Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

You are familiar with some scientifically or technically demanding topic.

Credits: 5

Schedule: 23.04.2021 - 28.05.2021

Teacher in charge (valid 01.08.2020-31.07.2022): Petri Vuorimaa

Teacher in charge (applies in this implementation): Maarit Käpylä, Linh Truong

Contact information for the course (valid 12.04.2021-21.12.2112):

More complete page on the course is maintained in Aalto gitlab:

https://version.aalto.fi/gitlab/lsca/cs-lsca/-/blob/master/README.md

Contact persons for the course are Linh Truong & Maarit Käpylä (firstname.lastname@aalto.fi)

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

Teaching language: English

Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • Valid 01.08.2020-31.07.2022:

    This course has a varying topic. The content of the course is a selected current topic areas in communication, computer and information sciences. When arranged, the course may be given in English. Information about the arrangement and the beginning of the course will be published in the web pages.

  • Applies in this implementation:

    This is a special couse on Large-Scale Computing and Data Analysis.
    The learning goal is to familiariaze the students with high-performance
    computing tools in use in present-day supercomputing facilities,
    and to practical applications that they can be utilized on. During this
    project-oriented course, the students are working hands on with pre-existing tools
    on challenging problems and data sets in a real supercomputing environment.
    In addition to working on a specific tool/application individually/in teams, the students will learn from
    other tools and applications through demonstrations by other students/teams.

    A preliminary list of topics has been collected, but students can also propose their
    own topic. A supercomputing environment will be set up for the course participants (hosted at
    CSC),
    hence the number of participants is limited to 10-12 students. Depending on the
    selection of topics, the students can either work individually or in teams.
    After introductory lecture(s) on how the environment works,
    the instructors of the topic will set up weekly meetings with the student (teams), and give materials and
    instructions on the project (introduction to the tool,
    documentations, papers, demonstration of the usage). After introductory session(s),
    the weekly meetings will serve as project update sessions. In the end of the course,
    the student (teams) are expected to give demonstrations to other student (teams) on their project.
    Participation in 80% of the sessions and a successful demonstration session to other students
    is required to pass the course. A session participation missed can be compensated by
    writing a learning diary in the form of a short email (or equivalent) to the instructor.


Assessment Methods and Criteria
  • Valid 01.08.2020-31.07.2022:

    Announced later.

  • Applies in this implementation:

    In the end of the course, the student (teams) are expected to give demonstrations to other student (teams) on their project. Participation in 80% of the sessions and a successful demonstration session to other students is required to pass the course. A session participation missed can be compensated by writing a learning diary in the form of a short email (or equivalent) to the instructor. The goal is to learn to use HPC facilities and relevant tools, and passing of the course does not depend on a successful implementation of certain project.

SDG: Sustainable Development Goals

    9 Industry, Innovation and Infrastructure