Scientific Computing in Practice

As time passes, consumer computers are becoming easier to use, but there are still no apps for making apps or doing research.  Thus, these days we need an even greater focus on basic computational literacy for research because the backgrounds of computational researchers are becoming more diverse and basic computational skills are being lost from academic courses.

SCIP is a lecture series at Aalto University which covers hands-on, practical scientific computing related topics. Lectures are open for the entire Aalto community as well as our partners at FGCI consortium.  For self-study, we have a comprehensive training guide.

Examples of topics covered at different lectures: HPC crash course, Triton kickstarts, Parallel programming models: MPI and OpenMP, GPU computing, Python for scientists, Data analysis with R and/or Python, Matlab, HTCondor and many others. See course archive links below.

Lectures by date and topics

Winter / Spring 2018 courses: tentative plan: Triton winter kickstart, Matlab continuation course, Introduction into MPILinux Shell Programming, Data analysis with R and Python. On top of them Summer Kickstart in June.

June 2018, Crash Course for computational scientists by Science IT people

A 3-day intensive kickstart to computational facilities available to Aalto researchers. Tentative plan: HPC crash course, CSC facilities and Cloud, Condor, Triton hands-on tutorial covering SLURM, Lustre etc, profiling and debugging tools on Triton. The course page.  This course, combined with CodeRefinery below, provides a comprehensive introduction to computation-heavy research.

May 2018, CodeRefinery at Aalto

An invited 3-days course given by NeIC people with the organizational help from Aalto Science IT. See details at course page The aim of this course is to demonstrate to and familiarize the workshop participants with best practices and tools in modern research software development. The main focus is on professional tools for efficiently developing and maintaining research software. To name a few: BASH, Python, PyCharm, Git, diff tools, Make, CMake, Jupyter Notebooks.  This course is appropriate for anyone who

 April 2018, Practical R and Python data analysis by Simo, Richard, Janne

The course will cover data analyzes techniques with R and Python. Oriented on Triton users (read Linux cluster users) mostly. Starts 9.4, consists of 6 sessions. Registration link and course details here.

March 2018, Linux Shell by Ivan Degtyarenko

We start with very basics of BASH and end up with a complicated scripting examples that help you to become a master of any Linux terminal. Starts on Monday 19.3, details at the course page.

March 2018, MPI introduction by Filippo Federici

Introduction to parallel programming with MPI. It stands for Message Passing Interface, a standard “de facto” for massive parallel calculations. See course details here.

Feb 2018, Matlab continuation by Juha Kuortti and Heikki Apiola

Advances of Matlab usage. Oriented on all Matlab users plus some specifics related to parallel runs on Triton. Requires a laptop with preinstalled Matlab. See course details here.

Jan 29th 2018, Winter kickstart by Science IT people

Getting started on Triton. All you need to start using a computational cluster efficiently.

Oct/Nov 2017, Matlab basics by Juha Kuortti

Basics of Matlab usage. Oriented on everyone and not specifically HPC oriented. Having Matlab installed on your workstation or laptop is enough to start using it. Matlab usage on Triton side is covered though as well. Details at  the course page.

Oct 2017, GPU computing with Filippo Federici

Practicalities of GPU computing with introduction to CUDA programming. Course will cover how to compile and run an application on GPU cards, how to use GPU libs in your code and how to write your own code from scratch with CUDA.

Details at the course page.

Sept/Oct 2017, Hands-on Molecular Dynamics with LAMMPS

Intro into Molecular Dynamics with practical aspects of LAMMPS package usage on Triton.

See details at

Jun 2017, Crash course for the computational scientists

Three days non-stop excursion into practical aspects of scientific computing.  Oriented on those who needs an intensive intro into computational resources available to Aalto users. “Must be” event for all new Triton users.

Covered topics: HPC basics, Triton practicalities like SLURM, Lustre etc, Matlab, R, GPU usage, CSC resources, Cloud and Condor computing. See details at  Scientific Computing in Practice: kickstart 2017

April 2017, Introduction to distributed computing with HTCondor

HTCondor is about how to utilize Aalto Linux workstations. The way to submit your application to a pool and let someone else to take care about where it is executed. Interested in running on your neighbors’ workstation while it’s idling? HTCondor is just about it. Come to try it.

Oct/Nov 2016, Matlab introduction & Matlab for advanced users

Lectures and tutorials that will consist of two parts, the first one is an introductory level course that will cover the basics, the second one deals with some more advanced techniques in Matlab. Details and registration are coming…

Oct 2016, Python for Scientific computing

Several  hands-on tutorials that will cover NumPy, SciPy, Cython and matplotlib packages. Given by CSC specialists. Details and registration.

6-8 June 2016, Summer kickstart for Triton newcommers

Must be event for all newcomers that started on Triton recently or plan to start soon. We cover all practicalities of Triton usage and on top of that advanced techniques for debugging and profiling the codes. Register and see details over here.

31 May 2016, CSC seminar on Cloud services

Addressed to wide audience interesting in Cloud Computing topic. Services provided by CSC available to all Aalto researchers, so come to listen what is it about.

May 2016, Scientific Data Analysis with Mathematica by FIlippo Federici

Want to hear what one can do with Wolfram Mathematica? Come to listen and try it.

April 2016, Condor introduction

Every modern workstation has at least four CPU cores and 8G of memory, often even more. What about use those in your department? How to utilize local idling workstations? HTCondor is about it. Come to try it.

March 2016, Hands-on Molecular dynamics

Theoretical intro into Molecular Dynamics with the help of LAMMPS package. Details at the course page.

February & March 2016, Triton Winter Kickstart & User Group Meeting

Kickstart for newcommers and User Groups meeting for all users. See dates, place.

October 2015, Introduction to GPU computing with CUDA

Serie of lectures and hands-on tutorials on general introduction into CUDA programming on GPU devices (Graphical Processing Units). See details at SCiP: GPU computing with CUDA page.

 June 1-3, 2015, Scientific Computing in Practice: kickstart 2015

It became an annual event. We go for the 3 day hands-on tutorial  once again. Triton introduction along with the overview of CSC, Grid and Condor computational resources available to Aalto researchers. In addition to basics we go for advances in profiling, debugging and code optimizing techniques and introduction into OpenMP programming. Details are at SCiP Kickstart 2015 page

June 9-11, 2014, Scientific Computing in Practice: kickstart 2014.

Following success of the SCiP kickstart 2013 we go for the three days HPC maraton in June 2014. This time, in addition to Triton user tutorial, Grid computing and CSC resources, you get to participate into Python for scientific computing and GPU computing parts. For exact dates and place see details at Scientific Computing in Practice: kickstart 2014.

June 10-12, 2013, Scientific Computing in Practice: kickstart 2013.

Three days of non-stop computing course oriented on new comers to fields of scientific computing at Physics, Chemistry, Computer Science, Math or any else at Aalto University. Or those who needs an intensive intro into computational resources available to Aalto users.

Covered topics: HPC basics, Triton practicalities, Condor, MPI programming, Matlab, Hadoop, GPU programming, CSC resources, Grid computing on FGI. See details at  Scientific Computing in Practice: kickstart 2013