我正在修改AVX-2指令,我正在寻找一种快速计算__m256i单词(有256个位)中的前导零的方法。
到目前为止,我已经想出了以下方法:
// Computes the number of leading zero bits.
// Here, avx_word is of type _m256i.
if (!_mm256_testz_si256(avx_word, avx_word)) {
uint64_t word = _mm256_extract_epi64(avx_word, 0);
if (word > 0)
return (__builtin_clzll(word));
word = _mm256_extract_epi64(avx_word, 1);
if (word > 0)
return (__builtin_clzll(word) + 64);
word = _mm256_extract_epi64(avx_word, 2);
if (word > 0)
return (__builtin_clzll(word) + 128);
word = _mm256_extract_epi64(avx_word, 3);
return (__builtin_clzll(word) + 192);
} else
return 256; // word is entirely zero然而,我发现在256位寄存器中找出确切的非零字是相当笨拙的。
有没有人知道是否有一种更优雅(或更快)的方法来做到这一点?
作为附加信息:我实际上想要计算逻辑数所创建的任意长向量的第一个集合位的索引,并将标准64位操作的性能与SSE和AVX-2代码进行比较。下面是我的全部测试代码:
#include <stdio.h>
#include <stdlib.h>
#include <immintrin.h>
#include <stdint.h>
#include <assert.h>
#include <time.h>
#include <sys/time.h>
#include <stdalign.h>
#define ALL 0xFFFFFFFF
#define NONE 0x0
#define BV_SHIFTBITS ((size_t) 6)
#define BV_MOD_WORD ((size_t) 63)
#define BV_ONE ((uint64_t) 1)
#define BV_ZERO ((uint64_t) 0)
#define BV_WORDSIZE ((uint64_t) 64)
uint64_t*
Vector_new(
size_t num_bits) {
assert ((num_bits % 256) == 0);
size_t num_words = num_bits >> BV_SHIFTBITS;
size_t mod = num_bits & BV_MOD_WORD;
if (mod > 0)
assert (0);
uint64_t* words;
posix_memalign((void**) &(words), 32, sizeof(uint64_t) * num_words);
for (size_t i = 0; i < num_words; ++i)
words[i] = 0;
return words;
}
void
Vector_set(
uint64_t* vector,
size_t pos) {
const size_t word_index = pos >> BV_SHIFTBITS;
const size_t offset = pos & BV_MOD_WORD;
vector[word_index] |= (BV_ONE << (BV_MOD_WORD - offset));
}
size_t
Vector_and_first_bit(
uint64_t** vectors,
const size_t num_vectors,
const size_t num_words) {
for (size_t i = 0; i < num_words; ++i) {
uint64_t word = vectors[0][i];
for (size_t j = 1; j < num_vectors; ++j)
word &= vectors[j][i];
if (word > 0)
return (1 + i * BV_WORDSIZE + __builtin_clzll(word));
}
return 0;
}
size_t
Vector_and_first_bit_256(
uint64_t** vectors,
const size_t num_vectors,
const size_t num_avx_words) {
for (size_t i = 0; i < num_avx_words; ++i) {
const size_t addr_offset = i << 2;
__m256i avx_word = _mm256_load_si256(
(__m256i const*) (vectors[0] + addr_offset));
// AND the AVX words
for (size_t j = 1; j < num_vectors; ++j) {
avx_word = _mm256_and_si256(
avx_word,
_mm256_load_si256((__m256i const*) (vectors[j] + addr_offset))
);
}
// test whether resulting AVX word is not zero
if (!_mm256_testz_si256(avx_word, avx_word)) {
uint64_t word = _mm256_extract_epi64(avx_word, 0);
const size_t shift = i << 8;
if (word > 0)
return (1 + shift + __builtin_clzll(word));
word = _mm256_extract_epi64(avx_word, 1);
if (word > 0)
return (1 + shift + __builtin_clzll(word) + 64);
word = _mm256_extract_epi64(avx_word, 2);
if (word > 0)
return (1 + shift + __builtin_clzll(word) + 128);
word = _mm256_extract_epi64(avx_word, 3);
return (1 + shift + __builtin_clzll(word) + 192);
}
}
return 0;
}
size_t
Vector_and_first_bit_128(
uint64_t** vectors,
const size_t num_vectors,
const size_t num_avx_words) {
for (size_t i = 0; i < num_avx_words; ++i) {
const size_t addr_offset = i << 1;
__m128i avx_word = _mm_load_si128(
(__m128i const*) (vectors[0] + addr_offset));
// AND the AVX words
for (size_t j = 1; j < num_vectors; ++j) {
avx_word = _mm_and_si128(
avx_word,
_mm_load_si128((__m128i const*) (vectors[j] + addr_offset))
);
}
// test whether resulting AVX word is not zero
if (!_mm_test_all_zeros(avx_word, avx_word)) {
uint64_t word = _mm_extract_epi64(avx_word, 0);
if (word > 0)
return (1 + (i << 7) + __builtin_clzll(word));
word = _mm_extract_epi64(avx_word, 1);
return (1 + (i << 7) + __builtin_clzll(word) + 64);
}
}
return 0;
}
uint64_t*
make_random_vector(
const size_t num_bits,
const size_t propability) {
uint64_t* vector = Vector_new(num_bits);
for (size_t i = 0; i < num_bits; ++i) {
const int x = rand() % 10;
if (x >= (int) propability)
Vector_set(vector, i);
}
return vector;
}
size_t
millis(
const struct timeval* end,
const struct timeval* start) {
struct timeval e = *end;
struct timeval s = *start;
return (1000 * (e.tv_sec - s.tv_sec) + (e.tv_usec - s.tv_usec) / 1000);
}
int
main(
int argc,
char** argv) {
if (argc != 6)
printf("fuck %s\n", argv[0]);
srand(time(NULL));
const size_t num_vectors = atoi(argv[1]);
const size_t size = atoi(argv[2]);
const size_t num_iterations = atoi(argv[3]);
const size_t num_dimensions = atoi(argv[4]);
const size_t propability = atoi(argv[5]);
const size_t num_words = size / 64;
const size_t num_sse_words = num_words / 2;
const size_t num_avx_words = num_words / 4;
assert(num_vectors > 0);
assert(size > 0);
assert(num_iterations > 0);
assert(num_dimensions > 0);
struct timeval t1;
gettimeofday(&t1, NULL);
uint64_t*** vectors = (uint64_t***) malloc(sizeof(uint64_t**) * num_vectors);
for (size_t j = 0; j < num_vectors; ++j) {
vectors[j] = (uint64_t**) malloc(sizeof(uint64_t*) * num_dimensions);
for (size_t i = 0; i < num_dimensions; ++i)
vectors[j][i] = make_random_vector(size, propability);
}
struct timeval t2;
gettimeofday(&t2, NULL);
printf("Creation: %zu ms\n", millis(&t2, &t1));
size_t* results_64 = (size_t*) malloc(sizeof(size_t) * num_vectors);
size_t* results_128 = (size_t*) malloc(sizeof(size_t) * num_vectors);
size_t* results_256 = (size_t*) malloc(sizeof(size_t) * num_vectors);
gettimeofday(&t1, NULL);
for (size_t j = 0; j < num_iterations; ++j)
for (size_t i = 0; i < num_vectors; ++i)
results_64[i] = Vector_and_first_bit(vectors[i], num_dimensions,
num_words);
gettimeofday(&t2, NULL);
const size_t millis_64 = millis(&t2, &t1);
printf("64 : %zu ms\n", millis_64);
gettimeofday(&t1, NULL);
for (size_t j = 0; j < num_iterations; ++j)
for (size_t i = 0; i < num_vectors; ++i)
results_128[i] = Vector_and_first_bit_128(vectors[i],
num_dimensions, num_sse_words);
gettimeofday(&t2, NULL);
const size_t millis_128 = millis(&t2, &t1);
const double factor_128 = (double) millis_64 / (double) millis_128;
printf("128 : %zu ms (factor: %.2f)\n", millis_128, factor_128);
gettimeofday(&t1, NULL);
for (size_t j = 0; j < num_iterations; ++j)
for (size_t i = 0; i < num_vectors; ++i)
results_256[i] = Vector_and_first_bit_256(vectors[i],
num_dimensions, num_avx_words);
gettimeofday(&t2, NULL);
const size_t millis_256 = millis(&t2, &t1);
const double factor_256 = (double) millis_64 / (double) millis_256;
printf("256 : %zu ms (factor: %.2f)\n", millis_256, factor_256);
for (size_t i = 0; i < num_vectors; ++i) {
if (results_64[i] != results_256[i])
printf("ERROR: %zu (64) != %zu (256) with i = %zu\n", results_64[i],
results_256[i], i);
if (results_64[i] != results_128[i])
printf("ERROR: %zu (64) != %zu (128) with i = %zu\n", results_64[i],
results_128[i], i);
}
free(results_64);
free(results_128);
free(results_256);
for (size_t j = 0; j < num_vectors; ++j) {
for (size_t i = 0; i < num_dimensions; ++i)
free(vectors[j][i]);
free(vectors[j]);
}
free(vectors);
return 0;
}汇编:
gcc -o main main.c -O3 -Wall -Wextra -pedantic-errors -Werror -march=native -std=c99 -fno-tree-vectorize执行:
./main 1000 8192 50000 5 9这些参数平均为:1000个测试用例,长度为8192位的向量,50000,测试重复(后两个参数为小调整)。
在我的机器上进行上述调用的示例输出:
Creation: 363 ms
64 : 15000 ms
128 : 10070 ms (factor: 1.49)
256 : 6784 ms (factor: 2.21)发布于 2018-03-11 00:02:18
(更新:2019-01-31年度以来的新答复)
三种备选方案是:
在这个答案中,将输入的epi64向量与零进行比较,这将产生一个掩码。此掩码被转换为4位索引i_mask (通过_mm256_movemask_pd)。使用索引i_mask,从两个查找表中读取两个值: 1.第一个非零64位元素的索引,2.前面(从左到右)零元素的非零数。最后,计算第一个非零64位元素的_lzcnt_u64并将其添加到查找表值中。函数mm256_lzcnt_si256实现了这个方法:
#include <stdio.h>
#include <stdint.h>
#include <x86intrin.h>
#include <stdalign.h>
/* gcc -Wall -m64 -O3 -march=haswell clz_avx256_upd.c */
int mm256_lzcnt_si256(__m256i input)
{
/* Version with lookup tables and scratch array included in the function */
/* Two tiny lookup tables (64 bytes each, less space is possible with uint8_t or uint16_t arrays instead of uint32_t): */
/* i_mask (input==0) 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 */
/* ~i_mask (input!=0) 1111 1110 1101 1100 1011 1010 1001 1000 0111 0110 0101 0100 0011 0010 0001 0000 */
static const uint32_t indx[16] = { 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 1, 1, 0, 0};
static const uint32_t lz_msk[16] = { 0, 0, 0, 0, 0, 0, 0, 0, 64, 64, 64, 64, 128, 128, 192, 192};
alignas(32) uint64_t tmp[4] = { 0, 0, 0, 0}; /* tmp is a scratch array of 32 bytes, preferably 32 byte aligned */
_mm256_storeu_si256((__m256i*)&tmp[0], input); /* Store input in the scratch array */
__m256i mask = _mm256_cmpeq_epi64(input, _mm256_setzero_si256()); /* Check which 64 bits elements are zero */
uint32_t i_mask = _mm256_movemask_pd(_mm256_castsi256_pd(mask)); /* Move vector mask to integer mask */
uint64_t input_i = tmp[indx[i_mask]]; /* Load the first (from the left) non-zero 64 bit element input_i */
int32_t lz_input_i = _lzcnt_u64(input_i); /* Count the number of leading zeros in input_i */
int32_t lz = lz_msk[i_mask] + lz_input_i; /* Add the number of leading zeros of the preceding 64 bit elements */
return lz;
}
int mm256_lzcnt_si256_v2(__m256i input, uint64_t* restrict tmp, const uint32_t* indx, const uint32_t* lz_msk)
{
/* Version that compiles to nice assembly, although, after inlining there won't be any difference between the different versions. */
_mm256_storeu_si256((__m256i*)&tmp[0], input); /* Store input in the scratch array */
__m256i mask = _mm256_cmpeq_epi64(input, _mm256_setzero_si256()); /* Check which 64 bits elements are zero */
uint32_t i_mask = _mm256_movemask_pd(_mm256_castsi256_pd(mask)); /* Move vector mask to integer mask */
uint64_t input_i = tmp[indx[i_mask]]; /* Load the first (from the left) non-zero 64 bit element input_i */
int32_t lz_input_i = _lzcnt_u64(input_i); /* Count the number of leading zeros in input_i */
int32_t lz = lz_msk[i_mask] + lz_input_i; /* Add the number of leading zeros of the preceding 64 bit elements */
return lz;
}
__m256i bit_mask_avx2_lsb(unsigned int n)
{
__m256i ones = _mm256_set1_epi32(-1);
__m256i cnst32_256 = _mm256_set_epi32(256,224,192,160, 128,96,64,32);
__m256i shift = _mm256_set1_epi32(n);
shift = _mm256_subs_epu16(cnst32_256,shift);
return _mm256_srlv_epi32(ones,shift);
}
int print_avx2_hex(__m256i ymm)
{
long unsigned int x[4];
_mm256_storeu_si256((__m256i*)x,ymm);
printf("%016lX %016lX %016lX %016lX ", x[3],x[2],x[1],x[0]);
return 0;
}
int main()
{
unsigned int i;
__m256i x;
printf("mm256_lzcnt_si256\n");
for (i = 0; i < 257; i++){
printf("x=");
x = bit_mask_avx2_lsb(i);
print_avx2_hex(x);
printf("lzcnt(x)=%i \n", mm256_lzcnt_si256(x));
}
printf("\n");
x = _mm256_set_epi32(0,0,0,0, 0,15,1,0);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256(x));
x = _mm256_set_epi32(0,0,0,8, 0,0,0,256);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256(x));
x = _mm256_set_epi32(0,0x100,0,8, 0,192,0,0);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256(x));
x = _mm256_set_epi32(-1,0x100,0,8, 0,0,32,0);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256(x));
/* Set arrays for mm256_lzcnt_si256_v2: */
alignas(32) static const uint32_t indx[16] = { 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 1, 1, 0, 0};
alignas(32) static const uint32_t lz_msk[16] = { 0, 0, 0, 0, 0, 0, 0, 0, 64, 64, 64, 64, 128, 128, 192, 192};
alignas(32) uint64_t tmp[4] = { 0, 0, 0, 0};
printf("\nmm256_lzcnt_si256_v2\n");
for (i = 0; i < 257; i++){
printf("x=");
x = bit_mask_avx2_lsb(i);
print_avx2_hex(x);
printf("lzcnt(x)=%i \n", mm256_lzcnt_si256_v2(x, tmp, indx, lz_msk));
}
printf("\n");
x = _mm256_set_epi32(0,0,0,0, 0,15,1,0);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256_v2(x, tmp, indx, lz_msk));
x = _mm256_set_epi32(0,0,0,8, 0,0,0,256);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256_v2(x, tmp, indx, lz_msk));
x = _mm256_set_epi32(0,0x100,0,8, 0,192,0,0);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256_v2(x, tmp, indx, lz_msk));
x = _mm256_set_epi32(-1,0x100,0,8, 0,0,32,0);
printf("x=");print_avx2_hex(x);printf("lzcnt(x)=%i \n", mm256_lzcnt_si256_v2(x, tmp, indx, lz_msk));
return 0;
}输出表明代码是正确的:
$ ./a.out
mm256_lzcnt_si256
x=0000000000000000 0000000000000000 0000000000000000 0000000000000000 lzcnt(x)=256
x=0000000000000000 0000000000000000 0000000000000000 0000000000000001 lzcnt(x)=255
...
x=0000000000000000 0000000000000000 7FFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF lzcnt(x)=129
x=0000000000000000 0000000000000000 FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF lzcnt(x)=128
x=0000000000000000 0000000000000001 FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF lzcnt(x)=127
...
x=7FFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF lzcnt(x)=1
x=FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF FFFFFFFFFFFFFFFF lzcnt(x)=0
x=0000000000000000 0000000000000000 000000000000000F 0000000100000000 lzcnt(x)=188
x=0000000000000000 0000000000000008 0000000000000000 0000000000000100 lzcnt(x)=124
x=0000000000000100 0000000000000008 00000000000000C0 0000000000000000 lzcnt(x)=55
x=FFFFFFFF00000100 0000000000000008 0000000000000000 0000002000000000 lzcnt(x)=0 函数mm256_lzcnt_si256_v2是同一个函数的另一个版本,但是现在指向查找表和划痕数组的指针是通过函数调用传递的。这导致了清洁装配代码 (没有堆栈操作),并给出了在循环中内联mm256_lzcnt_si256后需要哪些指令。
gcc 8.2和选项-m64 -O3 -march=skylake
mm256_lzcnt_si256_v2:
vpxor xmm1, xmm1, xmm1
vmovdqu YMMWORD PTR [rdi], ymm0
vpcmpeqq ymm0, ymm0, ymm1
vmovmskpd ecx, ymm0
mov eax, DWORD PTR [rsi+rcx*4]
lzcnt rax, QWORD PTR [rdi+rax*8]
add eax, DWORD PTR [rdx+rcx*4]
vzeroupper
ret在循环上下文中,通过内联,vpxor很可能挂起在循环之外。
发布于 2018-03-11 02:33:03
由于您还要求采用更优雅(即更简单)的方法来完成此操作:在我的计算机上,您的代码运行速度与下面的代码一样快。在这两种情况下,需要45毫秒才能计算出1000万个256位字的结果。
由于我用随机生成的64位整数(而不是均匀分布的256个整数)填充AVX寄存器,通过数组的迭代顺序对我的基准测试结果没有影响。而且,尽管这一点几乎不用说,编译器还是足够聪明地展开循环。
uint32_t countLeadZeros(__m256i const& reg)
{
alignas(32) uint64_t v[4];
_mm256_store_si256((__m256i*)&v[0], reg);
for (int i = 3; i >= 0; --i)
if (v[i]) return _lzcnt_u64(v[i]) + (3 - i)*64;
return 256;
}编辑:正如在下面的讨论和编辑历史中所看到的那样,我最初采用了类似@PeterCorbes (但他提供了一个更好的优化解决方案)的方法。当我开始做基准测试时,我改变了我的方法,因为我完全忽略了这样一个事实:实际上,我的所有输入都有位于AVX单词前64位内的最重要的位。
当我意识到我所犯的错误后,我决定尝试更正确地进行基准测试。我将在下面介绍两个结果。我搜索了我的文章的编辑历史,从那里我复制粘贴了我提交的函数(但后来编辑了出来),然后我改变了我的方法,开始使用分支版本。这项职能列示如下。我比较了我的“分支”函数、“无分支”函数和@PeterCorbes独立开发的无分支函数的性能。他的版本在性能上优于我的版本--请看他写得很好的文章,其中包含了许多有用的细节。。
int countLeadZeros(__m256i const& reg){
__m256i zero = _mm256_setzero_si256();
__m256i cmp = _mm256_cmpeq_epi64(reg, zero);
int mask = _mm256_movemask_epi8(cmp);
if (mask == 0xffffffff) return 256;
int first_nonzero_idx = 3 - (_lzcnt_u32(~mask) >> 3);
alignas(32) uint64_t stored[4]; // edit: added alignas(32)
_mm256_store_si256((__m256i*)stored, reg);
int lead_zero_count = _lzcnt_u64(stored[first_nonzero_idx]);
return (3 - first_nonzero_idx) * 64 + lead_zero_count;
}基准1
我将用伪码表示测试代码,以缩短测试代码。我实际上使用了AVX实现的随机数生成器,它可以快速地生成随机数。首先,让我们对使分支预测非常困难的输入进行测试:
tick()
for(int i = 0; i < N; ++i)
{
// "xoroshiro128+"-based random generator was actually used
__m256i in = _mm256_set_epi64x(rand()%2, rand()%2, rand()%2, rand()%2);
res = countLeadZeros(in);
}
tock();在一千万次的重复中,我的帖子顶部的功能需要200毫秒。我最初开发的实现只需要65 do就可以完成相同的工作。但是@PeterCorbes提供的函数只消耗了60 by就能吃到蛋糕。
基准2
现在让我们转到我最初使用的测试。同样,伪码:
tick()
for(int i = 0; i < N; ++i)
{
// "rand()" represents random 64-bit int; xoroshiro128+ waw actually used here
__m256i in = _mm256_set_epi64x(rand(), rand(), rand(), rand());
res = countLeadZeros(in);
}
tock();在这种情况下,具有分支的版本更快;需要45 is才能计算1 000万个结果。@PeterCorbes的函数需要50 my才能完成,而我的“无分支”实现需要55 my才能完成相同的工作。
我认为我不敢从中得出任何一般性的结论。在我看来,无分支方法似乎更好,因为它提供了更稳定的计算时间,但您是否需要这种稳定性可能取决于usecase。
编辑:随机生成器。
这是对@PeterCorbes评论的扩展回复。如前所述,基准测试代码只是伪代码。如果有人感兴趣,我实际上是如何生成这些数字的,下面是一个简短的描述。
我使用了xoroshiro128+算法,该算法被发布到公共域中,并且是可用的在这个网站上。用AVX指令重写算法非常简单,这样就可以并行生成四个数字。我编写了一个类,它接受所谓的初始种子(128位)作为参数。首先,通过四次复制初始种子,获得四个并行生成器中每一个的种子(状态);之后,我对第一个并行生成器I-次数使用跳转指令;i= {0,1,2,3}。每次跳转都会使内部状态J=2^64前进一步。这意味着我可以生成4*J数字(对于所有日常用途来说都不够),在任何并行生成器开始重复当前会话中任何其他生成器已经生成的数字序列之前,每次生成4个。我用_mm256_srli_epi64指令控制产生的数字的范围;第一次测试使用shift 63,第二次没有移位。
发布于 2018-03-11 02:09:05
我有一个并不是真正“优雅”的版本,但在这里更快(Apple版本9.0.0 (clang-900.0.39.2)):
#define NOT_ZERO(x) (!!(x))
#ifdef UNIFORM_DISTRIBUTION
#define LIKELY(x) __builtin_expect(NOT_ZERO(x), 1)
#define UNLIKELY(x) __builtin_expect(NOT_ZERO(x), 0)
#else
#define LIKELY(x) (x)
#define UNLIKELY(x) (x)
#endif
inline unsigned int clz_u128(uint64_t a, uint64_t b, int not_a, int not_b) {
if(UNLIKELY(not_a)) {
if(UNLIKELY(not_b)) {
return 128;
} else {
return (__builtin_clzll(b)) + 64;
}
} else {
return (__builtin_clzll(a));
}
}
unsigned int clz_u256(__m256i packed) {
const uint64_t a_0 = (uint64_t)_mm256_extract_epi64(packed, 0);
const uint64_t a_1 = (uint64_t)_mm256_extract_epi64(packed, 1);
const uint64_t b_0 = (uint64_t)_mm256_extract_epi64(packed, 2);
const uint64_t b_1 = (uint64_t)_mm256_extract_epi64(packed, 3);
const int not_a_0 = !a_0;
const int not_a_1 = !a_1;
if(UNLIKELY(not_a_0 & not_a_1)) {
return clz_u128(b_0, b_1, !b_0, !b_1) + 128;
} else {
return clz_u128(a_0, a_1, not_a_0, not_a_1);
}
}它将一个更大的问题分解成更小的问题,并利用这样一个事实:如果向量分布是均匀的,高比特比低比特更有可能成为非零比特。
如果期望均匀分布具有额外的性能,只需添加一个#define UNIFORM_DISTRIBUTION即可。
https://stackoverflow.com/questions/49213611
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