Bit packing of array of integers
I have an array of integers, lets assume they are of type int64_t
. Now, I know that only every first n
bits of every integer are meaningful (that is, I know that they are limited by some bounds).
What is the most efficient way to convert the array in the way that all unnecessary space is removed (i.e. I have the first integer at a[0]
, the second one at a[0] + n bits
and so on) ?
I would like it to be general as开发者_JS百科 much as possible, because n
would vary from time to time, though I guess there might be smart optimizations for specific n
like powers of 2 or sth.
Of course I know that I can just iterate value over value, I just want to ask you StackOverflowers if you can think of some more clever way.
Edit:
This question is not about compressing the array to take as least space as possible. I just need to "cut" n bits
from every integer and given the array I know the exact n
of bits I can safely cut.
Today I released: PackedArray: Packing Unsigned Integers Tightly (github project).
It implements a random access container where items are packed at the bit-level. In other words, it acts as if you were able to manipulate a e.g. uint9_t
or uint17_t
array:
PackedArray principle:
. compact storage of <= 32 bits items
. items are tightly packed into a buffer of uint32_t integers
PackedArray requirements:
. you must know in advance how many bits are needed to hold a single item
. you must know in advance how many items you want to store
. when packing, behavior is undefined if items have more than bitsPerItem bits
PackedArray general in memory representation:
|-------------------------------------------------- - - -
| b0 | b1 | b2 |
|-------------------------------------------------- - - -
| i0 | i1 | i2 | i3 | i4 | i5 | i6 | i7 | i8 | i9 |
|-------------------------------------------------- - - -
. items are tightly packed together
. several items end up inside the same buffer cell, e.g. i0, i1, i2
. some items span two buffer cells, e.g. i3, i6
I agree with keraba that you need to use something like Huffman coding or perhaps the Lempel-Ziv-Welch algorithm. The problem with bit-packing the way you are talking about is that you have two options:
- Pick a constant n such that the largest integer can be represented.
- Allow n to vary from value to value.
The first option is relatively easy to implement, but is really going to waste a lot of space unless all integers are rather small.
The second option has the major disadvantage that you have to convey changes in n somehow in the output bitstream. For instance, each value will have to have a length associated with it. This means you are storing two integers (albeit smaller integers) for every input value. There's a good chance you'll increase the file size with this method.
The advantage of Huffman or LZW is that they create codebooks in such a way that the length of the codes can be derived from the output bitstream without actually storing the lengths. These techniques allow you to get very close to the Shannon limit.
I decided to give your original idea (constant n, remove unused bits and pack) a try for fun and here is the naive implementation I came up with:
#include <sys/types.h>
#include <stdio.h>
int pack(int64_t* input, int nin, void* output, int n)
{
int64_t inmask = 0;
unsigned char* pout = (unsigned char*)output;
int obit = 0;
int nout = 0;
*pout = 0;
for(int i=0; i<nin; i++)
{
inmask = (int64_t)1 << (n-1);
for(int k=0; k<n; k++)
{
if(obit>7)
{
obit = 0;
pout++;
*pout = 0;
}
*pout |= (((input[i] & inmask) >> (n-k-1)) << (7-obit));
inmask >>= 1;
obit++;
nout++;
}
}
return nout;
}
int unpack(void* input, int nbitsin, int64_t* output, int n)
{
unsigned char* pin = (unsigned char*)input;
int64_t* pout = output;
int nbits = nbitsin;
unsigned char inmask = 0x80;
int inbit = 0;
int nout = 0;
while(nbits > 0)
{
*pout = 0;
for(int i=0; i<n; i++)
{
if(inbit > 7)
{
pin++;
inbit = 0;
}
*pout |= ((int64_t)((*pin & (inmask >> inbit)) >> (7-inbit))) << (n-i-1);
inbit++;
}
pout++;
nbits -= n;
nout++;
}
return nout;
}
int main()
{
int64_t input[] = {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20};
int64_t output[21];
unsigned char compressed[21*8];
int n = 5;
int nbits = pack(input, 21, compressed, n);
int nout = unpack(compressed, nbits, output, n);
for(int i=0; i<=20; i++)
printf("input: %lld output: %lld\n", input[i], output[i]);
}
This is very inefficient because is steps one bit at a time, but that was the easiest way to implement it without dealing with issues of endianess. I have not tested this either with a wide range of values, just the ones in the test. Also, there is no bounds checking and it is assumed the output buffers are long enough. So what I am saying is that this code is probably only good for educational purposes to get you started.
Most any compression algorithm will get close to the minimum entropy needed to encode the integers, for example, Huffman coding, but accessing it like an array will be non-trivial.
Starting from Jason B's implementation, I eventually wrote my own version which processes bit-blocks instead of single bits. One difference is that it is lsb: It starts from lowest output bits going to highest. This only makes it harder to read with a binary dump, like Linux xxd -b
. As a detail, int*
can be trivially changed to int64_t*
, and it should even better be unsigned
. I have already tested this version with a few million arrays and it seems solid, so I share will the rest:
int pack2(int *input, int nin, unsigned char* output, int n)
{
int obit = 0;
int ibit = 0;
int ibite = 0;
int nout = 0;
if(nin>0) output[0] = 0;
for(int i=0; i<nin; i++)
{
ibit = 0;
while(ibit < n) {
ibite = std::min(n, ibit + 8 - obit);
output[nout] |= (input[i] & (((1 << ibite)-1) ^ ((1 << ibit)-1))) >> ibit << obit;
obit += ibite - ibit;
nout += obit >> 3;
if(obit & 8) output[nout] = 0;
obit &= 7;
ibit = ibite;
}
}
return nout;
}
int unpack2(int *oinput, int nin, unsigned char* ioutput, int n)
{
int obit = 0;
int ibit = 0;
int ibite = 0;
int nout = 0;
for(int i=0; i<nin; i++)
{
oinput[i] = 0;
ibit = 0;
while(ibit < n) {
ibite = std::min(n, ibit + 8 - obit);
oinput[i] |= (ioutput[nout] & (((1 << (ibite-ibit+obit))-1) ^ ((1 << obit)-1))) >> obit << ibit;
obit += ibite - ibit;
nout += obit >> 3;
obit &= 7;
ibit = ibite;
}
}
return nout;
}
I know this might seem like the obvious thing to say as I'm sure there's actually a solution, but why not use a smaller type, like uint8_t
(max 255)? or uint16_t
(max 65535)?. I'm sure you could bit-manipulate on an int64_t
using defined values and or operations and the like, but, aside from an academic exercise, why?
And on the note of academic exercises, Bit Twiddling Hacks is a good read.
If you have fixed sizes, e.g. you know your number is 38bit rather than 64, you can build structures using bit specifications. Amusing you also have smaller elements to fit in the remaining space.
struct example {
/* 64bit number cut into 3 different sized sections */
uint64_t big_num:38;
uint64_t small_num:16;
uint64_t itty_num:10;
/* 8 bit number cut in two */
uint8_t nibble_A:4;
uint8_t nibble_B:4;
};
This isn't big/little endian safe without some hoop-jumping, so can only be used within a program rather than in a exported data format. It's quite often used to store boolean values in single bits without defining shifts and masks.
I don't think you can avoid iterating across the elements. AFAIK Huffman encoding requires the frequencies of the "symbols", which unless you know the statistics of the "process" generating the integers, you will have to compute (by iterating across every element).
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