Difference between revisions of "OpenMP in Small Bites/NUMA"

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{{Infobox OpenMP in Small Bites}}
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[[Category:Tutorials|Non-Uniform Memory Access (NUMA) Effects in OpenMP]]<nowiki />
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{{DISPLAYTITLE:Non-Uniform Memory Access (NUMA) Effects in OpenMP}}<nowiki />
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{{Syllabus OpenMP in Small Bites}}<nowiki />
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__TOC__
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This video shows how a non-uniform memory access (NUMA) architecture influences the performance of OpenMP programs. It explains how distribute data and threads across NUMA domains and how to avoid uncontrolled data or thread migration.
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=== Video === <!--T:5-->
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<youtube width="600" height="340" right>MhlM-GiS1EM</youtube>
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([[Media:hpc.nrw_11_NUMA.pdf | Slides as pdf]])
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=== Quiz === <!--T:5--> 
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{{hidden begin
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|title = 1. Why is it important to initialize your data in parallel when executing on a NUMA architecture?
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}}
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<quiz display=simple>
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{
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|type="()"}
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+ Click and submit to see the answer
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|| Initializing the data in parallel distributes the date amoung the different sockets. When accessing the data in a hotspot region in the same pattern you avoid remote memory accesses.
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</quiz>
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{{hidden end}}
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{{hidden begin
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|title = 2. Why is it important to bind the threads?
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}}
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<quiz display=simple>
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{
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|type="()"}
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+ Click and submit to see the answer
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|| Otherwise the operating system might decide to migrate the thread from one core to anothers. This results in a performance penalty due to the context switch and a potential remote data access on NUMA architectures.
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</quiz>
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{{hidden end}}
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{{hidden begin
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|title = 3. Given a NUMA architecture with to two sockets with six cores each: How can you place the threads of an OpenMP program running with 4 threads among both sockets and bind them to a core?
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}}
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<quiz display=simple>
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{
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|type="()"}
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+ Click and submit to see the answer
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|| Set <code>OMP_PROC_BIND=spread</code> and <code>OMP_PLACES=cores</code>
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</quiz>
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{{hidden end}}

Latest revision as of 17:42, 4 December 2020

Tutorial
Title: OpenMP in Small Bites
Provider: HPC.NRW

Contact: tutorials@hpc.nrw
Type: Multi-part video
Topic Area: Programming Paradigms
License: CC-BY-SA
Syllabus

1. Overview
2. Worksharing
3. Data Scoping
4. False Sharing
5. Tasking
6. Tasking and Data Scoping
7. Tasking and Synchronization
8. Loops and Tasks
9. Tasking Example: Sudoku Solver
10. Task Scheduling
11. Non-Uniform Memory Access

This video shows how a non-uniform memory access (NUMA) architecture influences the performance of OpenMP programs. It explains how distribute data and threads across NUMA domains and how to avoid uncontrolled data or thread migration.

Video

( Slides as pdf)

Quiz

1. Why is it important to initialize your data in parallel when executing on a NUMA architecture?

Click and submit to see the answer

2. Why is it important to bind the threads?

Click and submit to see the answer

3. Given a NUMA architecture with to two sockets with six cores each: How can you place the threads of an OpenMP program running with 4 threads among both sockets and bind them to a core?

Click and submit to see the answer