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cuda_2018

Canceled: GPU Programming with CUDA
Date: 12.12.2018 9:00 - 14.12.2018 17:00
Location details: The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.
Language: English
Lecturers: Jussi Enkovaara (CSC)
Fredrik Robertsen (CSC)
Price:
  • 180 euros + VAT (24%) for Finnish universities, polytechnics and governmental research institutes
  • 840 euros + VAT (24%) for others
The fee covers all materials, lunches as well as morning and afternoon coffees.
Registration is closed.
The seats are filled in the registration order. If a cancellation is received five (5) business days prior to the course, the course fee will be refunded with the exception of a handling fee of 10 €. For no-shows and cancellations after the cut of date no refunds will be made. Registration can be transferred to someone else from the same organization without additional charge.

Payment can be made with electronic invoicing, credit card, or direct bank transfer. Note that for electronic invoicing you need the operator and e-invoicing address (OVT code) of your organization. Please also note that invoice reference is needed for electronic invoicing in your organization, so please have this available when registering.
Additional information
Content: jussi.enkovaara@csc.fi
Practicalities: event-support@csc.fi

This course gives basic to intermediate level knowledge on CUDA programming. The course first gives a basic introduction to writing GPU applications using CUDA. Building on this more advanced topics are introduced that enable one to write efficient CUDA applications, including asynchronous execution with streams, utilizing Nvidia performance tools and how to write efficient kernels. Finally multi-GPU programming both within a node and between nodes, as well as new CUDA features will be discussed.

Prerequisities

Participants should have working knowledge on C programming language and basic knowledge on MPI programming. No prior knowledge on GPGPU programming or CUDA is required.

Learning outcome

After the course participants should be able to write simple CUDA programs that utilize multiple GPUs.

Program

Wednesday

  • Introduction to GPU programming
  • CUDA programming I: programming model & memory model
  • Nvidia tools for performance analysis and debugging
  • CUDA programming II: further topics on basic CUDA programming

Thursday

  • Cuda programming III: Streams and asynchronous execution
  • Cuda programming IV: Optimizing kernel performance
  • Advanced CUDA features I: Unified memory and Lambdas

Friday

  • Advanced CUDA features II: cooperative groups
  • Multi-GPU programming

Projects and Collaboration Networks
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