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README.md

TurboPFor: Fastest Integer Compression Build Status

  • TurboPFor: The new synonym for "integer compression"
    • 🆕 (2019.11) ALL functions now available for 64 bits ARMv8 NEON & Power9 Altivec
    • 100% C (C++ headers), as simple as memcpy. OS:Linux amd64, arm64, Power9, MacOs
    • 👍 Java Critical Natives/JNI. Access TurboPFor incl. SIMD/AVX2! from Java as fast as calling from C
    • FULL range 8/16/32/64 bits scalar + 16/32/64 bits SIMD functions
    • No other "Integer Compression" compress/decompress faster
    • Direct Access, integrated (SIMD/AVX2) FOR/delta/Delta of Delta/Zigzag for sorted/unsorted arrays
    • 16 bits + 64 bits SIMD integrated functions
  • For/PFor/PForDelta
    • Novel TurboPFor (PFor/PForDelta) scheme w./ direct access + SIMD/AVX2. +RLE
    • Outstanding compression/speed. More efficient than ANY other fast "integer compression" scheme.
    • Compress 70 times faster and decompress up to 4 times faster than OptPFD
  • Bit Packing
    • Fastest and most efficient "SIMD Bit Packing" 10 Billions integers/sec (40Gb/s!)
    • Scalar "Bit Packing" decoding nearly as fast as SIMD-Packing in realistic (No "pure cache") scenarios
    • Direct/Random Access : Access any single bit packed entry with zero decompression
  • Variable byte
    • Scalar "Variable Byte" faster and more efficient than ANY other implementation
    • 🆕 (2019.11) SIMD TurboByte fastest group varint (16+32 bits) incl. integrated delta,zigzag,...
    • 🆕 (2019.11) TurboByte+TurboPackV novel hybrid scheme combining the fastest SIMD codecs.
  • Simple family
    • Novel "Variable Simple" (incl. RLE) faster and more efficient than simple16, simple-8b
  • Elias fano
    • Fastest "Elias Fano" implementation w/ or w/o SIMD/AVX2
  • Transform
    • Scalar & SIMD Transform: Delta, Zigzag, Zigzag of delta, XOR, Transpose/Shuffle,
    • lossy floating point compression with TurboPFor or TurboTranspose+lz77
  • Floating Point Compression
    • Delta/Zigzag + improved gorilla style + (Differential) Finite Context Method FCM/DFCM floating point compression
    • Using TurboPFor, unsurpassed compression and more than 5 GB/s throughput
    • Point wise relative error bound lossy floating point compression
    • 🆕 (2019.11) TurboFloat novel efficient floating point compression using TurboPFor
  • Time Series Compression
    • Fastest Gorilla 16/32/64 bits style compression (zigzag of delta + RLE).
    • can compress times series to only 0.01%. Speed > 10 GB/s compression and > 13 GB/s decompress.
  • Inverted Index ...do less, go fast!
    • Direct Access to compressed frequency and position data w/ zero decompression
    • Novel "Intersection w/ skip intervals", decompress the minimum necessary blocks (~10-15%)!.
    • Novel Implicit skips with zero extra overhead
    • Novel Efficient Bidirectional Inverted Index Architecture (forward/backwards traversal) incl. "integer compression".
    • more than 2000! queries per second on GOV2 dataset (25 millions documents) on a SINGLE core
    • Revolutionary Parallel Query Processing on Multicores > 7000!!! queries/sec on a simple quad core PC.
      ...forget Map Reduce, Hadoop, multi-node clusters, ...

Promo video

Integer Compression Benchmark (single thread):

- Synthetic data:
  • Generate and test (zipfian) skewed distribution (100.000.000 integers, Block size=128/256)
    Note: Unlike general purpose compression, a small fixed size (ex. 128 integers) is in general used in "integer compression". Large blocks involved, while processing queries (inverted index, search engines, databases, graphs, in memory computing,...) need to be entirely decoded.

     ./icbench -a1.5 -m0 -M255 -n100M ZIPF
    
C Size ratio% Bits/Integer C MB/s D MB/s Name 2019.11
62,939,886 15.7 5.04 2369 10950 TurboPFor256
63,392,759 15.8 5.07 1359 7803 TurboPFor128
63,392,801 15.8 5.07 1328 924 TurboPForDA
65,060,504 16.3 5.20 60 2748 FP_SIMDOptPFor
65,359,916 16.3 5.23 32 2436 PC_OptPFD
73,477,088 18.4 5.88 408 2484 PC_Simple16
73,481,096 18.4 5.88 624 8748 FP_SimdFastPFor 64Ki *
76,345,136 19.1 6.11 1072 2878 VSimple
91,947,533 23.0 7.36 284 11737 QMX 64k *
93,285,864 23.3 7.46 1568 10232 FP_GroupSimple 64Ki *
95,915,096 24.0 7.67 848 3832 Simple-8b
99,910,930 25.0 7.99 17298 12408 TurboByte+TurboPack
99,910,930 25.0 7.99 17357 12363 TurboPackV sse
99,910,930 25.0 7.99 11694 10138 TurboPack scalar
99,910,930 25.0 7.99 8420 8876 TurboFor
100,332,929 25.1 8.03 17077 11170 TurboPack256V avx2
101,015,650 25.3 8.08 11191 10333 TurboVByte
102,074,663 25.5 8.17 6689 9524 MaskedVByte
102,074,663 25.5 8.17 2260 4208 PC_Vbyte
102,083,036 25.5 8.17 5200 4268 FP_VByte
112,500,000 28.1 9.00 1528 12140 VarintG8IU
125,000,000 31.2 10.00 13039 12366 TurboByte
125,000,000 31.2 10.00 11197 11984 StreamVbyte 2019
400,000,000 100.00 32.00 8960 8948 Copy
N/A N/A EliasFano

(*) codecs inefficient for small block sizes are tested with 64Ki integers/block.

  • MB/s: 1.000.000 bytes/second. 1000 MB/s = 1 GB/s
  • #BOLD = pareto frontier.
  • FP=FastPFor SC:simdcomp PC:Polycom
  • TurboPForDA,TurboForDA: Direct Access is normally used when accessing few individual values.
  • Eliasfano can be directly used only for increasing sequences

- Data files:
  • gov2.sorted from DocId data set Block size=128/Delta coding

     ./icbench -fS -r gov2.sorted
    

Speed/Ratio

Size Ratio % Bits/Integer C Time MB/s D Time MB/s Function 2019.11
3,321,663,893 13.9 4.44 1320 6088 TurboPFor
3,339,730,557 14.0 4.47 32 2144 PC.OptPFD
3,350,717,959 14.0 4.48 1536 7128 TurboPFor256
3,501,671,314 14.6 4.68 56 2840 VSimple
3,768,146,467 15.8 5.04 3228 3652 EliasFanoV
3,822,161,885 16.0 5.11 572 2444 PC_Simple16
4,411,714,936 18.4 5.90 9304 10444 TurboByte+TurboPack
4,521,326,518 18.9 6.05 836 3296 Simple-8b
4,649,671,427 19.4 6.22 3084 3848 TurboVbyte
4,955,740,045 20.7 6.63 7064 10268 TurboPackV
4,955,740,045 20.7 6.63 5724 8020 TurboPack
5,205,324,760 21.8 6.96 6952 9488 SC_SIMDPack128
5,393,769,503 22.5 7.21 14466 11902 TurboPackV256
6,221,886,390 26.0 8.32 6668 6952 TurboFor
6,221,886,390 26.0 8.32 6644 2260 TurboForDA
6,699,519,000 28.0 8.96 1888 1980 FP_Vbyte
6,700,989,563 28.0 8.96 2740 3384 MaskedVByte
7,622,896,878 31.9 10.20 836 4792 VarintG8IU
8,060,125,035 33.7 11.50 8456 9476 Streamvbyte 2019
8,594,342,216 35.9 11.50 5228 6376 libfor
23,918,861,764 100.0 32.00 5824 5924 Copy

Block size: 64Ki = 256k bytes. Ki=1024 Integers

Size Ratio % Bits/Integer C Time MB/s D Time MB/s Function
3,164,940,562 13.2 4.23 1344 6004 TurboPFor 64Ki
3,273,213,464 13.7 4.38 1496 7008 TurboPFor256 64Ki
3,965,982,954 16.6 5.30 1520 2452 lz4+DT 64Ki
4,234,154,427 17.7 5.66 436 5672 qmx 64Ki
6,074,995,117 25.4 8.13 1976 2916 blosc_lz4 64Ki
8,773,150,644 36.7 11.74 2548 5204 blosc_lz 64Ki

"lz4+DT 64Ki" = Delta+Transpose from TurboPFor + lz4
"blosc_lz4" internal lz4 compressor+vectorized shuffle

- Time Series:
Function C MB/s size ratio% D MB/s Text
bvzenc32 10632 45,909 0.008 12823 ZigZag
bvzzenc32 8914 56,713 0.010 13499 ZigZag Delta of delta
vsenc32 12294 140,400 0.024 12877 Variable Simple
p4nzenc256v32 1932 596,018 0.10 13326 TurboPFor256 ZigZag
p4ndenc256v32 1961 596,018 0.10 13339 TurboPFor256 Delta
bitndpack256v32 12564 909,189 0.16 13505 TurboPackV256 Delta
p4nzenc32 1810 1,159,633 0.20 8502 TurboPFor ZigZag
p4nzenc128v32 1795 1,159,633 0.20 13338 TurboPFor ZigZag
bitnzpack256v32 9651 1,254,757 0.22 13503 TurboPackV256 ZigZag
bitnzpack128v32 10155 1,472,804 0.26 13380 TurboPackV ZigZag
vbddenc32 6198 18,057,296 3.13 10982 TurboVByte Delta of delta
memcpy 13397 577,141,992 100.00
- Transpose/Shuffle (no compression)
    ./icbench -eTRANSFORM ZIPF
Size C Time MB/s D Time MB/s Function
100,000,000 9400 9132 TPbyte 4 TurboPFor Byte Transpose/shuffle AVX2
100,000,000 8784 8860 TPbyte 4 TurboPFor Byte Transpose/shuffle SSE
100,000,000 7688 7656 Blosc_Shuffle AVX2
100,000,000 5204 7460 TPnibble 4 TurboPFor Nibble Transpose/shuffle SSE
100,000,000 6620 6284 Blosc shuffle SSE
100,000,000 3156 3372 Bitshuffle AVX2
100,000,000 2100 2176 Bitshuffle SSE
- (Lossy) Floating point compression:
    ./icapp -Fd file          " 64 bits floating point raw file 
    ./icapp -Ff file          " 32 bits floating point raw file 
    ./icapp -Fcf file         " text file with miltiple entries (ex.  8.657,56.8,4.5 ...)
    ./icapp -Ftf file         " text file (1 entry per line)
    ./icapp -Ftf file -v5     " + display the first entries read
    ./icapp -Ftf file.csv -K3 " but 3th column in a csv file (ex. number,Text,456.5 -> 456.5
    ./icapp -Ftf file -g.001  " lossy compression with allowed pointwise relative error 0.001
- Compressed Inverted Index Intersections with GOV2

GOV2: 426GB, 25 Millions documents, average doc. size=18k.

  • Aol query log: 18.000 queries
    ~1300 queries per second (single core)
    ~5000 queries per second (quad core)
    Ratio = 14.37% Decoded/Total Integers.

  • TREC Million Query Track (1MQT):
    ~1100 queries per second (Single core)
    ~4500 queries per second (Quad core CPU)
    Ratio = 11.59% Decoded/Total Integers.

  • Benchmarking intersections (Single core, AOL query log)
max.docid/q Time s q/s ms/q % docid found
1.000 7.88 2283.1 0.438 81
10.000 10.54 1708.5 0.585 84
ALL 13.96 1289.0 0.776 100
q/s: queries/second, ms/q:milliseconds/query
  • Benchmarking Parallel Query Processing (Quad core, AOL query log)
max.docid/q Time s q/s ms/q % docids found
1.000 2.66 6772.6 0.148 81
10.000 3.39 5307.5 0.188 84
ALL 3.57 5036.5 0.199 100
Notes:

Compile:

    Download or clone TurboPFor
	git clone git://github.com/powturbo/TurboPFor.git
	cd TurboPFor
	make
    

    To benchmark external libraries + lz77 compression:
	git clone --recursive git://github.com/powturbo/TurboPFor.git
	cd TurboPFor
    make CODEC1=1 CODEC2=1 LZ=1
Windows visual c++
	nmake /f makefile.vs
Windows visual studio c++
    project files under vs/vs2017

Testing:

- Synthetic data (use ZIPF parameter):
  • benchmark groups of "integer compression" functions

    ./icbench -eBENCH -a1.2 -m0 -M255 -n100M ZIPF
    ./icbench -eBITPACK/VBYTE -a1.2 -m0 -M255 -n100M ZIPF
    

Type "icbench -l1" for a list

-zipfian distribution alpha = 1.2 (Ex. -a1.0=uniform -a1.5=skewed distribution)
-number of integers = 100.000.000
-integer range from 0 to 255

  • Unsorted lists: individual function test (ex. Copy TurboPack TurboPFor)

    ./icbench -a1.5 -m0 -M255 -ecopy/turbopack/turbopfor/turbopack256v ZIPF
    
  • Unsorted lists: Zigzag encoding w/ option -fz or FOR encoding

    ./icbench -fz -eturbovbyte/turbopfor/turbopackv ZIPF
    ./icbench -eturboforv ZIPF
    
  • Sorted lists: differential coding w/ option -fs (increasing) or -fS (strictly increasing)

    ./icbench -fs -eturbopack/turbopfor/turbopfor256v ZIPF
    
  • Generate interactive "file.html" plot for browsing

    ./icbench -p2 -S2 -Q3 file.tbb
    
  • Unit test: test function from bit size 0 to 32

    ./icbench -m0 -M32 -eturbpfor -fu 
    ./icbench -m0 -M8 -eturbopack -fs -n1M 
    
- Data files:
  • Raw 32 bits binary data file Test data

    ./icbench file
    ./icapp file           
    ./icapp -Fs file         "16 bits raw binary file
    ./icapp -Fu file         "32 bits raw binary file
    ./icapp -Fl file         "64 bits raw binary file
    ./icapp -Ff file         "32 bits raw floating point binary file
    ./icapp -Fd file         "64 bits raw floating point binary file
    
  • Text file: 1 entry per line. Test data: ts.txt(sorted) and lat.txt(unsorted))

    ./icbench -eBENCH -fts ts.txt
    ./icbench -eBENCH -ft  lat.txt
    
    ./icapp -Fts data.txt            "text file, one 16 bits integer per line
    ./icapp -Ftu ts.txt              "text file, one 32 bits integer per line
    ./icapp -Ftl ts.txt              "text file, one 64 bits integer per line
    ./icapp -Ftf file                "text file, one 32 bits floating point (ex. 8.32456) per line
    ./icapp -Ftd file                "text file, one 64 bits floating point (ex. 8.324567789) per line
    ./icapp -Ftd file -v5            "like prev., display the first 100 values read
    ./icapp -Ftd file -v5 -g.00001   "like prev., error bound lossy floating point compression
    ./icapp -Ftt file                "text file, timestamp in seconds iso-8601 -> 32 bits integer (ex. 2018-03-12T04:31:06)
    ./icapp -FtT file                "text file, timestamp in milliseconds iso-8601 -> 64 bits integer (ex. 2018-03-12T04:31:06.345)
    ./icapp -Ftl -D2 -H file         "skip 1th line, convert numbers with 2 decimal digits to 64 bits integers (ex. 456.23 -> 45623)
    ./icapp -Ftl -D2 -H -K3 file.csv  "like prev., use the 3th number in the line (ex. label=3245, text=99 usage=456.23 -> 456.23 )
    ./icapp -Ftl -D2 -H -K3 -k| file.csv "like prev., use '|' as separator
    
  • Text file: multiple numbers separated by non-digits (0..9,-,.) characters (ex. 134534,-45678,98788,4345, )

    ./icapp -Fc data.txt         "text file, 32 bits integers (ex. 56789,3245,23,678 ) 
    ./icapp -Fcd data.txt        "text file, 64 bits floting-point numbers (ex. 34.7689,5.20,45.789 )
    
  • Multiblocks of 32 bits binary file. (Example gov2 from DocId data set)
    Block format: [n1: #of Ids][Id1] [Id2]...[IdN] [n2: #of Ids][Id1][Id2]...[IdN]...

    ./icbench -fS -r gov2.sorted
    
- Intersections:

1 - Download Gov2 (or ClueWeb09) + query files (Ex. "1mq.txt") from DocId data set
8GB RAM required (16GB recommended for benchmarking "clueweb09" files).

2 - Create index file

    ./idxcr gov2.sorted .

create inverted index file "gov2.sorted.i" in the current directory

3 - Test intersections

    ./idxqry gov2.sorted.i 1mq.txt

run queries in file "1mq.txt" over the index of gov2 file

- Parallel Query Processing:

1 - Create partitions

    ./idxseg gov2.sorted . -26m -s8

create 8 (CPU hardware threads) partitions for a total of ~26 millions document ids

2 - Create index file for each partition

  ./idxcr gov2.sorted.s*

create inverted index file for all partitions "gov2.sorted.s00 - gov2.sorted.s07" in the current directory

3 - Intersections:

delete "idxqry.o" file and then type "make para" to compile "idxqry" w. multithreading

  ./idxqry gov2.sorted.s*.i 1mq.txt

run queries in file "1mq.txt" over the index of all gov2 partitions "gov2.sorted.s00.i - gov2.sorted.s07.i".

Function usage:

See benchmark "icbench" program for "integer compression" usage examples. In general encoding/decoding functions are of the form:

char *endptr = encode( unsigned *in, unsigned n, char *out, [unsigned start], [int b])
endptr : set by encode to the next character in "out" after the encoded buffer
in : input integer array
n : number of elements
out : pointer to output buffer
b : number of bits. Only for bit packing functions
start : previous value. Only for integrated delta encoding functions

char *endptr = decode( char *in, unsigned n, unsigned *out, [unsigned start], [int b])
endptr : set by decode to the next character in "in" after the decoded buffer
in : pointer to input buffer
n : number of elements
out : output integer array
b : number of bits. Only for bit unpacking functions
start : previous value. Only for integrated delta decoding functions

Simple high level functions:

size_t compressed_size = encode( unsigned *in, size_t n, char *out)
compressed_size : number of bytes written into compressed output buffer out

size_t compressed_size = decode( char *in, size_t n, unsigned *out)
compressed_size : number of bytes read from compressed input buffer in

Function syntax:

  • {vb | p4 | bit | vs}[n][d | d1 | f | fm | z ]{enc/dec | pack/unpack}[| 128V | 256V][8 | 16 | 32 | 64]:
    vb: variable byte
    p4: turbopfor
    vs: variable simple
    bit: bit packing
    n : high level array functions for large arrays.

    '' : encoding for unsorted integer lists
    'd' : delta encoding for increasing integer lists (sorted w/ duplicate)
    'd1': delta encoding for strictly increasing integer lists (sorted unique)
    'f' : FOR encoding for sorted integer lists
    'z' : ZigZag encoding for unsorted integer lists

    'enc' or 'pack' : encode or bitpack
    'dec' or 'unpack': decode or bitunpack
    'NN' : integer size (8/16/32/64)

header files to use with documentation:

c/c++ header file Integer Compression functions examples
vint.h variable byte vbenc32/vbdec32 vbdenc32/vbddec32 vbzenc32/vbzdec32
vsimple.h variable simple vsenc64/vsdec64
vp4.h TurboPFor p4enc32/p4dec32 p4denc32/p4ddec32 p4zenc32/p4zdec32
bitpack.h Bit Packing, For, +Direct Access bitpack256v32/bitunpack256v32 bitforenc64/bitfordec64
eliasfano.h Elias Fano efanoenc256v32/efanoc256v32

Note: Some low level functions (like p4enc32) are limited to 128/256 (SSE/AVX2) integers per call.

Environment:

OS/Compiler (64 bits):
  • Windows: MinGW-w64 makefile
  • Windows: Visual c++ (>=VS2008) - makefile.vs (for nmake)
  • Windows: Visual Studio project file - vs/vs2017 - Thanks to PavelP
  • Linux amd64: GNU GCC (>=4.6)
  • Linux amd64: Clang (>=3.2)
  • Linux arm64: 64 bits aarch64 ARMv8: gcc (>=6.3)
  • Linux arm64: 64 bits aarch64 ARMv8: clang
  • MaxOS: XCode (>=9)
  • PowerPC ppc64le (incl. SIMD): gcc (>=8.0)
Multithreading:
  • All TurboPFor integer compression functions are thread safe

References:

Last update: 20 Aug 2020

APPENDIX: icbench Integer Compression Benchmark

TurboPFor + external libraries
TurboPFor               	https://github.com/powturbo/TurboPFor
FastPFor (FP)              	https://github.com/lemire/FastPFor
lz4				https://github.com/Cyan4973/lz4
LittleIntPacker (LI)       	https://github.com/lemire/LittleIntPacker
MaskedVbyte             	http://maskedvbyte.org
Polycom (PC)               	https://github.com/encode84/bcm
simdcomp (SC)              	https://github.com/lemire/simdcomp
Simple-8b optimized     	https://github.com/powturbo/TurboPFor
Streamvbyte             	https://github.com/lemire/streamvbyte
VarintG8IU              	https://github.com/lemire/FastPFor
Functions integrated into 'icbench' for benchmarking
Codec group:
TURBOPFOR        TurboPFor library TurboPFor256V/TurboPack256V/TurboPFor256N/TurboPFor/TurboPackV/TurboVByte/TurboPack/TurboForDA/EliasFano/VSimple/TurboPForN/TurboPackN/TurboPForDI
DEFAULT          Default TurboPFor/TurboPackV/TurboVByte/TurboPack/TurboFor/TurboPForN/TurboPackN/TurboPForDI/TurboPFor256V/TurboPack256V/TurboPFor256N
BENCH            Benchmark TurboPFor/TurboPackV/TurboVByte/TurboPack/QMX/FP.SimdFastPfor/FP.SimdOptPFor/MaskedVbyte/StreamVbyte
EFFICIENT        Efficient TurboPFor/vsimple/turbovbyte
TRANSFORM        transpose/shufle,delta,zigzag tpbyte4s/tpbyte,4/tpnibble,4/ZigZag_32/Delta_32/BitShuffle,4
BITPACK          Bit Packing TurboPack256V/TurboPackV/TurboPackH/TurboPack/SC.SimdPack128/SC.SimdPack256
VBYTE            Variable byte TurboVByte/FP.VByte/PC.Vbyte/VarintG8IU/MaskedVbyte/StreamVbyte
SIMPLE           Simple Family simple8b/simple16/vsimple/qmx
LZ4              lz4+bitshufle/transpose 4,8 lz4_bitshufle/lz4_tp4/lz4_tp8
LI               Little Integer LI_Pack/LI_TurboPack/LI_SuperPack/LI_HorPack


Function         Description                                      level

--------         -----------                                      -----
TurboPFor        PFor (SSE2)
TurboPForN       PFor (SSE2) large blocks
TurboPFor256     PFor (AVX2)
TurboPFor256N    PFor (AVX2) large blocks
TurboPForDA      PFor direct access
TurboPForDI      PFord min
TurboPForZZ      PFor zigzag of delta
TurboFor         FOR
TurboForV        FOR (SIMD)
TurboFor256V     FOR (AVX2)
TurboForDA       FOR direct access
TurboPackDA      Bit packing direct access
TurboPack        Bit packing (scalar)
TurboPackN       Bit packing (scalar) large blocks
TurboPackV       Bit packing (SSE2 Vertical)
TurboPackH       Bit packing (SSE2 Horizontal)
TurboPackVN      Bit packing (SSE2 large block)
TurboPack256V    Bit packing (AVX2 Vertical)
TurboPack256N    Bit packing (AVX2 large block)
TurboVByte       Variable byte (scalar)
VSimple          Variable simple (scalar)
EliasFano        Elias fano (scalar)
EliasFanoV       Eliasfano  (SSE2)
EliasFano256V    Elias fano (AVX2)
memcpy           memcpy
copy             Integer copy
tpbyte4s         Byte Transpose (scalar)
tpbyte           Byte transpose (simd)  2,4,8
tpnibble         Nibble transpose (simd)  2,4,8
ZigZag32         ZigZag encoding (sse2)
Delta32          Delta encoding (sse2)
DDelta32         Delta of delta encoding (sse2)
Xor32            Xor encoding (sse2)
FP_PREV64        Floating point PFOR
FP_FCM64         Floating point PFOR (FCM)
FP_DFCM64        Floating point PFOR (DFCM)
TurboPFor64      PFOR 64
TurboPFor64V     PFOR 64
Simple8b         64 bits Simple family (instable)
PC_Simple16      Simple 16. limited to 28 bits
PC_OptPFD        OptPFD. limited to 28 bits
PC_Vbyte         Variable byte
PC_Rice          Rice coding (instable)
VarintG8IU       Variable byte SIMD
MaskedVbyte      Variable byte SIMD
StreamVbyte      Variable byte SIMD
FP_FastPFor      PFor scalar (inefficient for small blocks)
FP_SimdFastPFor  PFor SIMD (inefficient for small blocks)
FP_OptPFor       OptPFor scalar 
FP_SIMDOptPFor   OptPFor SIMD
FP_VByte         Variable byte
FP_Simple8bRLE   Simple-8b + rle
FP_GROUPSIMPLE   Group Simple
SC_SIMDPack128   Bit packing (SSE4.1)
SC_SIMDPack256   Bit packing (SSE4.1)
SC_For           For (SSE4.1)
SC_ForDA         For direct access (SSE4.1)
LibFor_For       For
LibFor_ForDA     For direct access
LI_Pack          Bit packing (scalar)
LI_TurboPack     Bit packing (scalar)
LI_SuperPack     Bit packing (scalar)
LI_HorPack       Bit packing (sse4.1 horizontal) 
LI_BMIPack256    Bit packing (avx2)
lz4              lz4
lz4_bit          Bitshuffle + [delta]+lz4 2,4,8
lz4_nibble       TurboPFor's [delta]+nibble transpose + lz4 2,4,8
lz4_bitxor       Bitshuffle + [xor]+lz4 2,4,8
lz4_nibblexor    TurboPFor's [xor]+nibble transpose + lz4 2,4,8
lz4_byte         TurboPFor's [delta]+byte transpose + lz4 2,4,8
BitShuffle       Bit shuffle (simd) 2,4,8
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