SciNet’s Summer School: a decade-old tradition

October 1, 2019 in blog, blog-general, for_educators, for_press, frontpage, news

Most would associate summertime with a relaxing and leisurely season of the year. However, HPC centres like SciNet, as in many others around the world, perceive this differently and are actually quite busy during this period.

Among the many activities SciNet carries out during the summer “break” are workshops and short courses. These activities are scheduled in the summer to fit between the term-long courses that SciNet offers to graduate students at the University of Toronto.

In particular, one of SciNet’s oldest training activities is a one-week intensive school on high-performance and technical computing. This annual summer school is our flagship training event, and is aimed at graduate students, undergraduate students, postdocs, researchers and occasionally even faculty members, who are engaged in compute intensive research. SciNet’s first such summer school was given in 2009, at which time it was called a “Parallel Scientific Computing” workshop. This first version of the school was heavily focused on parallel programming and applications in astrophysics.

These days, SciNet’s summer school is part of the Compute Ontario Summer School on Scientific and High Performance Computing. Held geographically in the west, centre and east of the province of Ontario in Canada, 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. The central edition is the continuation of the SciNet summer school.

Not only is the school organized in a wider context, its program has expanded as well. In the last three years, the Toronto edition has had three streams with a wide variety of topics, from shell programming to data science, machine learning and neural networks, biomedical computing, and, still, parallel programming.

The type of training offered at the summer school is very practical, with a lot of hands-on exercises and live coding. This practical approach is very typical for most of SciNet’s courses but takes its ultimate form during the summer school instruction.

In addition to the training that participants received, the school also offers the opportunity of participants to interact with other participants, as well as the instructors, exchange ideas or discuss about current problems they are trying to solve. In fact, since a couple of years, the program includes focused sessions such as “Bring your own code” and “Bio-Hacking”, where this sort of interactions are not only promoted but the main theme.

Our summer school has the add-on feature of being absolutely free of charge for participants! That’s something we believe is quite important for several reasons, but mostly because we believe that in this way we can reach more researchers from fields that are relatively new to doing computational research.

This type of event not only benefits the students and participants of the summer school, but also enables collaborations between departments and consortia, as part of the training was delivered in partnership with colleagues from SHARCNET and the Centre for Addiction and Mental Health.

click on picture to enlarge

SciNet’s first summer school in 2009 focussed on Parallel Scientific Computing and placed emphasis on scientific applications such as in astrophysics.

click on picture to enlarge

SciNet’s latest (and largest) summer school, held in June 2019. This summer school had three parallel streams: the traditional High-Performance Computing, one on Data Science and a stream on BioInformatics/Medical applications, which was added in 2017. Details of the courses covered in the school can be found in SciNet education website: SciNet.courses/438

Logistics and Organizational details of the Summer School

There is no simple recipe to make a successful summer school that attracts and retains motivated participants for five full days, but below are a few necessary ingredients.

Sessions and instructors… Coming up with a program of three streams with sessions on scientific computing, parallel programming and data science is a challenge, but finding the excellent instructors for them is an even greater challenge, especially in summer, when many people are away.
Nonetheless, the summer school has been able to grow from a single-stream offering of 100 lecture hours in 2014 to a three-stream program with nearly 300 lecture hours in 2019. Luckily, we are not limited just to SciNet staff for instructors, but get help from the people from SHARCNET and CAMH as well.

Rooms… Organizing a training section of one-week long from Monday to Friday starting at 9:30am and finishing 4:30pm, offers a lot of challenges. For starting, finding rooms (not only one, but actually three –as there are three parallel concurrent sessions), ideally on the same building and each of them able of hosting around a hundred people, with proper power outlets, AC capabilities, and comfortable enough is a task far from trivial. We manage to do this, again with the effort of our instructors and staff who start to look into booking rooms months in advance… again summertime is not that “quiet and relaxing time” people may think of at the university premises…

Taking attendance… We issue certificates for those participants that attend at least three days. This requires that we record the attendance of the participants for every session every day. In the initial summer schools, where there were one or two parallel sessions at most, and the total number of participants wasn’t too large, we used a paper signing list, where students self-reported their attendance. By the end of the week we would collect and count these lists and manually awarded certificates.

But with 3 parallel streams and more than two hundred participants, the task of manually sorting out attendance has become unfeasible. To tackle this issue, we developed a system using our own education website, where we ask the participants to take a “test” selecting from 10 randomly generated codes the one that is given in the session they are attending.
In this way, the participation of each student is recorded and tied to the specific session associated with the selected code. The same site handles registration and dispenses the students’ access to temporary accounts on computing resources they will use during the week, and contains the teaching materials.

Certificates… Having recorded the attendance from the participants, this is just the beginning of the process of issuing the certificates. After this, we have scripts that can identify the participants that would be awarded a certificate of participating according to the criteria stated before, and generate a PDF document stating that. Years ago, we use to run through the university campus on the last day to print hard-copies of these, but since last year we send the participants an electronic version of it. The number of certificates demonstrates the growth in attendance over the years: In 2014 we awarded 30 attendees with summer school certificates, in 2019, this number has grown to 159.

Financial support… One remarkable thing about the school is that we are able to continue offering this high-quality and relevant training free of cost to the participants. This is not a easy task to achieve, as there are several costs associated to the event. The cost of the instructors is absorbed by the partnering organization (SciNet, SHARCNET and CAMH), while logistic costs for the rooms and AV utilizations are covered by SciNet, while coffee breaks that are provided to the participants were sponsored by Compute Ontario.

Other centres have decided to charge their participants a modest registration fee for their summer school, which allows them to tackle two things: one is to alleviate the cost associated with the event itself; and secondly, to reduce the number of no-shows during the school. Fortunately our attendance numbers have been rising steadily every year, but our turn-out rate seems to be steady and predictable at 70%, making the no-show effect non-issue.

More summer activities…

SciNet also participates in the International HPC Summer School, sending a few instructors and 10 students to this competitive one-week program every year.

Last but not least, SciNet finished this year’s summer season co-organizing and hosting a “virtual” remotely hosted one week-long PetaScale Computing Institute at the end of August.

Although physically and intellectually exhausted, we finished one of the busiest summer seasons ever in SciNet’s training and education history, allowing us to keep pushing ourselves and re-charge of our energies for the beginning of the academic year.

Further details and information about SciNet’s education and teaching endeavours can be found in the following link:

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.

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.

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.

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

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.

SCHEDULE

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

LOCATION

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

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 www.studentlife.utoronto.ca/hs/summer .

MEALS

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

COMPUTING FACILITIES

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.

CERTIFICATES

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:




Expired: HPCS 2017, Kingston June 5-9, 2017

April 25, 2017 in blog-general, for_researchers, for_users, Uncategorized

HPCS (the High Performance Computing Symposium) is Canada’s premiere Advanced Research Computing (ARC) conference, bringing together top researchers from across Canada and around the world, as well as major industry partners.

This year’s conference is being held in Kingston, Ontario – June 5th – 9th, and will include a range of keynote sessions and technical workshops designed to appeal to the research community and ARC professionals. Topics will include “traditional” HPC disciplines, as well as emerging areas such as cognitive computing – and there will have sessions exploring future technologies.

For more information see 2017.hpcs.ca

Note that Ontario students can go for fee (see the flyer).

Gravitation waves detected, again!

June 15, 2016 in blog, blog-general, blog-technical, for_press, for_researchers, for_users, in_the_news, news, success_story, Testimonials

We congratulate the LIGO and Virgo collaborations to the second-ever observation of gravitational waves from colliding black holes.

SciNet is proud to have contributed to the computation of the waveform templates that were used in this latest discovery of LIGO. LIGO measured about 55 gravitational wave cycles for this new binary black hole system. This large number of cycles made detailed computations of the expected wave-shapes more important than for the first detected black hole merger that was announced in February.

Canada is a leader of numerical calculations of colliding black holes, research led by Professor Harald Pfeiffer, Canada Research Chair for Numerical Relativity and Gravitational Wave Astrophysics at the University of Toronto. Pfeiffer states: I am very grateful for the sustained support of the SciNet team during the last 7 years; their support and the access to computing time on SciNet’s supercomputers have been crucial for my research program and its profound contributions to the LIGO discovery.

frame06508

Above: The in-spiral and collision of two black holes similar to GW151226. The top portion of the frame shows the horizons of the two holes, in this case, at the moment close to the merger of the black holes. The middle portion of the frame shows the gravitational waveform projected onto the LIGO Livingston detector. The bottom part shows the frequency of the gravitational waves, gradually increasing from about 35Hz to above 700Hz. For this system, LIGO could observe many more gravitational wave cycles than for the first discoved system (named GW150914).

Visualization done by University of Toronto Undergraduate student Aliya Babul & Prof. Harald Pfeiffer, within the SXS Collaboration/www.black-holes.org.

2016 Ontario HPC Summer School – Toronto

June 2, 2016 in blog, blog-general, for_educators, for_press, for_researchers, for_users, frontpage, news

ohpcss

The 2016 Ontario Summer School on High Performance Computing is a week-long academic workshop that provides attendees with opportunities to learn and share knowledge and experiences in high performance computing, technical computing, and data science. The Ontario HPC Summer School is given in three locations, in different weeks. The first one was from May 30 to June 3 in Hamilton, the second will be in Toronto from July 11 to 15, hosted by SciNet, while a third will take place in Ottawa from August 8 to 12.

The format of the school is that of a five-day workshop with mixed lectures and hands-on sessions on a number of selected topics, including shared memory programming, distributed memory programming and general purpose graphics processing unit programming, and data science. The program varies slightly per location.

Most sessions are given in parallel. When registering for the Toronto event, you can pick the sessions you are interested in from the following schedule (note that you cannot register for only part of a session):

SCHEDULE

Monday July 11, 2016
9:30 am – 12:30 pm
single stream: Intro to high performance computing and SciNet
1:30pm – 4:30 pm
stream 1: Shared memory programming with OpenMP, part 1 of 2
stream 2: Intro to the Linux Shell

Tuesday July 12, 2016
9:30 am – 12:30 pm
stream 1: Shared memory programming with OpenMP, part 2 of 2
stream 2: R for data science
1:30pm – 4:30 pm
stream 1: Programming Clusters with MPI, part 1 of 3
stream 2: Parallel R for data science

Wednesday July 13, 2016
9:30 am – 12:30 pm
stream 1: Programming Clusters with MPI, part 2 of 3
stream 2: Python for scientific computing
1:30pm – 4:30 pm
stream 1: Programming Clusters with MPI, part 3 of 3
stream 2: Python for high performance computing

Thursday July 14, 2016
9:30 am – 12:30 pm
stream 1: Programming GPUs with CUDA, part 1 of 4
stream 2: Visualization, part 1 of 2
1:30pm – 4:30 pm
stream 1: Programming GPUs with CUDA, part 2 of 4
stream 2: Visualization, part 2 of 2

Friday July 15, 2016
9:30 am – 12:30 pm
stream 1: Programming GPUs with CUDA, part 3 of 4
stream 2: Debugging
1:30pm – 4:30 pm
stream 1: Programming GPUs with CUDA, part 4 of 4
stream 2: Bring your own code

LOCATION

This event will be held in the Mechanical Engineering Building at the University of Toronto

Wallberg Building
Rooms 116 and 119
University of Toronto
St. George Campus
184-200 College Street
Toronto, Ontario, M5S 3E5
Canada.

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

LODGING

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 www.studentlife.utoronto.ca/hs/summer .

MEALS

Meals are not provided by the organization, but refreshments will be provided during the morning and afternoon breaks.

COMPUTING FACILITIES

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’s supercomputers, to which the participant will get access for the duration of the School.

CERTIFICATES

Participants that complete at least three days worth of instruction are to receive an 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.

MORE INFORMATION AND REGISTRATION

For more information on the sessions and for registration, please go to
www.sharcnet.ca/events/ss2016

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.

Big Data Challenge for HighSchool Students 2016

February 12, 2016 in blog-general, for_educators, for_press, frontpage, success_story

IMG_20160204_091035 IMG_20160204_144339 IMG_20160204_144158

SciNet in partnership with STEM Fellowship (http://stemfellowship.org/), SAS and Open Data Toronto, organized the second edition of the “Big Data Challenge for High School Students”.

On Feb. 4th, the 2015/2016 Big Data Challenge for high school students took place. 8 teams from several schools across the GTA presented their research on data analytic in front of peers and judges.

Inspired by “Big Data in the City” theme, students gathered data from Open Data Toronto, analysed and investigated topics such as: immigration relocation strategies, emergency response for first responders services, identification of clusters in Toronto, environmental analysis of Toronto neighbourhoods, debt risk analysis of the city, collision patterns and prevention, data mining from social media related to energy efficient companies, among many others.

SciNet members, in addition to organize this event participated evaluating the initial proposals and judging the final 8 qualified for the final presentation.

IMG_20160204_143755

Participants of the Big Data Challenge will be participating in tours to SciNet’s datacenter, as an unique opportunity to experience and visit the home of the largest super-computers in Canada!

 

Congratulations to all the participants!!!

 

Further information can be found in the following links:

http://stemfellowship.org/bigdata

http://journal.stemfellowship.org/doi/abs/10.17975/sfj-2015-013

https://support.scinet.utoronto.ca/education/go.php/230/index.php/ib/1//p_course/230