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DESCRIPTION:# Overview\nWe currently live in an era where most computers po
 ssess multiple computing units\, and where parallelization is key.\nIn par
 ticular\, GPGPUs (General Purpose Graphical Processing Units) are built fo
 r massive parallelism and they have recently risen to prominence as they a
 re now used for many scientific tasks\, such as physics or biological simu
 lations\, statistical inference or machine learning.\n\nIn this crash cour
 se we will focus on CUDA as well as several CUDA-based API\, including ope
 nMP GPU offloading and python APIs. Through concrete examples we will desc
 ribe the principles at the core of a successful parallelization attempt.\n
 \n# Audience\nThis course is intended for programmers and computational bi
 ologists who want to take their first steps with GPU programming.\n\nWe wi
 ll assume no previous knowledge of GPU programming\, CUDA\, or paralleliza
 tion techniques\, but we require that the participant be proficient in at 
 least one language among python or C++.\n\n\n# Learning outcomes\nBy the e
 nd of the course\, the participant will be able to:\n * identify good cand
 idates tasks for GPU acceleration\n * understand the structure of a GPU\, 
 including memory handling\n * perform some computations on a GPU\, using e
 ither python or C++\n * manage memory transfers to the GPU for better perf
 ormances\n * evaluate their GPU code using profiling\n\n\n# Prerequisites\
 n#### Knowledge / competencies\nParticipants should be comfortable working
  in a Linux/UNIX environment and have some basic experience in programming
 .\nSome knowledge of C/C++\, Fortran or Python is necessary.\n\n\n#### Tec
 hnical\nYou are required to work on your own laptop with an Internet conne
 ction.\nThe computer you use for the practicals should be the same as the 
 one you use to connect to the course zoom room (in order for us to help yo
 u debug your code during practicals).\n\n\n# Schedule - CET time zone\n**T
 entative program**\n\nMorning 9:00 -12:00\n\n* Introduction: what is a GPU
 ?\n* What problems can it solve? And how to use it?\n* First real life exa
 mples and practical\n\nLunch break : 12:00 - 13:00\n\nAfternoon 13:00- 17:
 00\n\n* Real life examples\, and random number generation on a GPU\n* Comm
 on pitfalls in GPU programming\n* Memory management on a GPU\n* GPU monito
 ring \n* Practical\n\n# Application\n\n\n\n\nThe registration fees for aca
 demics are **60 CHF** and **300 CHF** for for-profit companies.\n\nWhile p
 articipants are registered on a first come\, first serve basis\, exception
 s may be made to ensure diversity and equity.\n\nYou will be informed by e
 mail of your registration confirmation. Upon reception of the confirmation
  email\, participants will be asked to confirm attendance by paying the fe
 es within 5 days.\n\nApplications will close as soon as the places will be
  filled up. Deadline for free-of-charge cancellation is set to **07/02/202
 3**. Cancellation after this date will not be reimbursed. Please note that
  participation in SIB courses is subject to our [general conditions](http:
 //www.sib.swiss/training/terms-and-conditions).\n\n# Venue and Time\nThis 
 course will be streamed online. It will start at 9:00 and end around 17:00
  CET.\n\nPrecise information will be provided to the participants before t
 he course.\n\n#  Additional information\nCoordination: Monique Zahn\, SIB 
 Training Group.\n\nYou are welcome to register to the SIB courses mailing 
 list to be informed of all future courses and workshops\, as well as all i
 mportant deadlines using the form [here](https://lists.sib.swiss/mailman/l
 istinfo/courses).\n\nPlease note that participation in SIB courses is subj
 ect to our [general conditions](http://www.sib.swiss/training/terms-and-co
 nditions).\n\nSIB abides by the [ELIXIR Code of Conduct](https://elixir-eu
 rope.org/events/code-of-conduct). Participants of SIB courses are also req
 uired to abide by the same code.\n\nFor more information\, please contact 
 [training@sib.swiss](mailto://training@sib.swiss).
SUMMARY:Introduction to GPU Programming for Life Sciences
URL;VALUE=URI:https://www.sib.swiss/training/course/20230214_GPU
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