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johnj/llds

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Low-Level Data Structure - efficient data structures, and fast data access in the 3.x/4.x/5.x/6.x kernel

9 mentions on Hacker News by 1 person: 2 stories, 7 comments · first 2012-05-30 · latest 2018-01-03

Mentions per year 9 mentions · busiest year 2012 (5)
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  1. …the past it has been reserved for use cases like search engines with massive in-memory trees. [1] https://github.com/johnj/llds
  2. Supporting benchmarks that might be interesting alongside the OP: https://github.com/johnj/llds#wall-timings-in-seconds Same concept applies, reducing translations for page lookups reduces latency.
    comment by zippie · 2014-02-23 · in How Bad Can 1 GB Pages Be?
  3. There is, of sorts (rbtree), http://github.com/johnj/llds
  4. …I've run into this problem with our btree search indexes on bare metal (~96GB), some more reading: https://github.com/johnj/llds
  5. …prefetching on modern processors with large data structures (usually limited to L1d cache lines): https://github.com/johnj/llds#l1-data-prefetch-misses-200000... A plausible analogy for CPU prefetching would be "readahead" mechanisms…
  6. …for instance treats cache lines as registers and heavily optimizes for cache friendly operations: https://github.com/johnj/llds
    comment by zippie · 2012-09-02 · in Cache Lines Are The New Registers
  7. ▲ 59
    Virtual memory overhead for trees
    story by zippie · 2012-08-04 · 19 comments
  8. …memory access. We used Low-Level Data Structure to get the 2x improvements in memory latency: https://github.com/johnj/llds
  9. ▲ 2
    Llds: Low-Level Data Structure
    story by zippie · 2012-05-30 · 0 comments