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CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step”

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Further reading 2

Caption notes

Swiss Tables replace pointer chains with open addressing, compact control bytes and SIMD scans. The performance tradeoffs depend on keys, loads and cache behavior.

Original passages · 6
this "what do we gain", "what do we lose"?
CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step” · ▶ 12:47–12:49
You get 16 probe length in three instructions. It's amazing.
CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step” · ▶ 31:12–31:16
But without running the data once, how do you know what dimensions are inconsequential?
CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step” · ▶ 20:19–20:25
they will rely upon it, given enough users.
CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step” · ▶ 5:27–5:32
We eliminate a memory interaction, on "find" and "insert".
CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step” · ▶ 12:43–12:47
You get 16 probe length in three instructions
CppCon 2017: Matt Kulukundis “Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step” · ▶ 31:12–31:14

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