Kokkos Lecture Series

The Kokkos Lectures

First Held: July-September 2020

The following Kokkos Lecture series presents an extensive introduction into everything necessary to start using Kokkos to write performance portable code. The Kokkos Lectures consist of 2-hour lectures and associated exercises. If you have question please join our slack channel at https://kokkosteam.slack.com

The first instance of the training is currently running. We will update this page with links to the recording, and Q&A when they become available. For updates and questions on the currently running series please visit: https://github.com/kokkos/kokkos-tutorials/issues/38

Office Hours Tuesday 3-5PM ET: login-info

Contents of the Lectures

This is a preliminary outline of the training. We are keeping a 9th day in reserve for anticipated schedule slippage. The lectures will be held Fridays: 10:00-12:00 MT (12:00-14:00 ET; 9:00-11:00 PT).

• Module 1: Introduction 07/17/2020 [ Slides ] [ Recording ] [ Q&A ]
  • Introduction
  • Concepts for Data Parallelism
  • Data parallel patterns
  • Building Applications with Kokkos
• Module 2: Views and Spaces 07/24/2020 [ Slides ] [ Recording ] [ Q&A ]
  • Views
  • Memory Space and Execution Spaces
  • Memory access patterns (Layouts)
  • Advanced Reductions
• Module 3: Data Structures and MDRange 07/31/2020 [ Slides ] [ Recording ] [ Q&A ]
  • Subview
  • MDRange
  • Dual View
  • Atomics
  • Scatter View
• Module 4: Hierarchical Parallelism 08/07/2020
  • Hierarchical parallelism
  • Scratch Space
  • UniqueToken
• Module 5: Streams, Tasking and SIMD 08/14/2020
  • Stream Integration
  • Tasking
  • SIMD
• Module 6: MPI and PGAS 08/21/2020
  • Fortran and Python Interop
  • MPI
  • PGAS
• Module 7: Tools 08/28/2020
  • Profiling
  • Tuning
  • Static Analysis
• Module 8: Kokkos Kernels 09/04/2020
  • BLAS
  • Sparse BLAS
• Backup Day: 09/11/2020

How to Attend

• The lecture series is available to everyone
• No-cost registration is necessary, meeting password will be send to registrants.
• For the exercises access to an NVIDIA GPU system or AMD GPU system with up-to-date software stack is recommended.