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README.md
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README.md
@ -3,10 +3,10 @@ TurboPFor: Fastest Integer Compression [, as simple as memcpy
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* :+1: **Java** Critical Natives/JNI. Access TurboPFor **incl. SIMD/AVX2!** from Java as fast as calling from C
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* :sparkles: **FULL** range 8/16/32/64 bits scalar + 16/32 bits SIMD functions
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* :sparkles: **FULL** range 8/16/32/64 bits scalar + 16/32/64 bits SIMD functions
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* No other "Integer Compression" compress/decompress faster
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* :sparkles: Direct Access, **integrated** (SIMD/AVX2) FOR/delta/Zigzag for sorted/unsorted arrays
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* :new: **16 bits** SIMD integrated functions
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* :new: **16 bits** + **64 bits** SIMD integrated functions
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* **For/PFor/PForDelta**
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* **Novel TurboPFor** (PFor/PForDelta) scheme w./ **direct access** + **SIMD/AVX2**.
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* Outstanding compression/speed. More efficient than **ANY** other fast "integer compression" scheme.
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@ -24,8 +24,8 @@ TurboPFor: Fastest Integer Compression [ Finite Context Method FCM/DFCM floating point compression
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* Using **TurboPFor**, more than 2 GB/s throughput
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* Delta/Delta of delta + (Differential) Finite Context Method FCM/DFCM floating point compression
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* Using **TurboPFor**, unsurpassed compression and more than 5 GB/s throughput
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* **Inverted Index ...do less, go fast!**
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* Direct Access to compressed *frequency* and *position* data w/ zero decompression
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* **Novel** **"Intersection w/ skip intervals"**, decompress the minimum necessary blocks (**~10-15%)!**.
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@ -385,5 +385,5 @@ header files to use with documentation:<br />
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* [Small Polygon Compression](https://arxiv.org/abs/1509.05505) + [Poster](http://abhinavjauhri.me/publications/dcc_poster_2016.pdf) + [code](https://github.com/ajauhri/bignum_compression)
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* [Parallel Graph Analysis (Lecture 18)](http://www.cs.rpi.edu/~slotag/classes/FA16/) + [code](http://www.cs.rpi.edu/~slotag/classes/FA16/handson/lec18-comp2.cpp)
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Last update: 21 Jan 2018
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Last update: 05 Feb 2018
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