Daniel Lemire's blog

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Decoding over 4 billion integers per second in C

8 thoughts on “Decoding over 4 billion integers per second in C”

  1. Alecco says:

    Excellent. Very easy to use! Thanks!

  2. anonymous says:

    Has FastPFOR been used/evaluated in a real contex such as lucene text search?

  3. @anonymous

    Lucene uses what is effectively the FastPFOR algorithm inspired by the JavaFastPFOR library. As for using the C++ library, I do not know if it is practical since Lucene is written in Java.

  4. powturbo says:

    In my tests SIMD bitpacking offer no speed advantage over optimized scalar bitpacking when used with large buffers (see simplebenchmark in FastPFor). This is valable for most applications (ex. inverted index). A realistic benchmark should compare SIMD/Scalar bitpacking only on large buffers.

  5. @powturbo

    If you are going to take the data from RAM, bring it all the way to L1 cache, load it in registers, then push it out all the back to RAM… you are IO bound… your CPU runs empty and so, saving CPU cycles becomes irrelevant. To make things worse, you can pretty much forget about using more than one core because your L3 cache is going to be overwhelmed by one core.

    So? So you avoid decompressing whole arrays to RAM.

    We have demonstrated directly the benefit of SIMD bit packing in our latest paper (see http://arxiv.org/abs/1401.6399).

  6. Garen says:

    If you’re out of disk-space, is there a way to handle updates in a way that won’t require additional scratch space?

  7. @Garen

    This particular library does not handle disk storage at all (by design). However, there is no particular problem with updates and this library. In fact, it compresses super fast so recompressing updating blocks should be quite fast.