In this presentation we go through the parallel programming posibilities in .NET C#. First we discuss some core concepts then we explore the problem space and the related toolbox. Finally we will have a sample library which implements the same interface in 20+ different ways to show you the alternatives. Related code can be reached here: https://github.com/peter-csala/parallel-programming-dotnet

1. Peter Csala

2. 2
Agenda
• Definitions & Terminologies
• Problems & Toolbox
• Demos

3. Definitions and Terminologies

4. 4
Concepts & Misconceptions
Parallel Programming
Concurrent Programming Asyncronous Programming
Multi-Threaded Programming

5. 5
Prog. model: Sync vs Async

6. 6
Execution: Parallel vs Concurrent

7. 7
Environment: Single vs Multi Threading

8. 8
Rumor: Zen 3 can run 4 threads / core

9. 9
Rumor: Ryzen ThreadRipper (64cores)

10. 10
Types: Data vs Task

11. Problems & Tools

12. 12
Problems: Shared State

13. 13
Toolbox against concurrent mutation
• Syncronization Primitives
• Concurrent Collections
• Immutable state

14. 14
Patterns against concurrent mutation
• Fork / Join
• Master – Worker
• Producer + Consumer
• Divide & Conquer
• MapReduce
• Observer
• Pipeline
• All To All
• Stencil
• Etc.

15. 15
It’s all about isolation

16. Enough theory, Let’s practice

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The Downloader
Functional Req.s
• I want to be able to download
arbitrary number of web contents
• I want to be able to process them
in arbitrary way
• It MUST be blazingly fast
• It MUST be superb easy to use
• Why is this not done yet?
Non-Functional Req.s
• Ensure that the provided strings
are valid Uris
• Ensure post-processing ability via
continuation / callback
• It should run in parallel without
exhausting all resources
• Interface should ask for only the
bear minimum (use default
params)

18. 18
Architecture: Cardinality

19. 19
Architecture: Cardinality

20. 20
Architecture: Cardinality

21. 21
Architecture: Cardinality

22. 22
Architecture: Throttling

23. 23
Architecture: Shared State
• The whole source is shared
• The source is pre-partitioned
• The partitions are processed
separately by pulling

24. 24
Architecture: Shared State
• The source is pre-partitioned
• The partitions are not shared
• The partitions are processed
separately by iterating

25. 25
Architecture: Shared State
• The whole source is shared
• The source is dynamically
partitioned
• The source pushes the data to the
targets

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It’s demo time

27. 27
What have we learnt?

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What have we learnt?
• (Non-)deterministic
• Slow down
• Over parallelisation
• Partitioning is hard
• Common pitfalls
• Measure base line
• Measure speed-up
• CPU vs I/O bound
• Immutables
• Enormous toolset

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Where should I look for details?
• Parallel class
• PLINQ partitioning
• Channels
• Parallel data structure, 2
• Synchronization primitives, 2
• Compare Parallel models
• Immutable Collections, 2
• Throttling
• Potential Pitfalls, PLINQ
• Async Guidance
• Async antipatterns
• Avoid sync problem
• VS Threading nuget
• Concurrency Visualizer

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Is there any free e-book?
• Patterns & Practices Parallel Programming with Microsoft
.NET
• Patterns of Parallel Programming
• Introduction of TPL Dataflow
• Parallel Extension Extras

31. 31
Is there any good book?