Study on the role of mediator complex in gene expression in collaboration with SciNet

September 10, 2019 in for_press, for_researchers, frontpage, in_the_news, news, science, success_story, Testimonials

For the last two years, SciNet has been collaborating with PhD candidate Alejandro Saettone from the Fillingham lab from Ryerson University. One of the research projects, which also involved the group of Dr. Ronald Pearlman at York University, deciphered some aspects of the mediator complex’s role in transcription and gene expression using the model organism Tetrahymena thermophila. See the EurekAlert! story on the matter, or the original paper in Current Biology.

The collaboration of SciNet’s Dr. Marcelo Ponce and Alejandro Saettone led to the development of the RACS (“Rapid Analysis of ChIP-Seq data”) pipeline, which serves to analyze data obtained from Chromatin Immunoprecipation followed by next generation Sequencing experiments (ChIp-Seq for short). The paper on this computational pipeline has been recently accepted for publication in BMC BioInformatics. The RACS pipeline, a set of bash shell scripts and R scripts, is open-source software available as a git repository at https://bitbucket.org/mjponce/RACS.

The RACS pipeline has been quite fruitful, having already resulted in two papers where it was applied to data from the model organism Tetrahymena thermophila. The pipeline is expected to result in a few more papers analyzing further data, and there are plans to make it suitable to target more general cases.

Alejandro Saettone: “Our group was very fortunate to collaborate with Dr. Ponce from SciNet. He helped our lab to solve bioinformatic problems involving big data. With this collaboration, we were able to advance knowledge in chromatin remodeling and gene expression.”

Learn more about SciNet’s research and opportunities to establish research collaborations visiting our research website.

SciNet’s publication about Niagara deployment

August 3, 2019 in blog, blog-general, blog-technical, for_press, for_researchers, for_users, frontpage, news, Road_to_Niagara

Have you ever wondered how a supercomputer is designed and brought to life?
Read SciNet’s latest paper on the deployment of Canada’s fastest supercomputer: Niagara.

Niagara is currently the fastest supercomputer accessible to academics in Canada.
In this paper we describe the transition process from our previous systems, the TCS and GPC, the procurement and deployment processes, as well as the unique features that make Niagara a one-of-a-kind machine in Canada.

Please cite this paper when using Niagara to run your computations, simulations or analysis:
“Deploying a Top-100 Supercomputer for Large Parallel Workloads: the Niagara Supercomputer”, Ponce et al, “Proceedings of PEARC’19: Practice and Experience in Advanced Research Computing on Rise of the Machines (Learning)”, 34 (2019).

Learn more about SciNet’s research and publications by visiting the following link.

2019 Compute Ontario Summer School Central

May 14, 2019 in blog, for_educators, for_press, for_researchers, for_users, frontpage, news

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 June 24-28, 2019 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 or Compute Canada account (although you can use that). Please be advised that seats are limited and tend to fill up.

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)
    https://doi.org/10.22369/issn.2153-4136/10/1/1

    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)
    https://doi.org/10.22369/issn.2153-4136/10/1/5

    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)
    https://doi.org/10.22369/issn.2153-4136/10/1/9

    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.

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: http://ss19.ihpcss.org.

Contacts:

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

PRACE:
Hermann Lederer
Max Planck Computing and Data Facility, Germany
Email: lederer at mpcdf.mpg.de

Simon Wong
ICHEC, Ireland
Email: simon.wong at ichec.ie

RIKEN:
Toshiyuki Imamura
CCS, RIKEN
Email: Imamura.toshiyuki at riken.jp

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

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.

International HPC Summer School 2018 in Ostrava, by SciNet, XSEDE, PRACE and Riken

December 22, 2017 in for_educators, for_researchers, for_users, frontpage, in_the_news, news

A High-Performance Computing Summer Institute
July 8-13, Ostrava, Czech Republic
Expenses-paid program
Apply by February 13, 2018
Website: http://ihpcss18.it4i.cz


Graduate students and postdoctoral scholars from institutions in Canada, Europe, Japan and the United States are invited to apply for the ninth International Summer School on HPC Challenges in Computational Sciences, to be held July 8 to 13, 2018, in Ostrava, in the Czech Republic, and hosted by the IT4Innovations National Supercomputing Centre.

Applications are due Feb 13, 2018. The summer school is organized by the Partnership for Advanced Computing in Europe (PRACE), the Extreme Science and Engineering Discovery Environment (XSEDE), the RIKEN Advanced Insti­tute for Computational Science (RIKEN AICS), and the SciNet HPC Consortium.

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

  • HPC challenges by discipline
  • HPC programming proficiencies
  • Performance analysis & profiling
  • Algorithmic approaches & numerical libraries
  • Data-intensive computing
  • Scientific visualization
  • 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 efforts
  • 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 13, 2018. Participation, meals and housing will be covered for the selected participants, also support for intercontinental travel will be given (contingent to funding).

Further information and application, see http://ihpcss18.it4i.cz.

Road to Niagara 1: Tightly Coupled Cluster Decommissioned

October 25, 2017 in frontpage, news, Road_to_Niagara


This is the first of a series of posts on the transition to SciNet’s new supercomputer called “Niagara”, which will replace our aging 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.

To make room for Niagara, old systems will have to go. Because enabling research computing is our priority, throughout the process of installting Niagara, at least 50% of the GPC will be kept running. The GPC will not be completely switched off until Niagara is available.

The first cluster to go was the TCS. This was SciNet’s first supercomputer, a 102-node, 3264-core, IBM Power 6 system installed in January of 2009.

The TCS was shut off on September 29, 2017, and physically removed in October. The end of an era.

As the pictures below show, you don’t just put your old supercomputer to the curb, there is a bit of work involved in removing it. It took about 8 hours, 14 pallets, 10 racks, and 3 truck loads. And a $5 bill was found under one of the TCS racks, so we made some money as well!

Currently we are in mids of finalizing the contract for Niagara, so the next post in this series will provided more details on the new system to come.

Decommissioning the old Power 6 TCS requires a little fork lift; those are heavy nodes.

TCS nodes taken out of their racks.


The empty space left behind by the TCS…


Decommissing TCS subfloor connections.