1. 编译不带ICU支持的boost库 此种情况下的boost库编译起来比较的简单,在准备好的console窗口中输入:
为此,我们可以分别使用cpp_float_50或cpp_dec_float_100。让我们看一下示例以获得更好的主意。 示例 #include<iostream> #include <boost/multiprecision/cpp_dec_float.hpp> #include <boost/math/constants/constants.hpp> using boost::multiprecision::cpp_dec_float_50; using namespace std; template<typename...
3) Multiprecision Float:使用 Boost Multiprecision float,我们可以分别使用 cpp_float_50 和 cpp_dec_float_100 实现高达 50 和 100 的精度。 以下是使用float、decimal和cpp_float_50类型计算不同精度圆面积的C++代码: CPP实现 // CPP Program to demonstrate Boost Multiprecision float #include<boost/math/cons...
h> #include <sstream> #include <vector> #include using F = boost::multiprecision::cpp_dec_float_50; namespace ba = boost::archive; int main() { F f{"2837498273489289734982739482398426938568923658926938478923748"}; std::vector<unsigned char> raw; { std::ostringstream oss; { ba::binary_oarchi...
cout <<"根号2是:"<<setprecision(50) <<root_two<cpp_dec_float_50>() << endl;return0; }// 圆周率π是:3.1415926535897932384626433832795028841971693993751// 自然对数e是:2.7182818284590452353602874713526624977572470937// 根号2是:1.4142135623730950488016887242096980785696718753769 ...
#include<boost/math/constants/constants.hpp>#include<boost/multiprecision/cpp_dec_float.hpp>#include<iostream>#include<iomanip>using namespace std;using namespace boost::math::constants;using namespace boost::multiprecision;intmain(){cout<<"圆周率是:"<<setprecision(50)<<pi<cpp_dec_float_50>()...
#include <boost/multiprecision/cpp_dec_float.hpp> #include <iostream> #include <iomanip> usingnamespacestd; usingnamespaceboost::math::constants; usingnamespaceboost::multiprecision; intmain() { cout<<"圆周率是:"<<setprecision(50)<<pi<cpp_dec_float_50>()<<endl; ...
@@ -71,18 +86,20 @@ T f(const T& w, const T& x, const T& y, const T& z) int main() { using cpp_dec_float_100 = boost::multiprecision::cpp_dec_float_100; - // Calculated from Mathematica symbolic differentiation. See multiprecision.nb for script. - const cpp_dec_float_100...
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--gpt_attention_plugin float16 --workers 1 --max_batch_size 32 --max_seq_len 131072 --use_fused_mlp enable --reduce_fusion enable --use_paged_context_fmha enable --multiple_profiles enable --gemm_plugin fp8 python3 /app/tensorrt_llm/benchmarks/cpp/prepare_dataset.py ...