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I have a sparse array a (mostly zeroes):
unsigned char a[1000000];
and I would like to create an array b of indexes to non-zero elements of a using SIMD instructions on Intel x64 architecture with AVX2. I'm looking for tips how to do it efficiently. Specifically, are there SIMD instruction(s) to get positions of consecutive non-zero elements in SIMD register, arranged contiguously?
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Five methods to compute the indices of the nonzeros are:
Semi vectorized loop: Load a SIMD vector with chars, compare with zero and apply a movemask. Use a small scalar loop if any of the chars is nonzero
(also suggested by @stgatilov). This works well for very sparse arrays. Function arr2ind_movmsk in the code below uses BMI1 instructions
for the scalar loop.
Vectorized loop: Intel Haswell processors and newer support the BMI1 and BMI2 instruction sets. BMI2 contains
the pext instruction (Parallel bits extract, see wikipedia link),
which turns out to be useful here. See arr2ind_pext in the code below.
Classic scalar loop with if statement: arr2ind_if.
Scalar loop without branches: arr2ind_cmov.
Lookup table: @stgatilov shows that it is possible to use a lookup table instead of the pdep and other integer instructions. This might work well, however, the lookup table is quite large: it doesn't fit in the L1 cache. Not tested here. See also the discussion here.
/*
gcc -O3 -Wall -m64 -mavx2 -fopenmp -march=broadwell -std=c99 -falign-loops=16 sprs_char2ind.c
example: Test different methods with an array a of size 20000 and approximate 25/1024*100%=2.4% nonzeros:
./a.out 20000 25
*/
#include <stdio.h>
#include <immintrin.h>
#include <stdint.h>
#include <omp.h>
#include <string.h>
__attribute__ ((noinline)) int arr2ind_movmsk(const unsigned char * restrict a, int n, int * restrict ind, int * m){
int i, m0, k;
__m256i msk;
m0=0;
for (i=0;i<n;i=i+32){ /* Load 32 bytes and compare with zero: */
msk=_mm256_cmpeq_epi8(_mm256_load_si256((__m256i *)&a[i]),_mm256_setzero_si256());
k=_mm256_movemask_epi8(msk);
k=~k; /* Search for nonzero bits instead of zero bits. */
while (k){
ind[m0]=i+_tzcnt_u32(k); /* Count the number of trailing zero bits in k. */
m0++;
k=_blsr_u32(k); /* Clear the lowest set bit in k. */
}
}
*m=m0;
return 0;
}
__attribute__ ((noinline)) int arr2ind_pext(const unsigned char * restrict a, int n, int * restrict ind, int * m){
int i, m0;
uint64_t cntr_const = 0xFEDCBA9876543210;
__m256i shft = _mm256_set_epi64x(0x04,0x00,0x04,0x00);
__m256i vmsk = _mm256_set1_epi8(0x0F);
__m256i cnst16 = _mm256_set1_epi32(16);
__m256i shf_lo = _mm256_set_epi8(0x80,0x80,0x80,0x0B, 0x80,0x80,0x80,0x03, 0x80,0x80,0x80,0x0A, 0x80,0x80,0x80,0x02,
0x80,0x80,0x80,0x09, 0x80,0x80,0x80,0x01, 0x80,0x80,0x80,0x08, 0x80,0x80,0x80,0x00);
__m256i shf_hi = _mm256_set_epi8(0x80,0x80,0x80,0x0F, 0x80,0x80,0x80,0x07, 0x80,0x80,0x80,0x0E, 0x80,0x80,0x80,0x06,
0x80,0x80,0x80,0x0D, 0x80,0x80,0x80,0x05, 0x80,0x80,0x80,0x0C, 0x80,0x80,0x80,0x04);
__m128i pshufbcnst = _mm_set_epi8(0x80,0x80,0x80,0x80,0x80,0x80,0x80,0x80, 0x0E,0x0C,0x0A,0x08,0x06,0x04,0x02,0x00);
__m256i i_vec = _mm256_setzero_si256();
m0=0;
for (i=0;i<n;i=i+16){
__m128i v = _mm_load_si128((__m128i *)&a[i]); /* Load 16 bytes. */
__m128i msk = _mm_cmpeq_epi8(v,_mm_setzero_si128()); /* Generate 16x8 bit mask. */
msk = _mm_srli_epi64(msk,4); /* Pack 16x8 bit mask to 16x4 bit mask. */
msk = _mm_shuffle_epi8(msk,pshufbcnst); /* Pack 16x8 bit mask to 16x4 bit mask. */
msk = _mm_xor_si128(msk,_mm_set1_epi32(-1)); /* Invert 16x4 mask. */
uint64_t msk64 = _mm_cvtsi128_si64x(msk); /* _mm_popcnt_u64 and _pext_u64 work on 64-bit general-purpose registers, not on simd registers.*/
int p = _mm_popcnt_u64(msk64)>>2; /* p is the number of nonzeros in 16 bytes of a. */
uint64_t cntr = _pext_u64(cntr_const,msk64); /* parallel bits extract. cntr contains p 4-bit integers. The 16 4-bit integers in cntr_const are shuffled to the p 4-bit integers that we want */
/* The next 7 intrinsics unpack these p 4-bit integers to p 32-bit integers. */
__m256i cntr256 = _mm256_set1_epi64x(cntr);
cntr256 = _mm256_srlv_epi64(cntr256,shft);
cntr256 = _mm256_and_si256(cntr256,vmsk);
__m256i cntr256_lo = _mm256_shuffle_epi8(cntr256,shf_lo);
__m256i cntr256_hi = _mm256_shuffle_epi8(cntr256,shf_hi);
cntr256_lo = _mm256_add_epi32(i_vec,cntr256_lo);
cntr256_hi = _mm256_add_epi32(i_vec,cntr256_hi);
_mm256_storeu_si256((__m256i *)&ind[m0],cntr256_lo); /* Note that the stores of iteration i and i+16 may overlap. */
_mm256_storeu_si256((__m256i *)&ind[m0+8],cntr256_hi); /* Array ind has to be large enough to avoid segfaults. At most 16 integers are written more than strictly necessary */
m0 = m0+p;
i_vec = _mm256_add_epi32(i_vec,cnst16);
}
*m=m0;
return 0;
}
__attribute__ ((noinline)) int arr2ind_if(const unsigned char * restrict a, int n, int * restrict ind, int * m){
int i, m0;
m0=0;
for (i=0;i<n;i++){
if (a[i]!=0){
ind[m0]=i;
m0=m0+1;
}
}
*m=m0;
return 0;
}
__attribute__((noinline)) int arr2ind_cmov(const unsigned char * restrict a, int n, int * restrict ind, int * m){
int i, m0;
m0=0;
for (i=0;i<n;i++){
ind[m0]=i;
m0=(a[i]==0)? m0 : m0+1; /* Compiles to cmov instruction. */
}
*m=m0;
return 0;
}
__attribute__ ((noinline)) int print_nonz(const unsigned char * restrict a, const int * restrict ind, const int m){
int i;
for (i=0;i<m;i++) printf("i=%d, ind[i]=%d a[ind[i]]=%u\n",i,ind[i],a[ind[i]]);
printf("\n"); fflush( stdout );
return 0;
}
__attribute__ ((noinline)) int print_chk(const unsigned char * restrict a, const int * restrict ind, const int m){
int i; /* Compute a hash to compare the results of different methods. */
unsigned int chk=0;
for (i=0;i<m;i++){
chk=((chk<<1)|(chk>>31))^(ind[i]);
}
printf("chk = %10X\n",chk);
return 0;
}
int main(int argc, char **argv){
int n, i, m;
unsigned int j, k, d;
unsigned char *a;
int *ind;
double t0,t1;
int meth, nrep;
char txt[30];
sscanf(argv[1],"%d",&n); /* Length of array a. */
n=n>>5; /* Adjust n to a multiple of 32. */
n=n<<5;
sscanf(argv[2],"%u",&d); /* The approximate fraction of nonzeros in a is: d/1024 */
printf("n=%d, d=%u\n",n,d);
a=_mm_malloc(n*sizeof(char),32);
ind=_mm_malloc(n*sizeof(int),32);
/* Generate a pseudo random array a. */
j=73659343;
for (i=0;i<n;i++){
j=j*653+1;
k=(j & 0x3FF00)>>8; /* k is a pseudo random number between 0 and 1023 */
if (k<d){
a[i] = (j&0xFE)+1; /* Set a[i] to nonzero. */
}else{
a[i] = 0;
}
}
/* for (i=0;i<n;i++){if (a[i]!=0){printf("i=%d, a[i]=%u\n",i,a[i]);}} printf("\n"); */ /* Uncomment this line to print the nonzeros in a. */
char txt0[]="arr2ind_movmsk: ";
char txt1[]="arr2ind_pext: ";
char txt2[]="arr2ind_if: ";
char txt3[]="arr2ind_cmov: ";
nrep=10000; /* Repeat a function nrep times to make relatively accurate timings possible. */
/* With nrep=1000000: ./a.out 10016 4 ; ./a.out 10016 48 ; ./a.out 10016 519 */
/* With nrep=10000: ./a.out 1000000 5 ; ./a.out 1000000 52 ; ./a.out 1000000 513 */
printf("nrep = \%d \n\n",nrep);
arr2ind_movmsk(a,n,ind,&m); /* Make sure that the arrays a and ind are read and/or written at least one time before benchmarking. */
for (meth=0;meth<4;meth++){
t0=omp_get_wtime();
switch (meth){
case 0: for(i=0;i<nrep;i++) arr2ind_movmsk(a,n,ind,&m); strcpy(txt,txt0); break;
case 1: for(i=0;i<nrep;i++) arr2ind_pext(a,n,ind,&m); strcpy(txt,txt1); break;
case 2: for(i=0;i<nrep;i++) arr2ind_if(a,n,ind,&m); strcpy(txt,txt2); break;
case 3: for(i=0;i<nrep;i++) arr2ind_cmov(a,n,ind,&m); strcpy(txt,txt3); break;
default: ;
}
t1=omp_get_wtime();
printf("method = %s ",txt);
/* print_chk(a,ind,m); */
printf(" elapsed time = %6.2f\n",t1-t0);
}
print_nonz(a, ind, 2); /* Do something with the results */
printf("density = %f %% \n\n",((double)m)/((double)n)*100); /* Actual nonzero density of array a. */
/* print_nonz(a, ind, m); */ /* Uncomment this line to print the indices of the nonzeros. */
return 0;
}
/*
With nrep=1000000:
./a.out 10016 4 ; ./a.out 10016 4 ; ./a.out 10016 48 ; ./a.out 10016 48 ; ./a.out 10016 519 ; ./a.out 10016 519
With nrep=10000:
./a.out 1000000 5 ; ./a.out 1000000 5 ; ./a.out 1000000 52 ; ./a.out 1000000 52 ; ./a.out 1000000 513 ; ./a.out 1000000 513
*/
The code was tested with array size of n=10016 (the data fits in L1 cache) and n=1000000, with different nonzero densities of about 0.5%, 5% and 50%. For accurate timing the functions were called 1000000 and 10000 times, respectively.
Time in seconds, size n=10016, 1e6 function calls. Intel core i5-6500
0.53% 5.1% 50.0%
arr2ind_movmsk: 0.27 0.53 4.89
arr2ind_pext: 1.44 1.59 1.45
arr2ind_if: 5.93 8.95 33.82
arr2ind_cmov: 6.82 6.83 6.82
Time in seconds, size n=1000000, 1e4 function calls.
0.49% 5.1% 50.1%
arr2ind_movmsk: 0.57 2.03 5.37
arr2ind_pext: 1.47 1.47 1.46
arr2ind_if: 5.88 8.98 38.59
arr2ind_cmov: 6.82 6.81 6.81
In these examples the vectorized loops are faster than the scalar loops.
The performance of arr2ind_movmsk depends a lot on the density of a. It is only
faster than arr2ind_pext if the density is sufficiently small. The break-even point also depends on the array size n.
Function 'arr2ind_if' clearly suffers from failing branch prediction at 50% nonzero density.
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