CUDA GPU Programming Hands-on: Difference between revisions
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* Memory hierarchy/Shared Memory |
* Memory hierarchy/Shared Memory |
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== connection== |
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ssh -p24 gs135@gks-011.scc.kit.edu -X |
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ssh -p 22 proxy@ufo.kit.edu -L 110rc:yourmachine.ka.fzk.de:22 |
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in another terminal: |
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ssh -p24 gs135@gks-011.scc.kit.edu -X |
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ssh gs135@localhost -p 110rc -X |
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if (nasty message) |
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edit /home/gs135/.ssh/known_hosts |
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== Material == |
== Material == |
Revision as of 14:16, 29 August 2013
Introduction
While the computing community is racing to build tools and libraries to ease the use of these heterogeneous parallel computing systems, effective and confident use of these systems will always require knowledge about the low-level programming interfaces in these systems. This lecture is designed to introduce through examples and hands-on exercises, based on the CUDA programming language, the three abstractions that make the foundations of GPU programming:
- Thread hierarchy
- Synchronization
- Memory hierarchy/Shared Memory
connection
ssh -p24 gs135@gks-011.scc.kit.edu -X
ssh -p 22 proxy@ufo.kit.edu -L 110rc:yourmachine.ka.fzk.de:22
in another terminal:
ssh -p24 gs135@gks-011.scc.kit.edu -X
ssh gs135@localhost -p 110rc -X
if (nasty message)
edit /home/gs135/.ssh/known_hosts
Material
Reference
Programming Massively Parallel Processors: A Hands-on Approach By David Kirk and Wen-mei Hwu