在我的
previous post
void getDataAVX2(u_char* data, size_t cols, std::vector<double>& info)
{
__m256d dividend = _mm256_set_pd(1 / 64.0, 1 / 64.0, 1 / 64.0, 1 / 64.0);
info.resize(cols);
__m256d result;
for (size_t i = 0; i < cols / 4; i++)
{
__m256d divisor = _mm256_set_pd((double(data[4 * i + 3 + cols] << 8) + double(data[4 * i + 2 * cols + 3])),
(double(data[4 * i + 2 + cols] << 8) + double(data[4 * i + 2 * cols + 2])),
(double(data[4 * i + 1 + cols] << 8) + double(data[4 * i + 2 * cols + 1])),
(double(data[4 * i + cols] << 8) + double(data[4 * i + 2 * cols])));
result = _mm256_sqrt_pd(_mm256_mul_pd(divisor, dividend));
info[size_t(4 * i)] = result[0];
info[size_t(4 * i + 1)] = result[1];
info[size_t(4 * i + 2)] = result[2];
info[size_t(4 * i + 3)] = result[3];
}
}
我认为应该是等价的:
void getDataAVX512(u_char* data, size_t cols, std::vector<double>& info)
{
__m512d dividend = _mm512_set_pd(1 / 64.0, 1 / 64.0, 1 / 64.0, 1 / 64.0, 1 / 64.0, 1 / 64.0, 1 / 64.0, 1 / 64.0);
info.resize(cols);
__m512d result;
for (size_t i = 0; i < cols / 8; i++)
{
__m512d divisor = _mm512_set_pd((double(data[4 * i + 7 + cols] << 8) + double(data[4 * i + 2 * cols + 7])),
(double(data[4 * i + 6 + cols] << 8) + double(data[4 * i + 2 * cols + 6])),
(double(data[4 * i + 5 + cols] << 8) + double(data[4 * i + 2 * cols + 5])),
(double(data[4 * i + 4 + cols] << 8) + double(data[4 * i + 2 * cols + 4])),
(double(data[4 * i + 3 + cols] << 8) + double(data[4 * i + 2 * cols + 3])),
(double(data[4 * i + 2 + cols] << 8) + double(data[4 * i + 2 * cols + 2])),
(double(data[4 * i + 1 + cols] << 8) + double(data[4 * i + 2 * cols + 1])),
(double(data[4 * i + cols] << 8) + double(data[4 * i + 2 * cols])));
result = _mm512_sqrt_pd(_mm512_mul_pd(divisor, dividend));
info[size_t(4 * i)] = result[0];
info[size_t(4 * i + 1)] = result[1];
info[size_t(4 * i + 2)] = result[2];
info[size_t(4 * i + 3)] = result[3];
info[size_t(4 * i + 4)] = result[4];
info[size_t(4 * i + 5)] = result[5];
info[size_t(4 * i + 6)] = result[6];
info[size_t(4 * i + 7)] = result[7];
}
}
以非AVX形式表示为:
void getData(u_char* data, size_t cols, std::vector<double>& info)
{
info.resize(cols);
for (size_t i = 0; i < cols; i++)
{
info[i] = sqrt((double(data[cols + i] << 8) + double(data[2 * cols + i])) / 64.0);
;
}
}
编译代码后,我得到以下错误:
Illegal instruction (core dumped)
sqrt
在
getData
sqrt公司
调用,则错误将进一步显示在
__m512d divisor = _mm512_set_pd((d....
Here
是一个完整的例子。
我正在编译
c++
(7.3.0)具有以下选项
-std=c++17 -Wall -Wextra -O3 -fno-tree-vectorize -mavx512f
. 我已经按说明检查过了
here
我的CPU(Intel(R)Core(TM)i7-4710HQ CPU@2.50GHz)支持AVX2。列表中是否应该有AVX-512来表示对此的支持?