner with SciNet’s scientists, in order to pursue short and long term research projects.

More information about this program, ongoing collaborations and areas of expertise can be found at the
Research @ SciNet page.

2017 Compute Ontario Summer School Central

June 14, 2017 in blog, blog-general, for_educators, for_press, for_researchers, for_users, frontpage, news, Uncategorized

The Compute Ontario Summer School on Scientific and High Performance Computing is an annual educational event for graduate/undergraduate students, postdocs and researchers who are engaged in a compute intensive research. Held geographically in the west, centre and east of the province of Ontario, the summer school provides attendees with the opportunity to learn and share knowledge and experience in high performance and technical computing on modern HPC platforms.

Each site will have a slightly different list of courses. The summer school will include both in-class lectures and hands-on labs (done on the participants’ laptops). Those who attend at least three full days cumulatively will receive an official certificate in HPC training (i.e., a total of 6 full morning and afternoon sessions).

Instructors for this school have been provided by SciNet, CAMH and SHARCNET. Break refreshments are provided courtesy of Compute Ontario.


Registration for the central installment in Toronto from July 24-28, 2017 is now open!

The registration is free and is aimed at Compute Canada users as well as students, post-docs and other researchers from academic institutions. You do not need to have a SciNet account. Please be advised that seats are limited and tend to fill up.

More information and registration can be found on the summer school website.


High Performance Computing Stream Data Science Stream Biomedical Stream
Mon, Jul 24
Morning: 09:00-12:00
Welcome and Introduction to HPC and SciNet
Afternoon: 13:30-16:30
Shared Memory Programming with OpenMP Introduction to the Linux Shell PLINK
Tue, Jul 25
Morning: 09:00-12:00
Shared Memory Programming with OpenMP Introduction to R Next Generation Sequencing
Afternoon: 13:30-16:30
Programming Clusters with Message Passing Interface Data Science with Python RNASeq
Wed, Jul 26
Morning: 09:00-12:00
Programming Clusters with Message Passing Interface Parallel R for Data Science Python for MRI analysis
Afternoon: 13:30-16:30
Programming Clusters with Message Passing Interface Python for High Performance Computing (Parallel Python) Image Analysis at Scale
Thu, Jul 27
Morning: 09:00-12:00
Programming GPUs with CUDA Visualization with Python Machine Learning for Neuroimaging
Afternoon: 13:30-16:30
Programming GPUs with CUDA Scientific Visualization Suites R for MRI analysis
Fri, Jul 28
Morning: 09:00-12:00
Programming GPUs with CUDA Debugging, Profiling and Bring-Your-Own-Code Lab Public Datasets for Neuroimaging
Afternoon: 13:30-16:30
Programming GPUs with CUDA Debugging, Profiling and Bring-Your-Own-Code Lab Unit Testing / Neuroinformatics Pipeline Development


This event will be held in the Medical Science Building at the University of Toronto, 1 King Circle, Toronto, Ontario, M5S 1A8, Canada.

The nearest subway station is “Queen’s Park”. Paid parking is available on the St. George Campus.


Lodging is not provided by the organization. If you require lodging, you will have to make arrangements yourself. It may be worthwhile checking out the University’s summer residence program at .


Meals are *not* provided by the organization, but refreshments will be provided during the morning and afternoon breaks, courtesy of Compute Ontario.


For the hands-on sessions, participants are to bring their own laptop with working wireless and with an ssh client with X-windows installed. The latter is needed to connect to one of SciNet or SHARCNET supercomputers, to which the participant will get access for the duration of the School.


Participants that complete at least three days worth of instruction (i.e., a total of 6 morning and afternoon sessions combined) are to receive a Compute Ontario Summer School Certificate on the last day of the School. Note that this certificate is separate from the SciNet certificates, but parts of the school may count towards a SciNet certificate as well.

Grand Opening of the ArcNet Space at MaRS

May 15, 2017 in blog-general, for_educators, for_press, for_researchers, for_users, frontpage, news, Uncategorized

On May 9, 2017, the Grand Opening of the ArcNet space took place (despite having moved a while ago). What is ArcNet? It is a space where expertise and support of Advanced Research Computing (the “ARC” in ArcNet) from three organizations come together. SciNet is the oldest of the three; It is the supercomputing consortium at the University of Toronto, which has been providing Canadian researchers with computational resources and expertise necessary to perform their research on scales not previously possible in Canada, from the biomedical sciences and aerospace engineering to astrophysics and climate science. SOSCIP is a research and development consortium that pairs academic and industry researchers with advanced computing tools to fuel Canadian innovation. The third organization, Compute Ontario, partners with the four academic computing consortia in Ontario aims to drive advanced computing to accelerate research and enhance competitiveness in the global marketplace resulting in a more prosperous Ontario.

The Grand Opening brought together many of our stakeholders, and was also attended by the Ontario Minister of Research, Innovation and Science, MPP Rezi Moridi, by the President of the University of Toronto Meric Gertler, by the Vice-President of Research at the University of Toronto Prof. Vivek Goel, and by the Scientific Directory of SciNet Prof. W. Richard Peltier. We were honoured that each was willing to say a few words about the opening of this space.

“This facility is a true partnership between the University of Toronto’s SciNet High Performance Computing Consortium, SOSCIP and Compute Ontario. Bringing them together in a state-of-the-art facility will strengthen their partnership and undoubtably create new opportunities to drive innovation through advanced computing in Ontario.” said Prof. Goel, one of the driving forces of the creation of the space.

The President of the University of Toronto reminded us that “With ARCNet, we have created an amazing hub of talent and technology that fosters collaboration between the public and private sector.”

Minister Rezi Moridi remarked that “Today we are here to celebrate the grand opening of the Advanced Research Computing facility. It is great to see that three organizations got together and set up this wonderful facility: SOSCIP,
Compute Ontario, and University of Toronto’s SciNet. I wish you all the best in serving our research community.”

The speeches were given in the new teaching and visualization room. This room holds up to 40 students and is already frequently used for courses and other events. It features a large visualization wall, i.e., a 13 x 7.5 feet ultrahigh resolution screen (8K, to be precise).

Two presentations were given by SciNet analysts to demonstrate the capabilities of this visualization wall; Ramses van Zon showed how to get insight into the complexity of the software installed on SciNet’s main cluster by using graph visualizations, while Marcelo Ponce showed visualizations of several aspects of interacting neutron stars, with data from numerical general relativity simulations.

You can see the capabilities of the visualization wall in the following video: