我在 C++11 中的程序正在执行序列化数据的在线处理，循环需要在数百万个内存位置上运行。计算效率是必须的，我担心的是，通过在这样的循环中调用函数或类将创建不必要的操作，这些操作会影响效率，例如在不同变量范围之间传输操作所需的多个指针值。
为了举例说明，让我们考虑以下虚拟示例，其中"某物"是重复的操作。请注意，"something"中的代码使用循环范围内的变量。
do {
something(&span,&foo);
spam++
foo++
if ( spam == spam_spam ) {
something(&span,&foo);
other_things(&span,&foo);
something(&span,&foo);
}
else {
something(&span,&foo);
still_other_things(&span,&foo);
something(&span,&foo);
}
}
while (foo<bar);
有没有办法重复代码块并避免使用不必要的操作移动和复制变量？在这样的循环中使用函数和类是否实际上意味着额外的操作以及如何避免它？
更新
按照建议，我使用下面介绍的代码运行了一些测试。我测试了几个关于如何调用简单增量 1 亿次的选项。我在 Hyper-V 下的x86_64虚拟机上使用 GCC 而不是 RHEL 7 Server 7.6。
最初，编译为 "g++ -std=c++17 -o test.o test.cpp">
简单循环计算(基线)：211.046ms
内联功能：468.768ms
λ函数：253.466ms
定义宏：211.995ms
函数传递值：466.986ms
函数传递指针：344.646ms
无效功能：190.557ms
使用成员操作的对象方法：231.458ms
对象方法传递值：227.615ms
从这些结果中，我意识到编译器没有接受内联建议，即使在尝试按照 g++ 的建议将其膨胀以执行它之后 内联函数
后来，正如 Mat 在同一帖子中的答案所建议的那样，我使用"g++ -std=c++17 -O2 -o test.o test.cpp"打开了编译器优化，并得到了以下结果与没有优化的测试相比，迭代次数相同。
简单循环计算(基线)：62.9254ms
内联功能：65.0564ms
λ函数：32.8637ms
定义宏：63.0299ms
函数传递值：64.2876ms
函数传递指针：63.3416ms
无效功能：32.1073ms
对象方法使用成员操作：63.3847ms
对象方法传递值：62.5151ms
结论如下：
内联函数不是好的选择，因为人们无法确定编译器将如何真正接受它，并且结果可能与使用标准函数一样糟糕。
">定义宏"和"lambda 函数"是内联的更好替代方案。每个都有其优点和功能，#define 更加灵活。
使用对象成员和方法可以很好地平衡解决任何情况下的问题，同时以更易于维护和优化的形式维护代码。
调整编译器是值得的;
遵循用于测试的代码：
// Libraries
#include <iostream>
#include <cmath>
#include <chrono>
// Namespaces
using namespace std;
using namespace std::chrono;
// constants that control program behaviour
const long END_RESULT = 100000000;
const double AVERAGING_LENGTH = 40.0;
const int NUMBER_OF_ALGORITHM = 9;
const long INITIAL_VALUE = 0;
const long INCREMENT = 1;
// Global variables used for test with void function and to general control of the program;
long global_variable;
long global_increment;
// Function that returns the execution time for a simple loop
int64_t simple_loop_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Perform the computation for baseline
do {
local_variable += local_increment;
} while ( local_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return(duration_cast<microseconds>( timer_stop - timer_start ).count());
}
// Functions that computes the execution time when using inline code within the loop
inline long increment_variable() __attribute__((always_inline));
inline long increment_variable(long local_variable, long local_increment) {
return local_variable += local_increment;
}
int64_t inline_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Perform the computation for baseline
do {
local_variable = increment_variable(local_variable,local_increment);
} while ( local_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// Functions that computes the execution time when using lambda code within the loop
int64_t labda_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// define lambda function
auto lambda_increment = [&] {
local_variable += local_increment;
};
// Perform the computation for baseline
do {
lambda_increment();
} while ( local_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// define lambda function
#define define_increment() local_variable += local_increment;
// Functions that computes the execution time when using lambda code within the loop
int64_t define_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Perform the computation for baseline
do {
define_increment();
} while ( local_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// Functions that compute the execution time when calling a function within the loop passing variable values
long increment_with_values_function(long local_variable, long local_increment) {
return local_variable += local_increment;
}
int64_t function_values_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Perform the computation for baseline
do {
local_variable = increment_with_values_function(local_variable,local_increment);
} while ( local_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// Functions that compute the execution time when calling a function within the loop passing variable pointers
long increment_with_pointers_function(long *local_variable, long *local_increment) {
return *local_variable += *local_increment;
}
int64_t function_pointers_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Perform the computation for baseline
do {
local_variable = increment_with_pointers_function(&local_variable,&local_increment);
} while ( local_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// Functions that compute the execution time when calling a function within the loop without passing variables
void increment_with_void_function(void) {
global_variable += global_increment;
}
int64_t function_void_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// set global variables
global_variable = local_variable;
global_increment = local_increment;
// Perform the computation for baseline
do {
increment_with_void_function();
} while ( global_variable != END_RESULT);
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// Object and Function that compute the duration when using a method of the object where data is stored without passing variables
struct object {
long object_variable = 0;
long object_increment = 1;
object(long local_variable, long local_increment) {
object_variable = local_variable;
object_increment = local_increment;
}
void increment_object(void){
object_variable+=object_increment;
}
void increment_object_with_value(long local_increment){
object_variable+=local_increment;
}
};
int64_t object_members_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Create object
object object_instance = {local_variable,local_increment};
// Perform the computation for baseline
do {
object_instance.increment_object();
} while ( object_instance.object_variable != END_RESULT);
// Get the results out of the object
local_variable = object_instance.object_variable;
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
// Function that compute the duration when using a method of the object where data is stored passing variables
int64_t object_values_computation(long local_variable, long local_increment) {
// Starts the clock to measure the execution time for the baseline
high_resolution_clock::time_point timer_start = high_resolution_clock::now();
// Create object
object object_instance = {local_variable,local_increment};
// Perform the computation for baseline
do {
object_instance.increment_object_with_value(local_increment);
} while ( object_instance.object_variable != END_RESULT);
// Get the results out of the object
local_variable = object_instance.object_variable;
// Stop the clock to measure performance of the silly version
high_resolution_clock::time_point timer_stop = high_resolution_clock::now();
return duration_cast<microseconds>( timer_stop - timer_start ).count();
}
int main() {
// Create array to store execution time results for all tests
pair<string,int64_t> duration_sum[NUMBER_OF_ALGORITHM]={
make_pair("Simple loop computation (baseline): ",0.0),
make_pair("Inline Function: ",0.0),
make_pair("Lambda Function: ",0.0),
make_pair("Define Macro: ",0.0)
make_pair("Function passing values: ",0.0),
make_pair("Function passing pointers: ",0.0),
make_pair("Function with void: ",0.0),
make_pair("Object method operating with members: ",0.0),
make_pair("Object method passing values: ",0.0),
};
// loop to compute average of several execution times
for ( int i = 0; i < AVERAGING_LENGTH; i++) {
// Compute the execution time for a simple loop as the baseline
duration_sum[0].second = duration_sum[0].second + simple_loop_computation(INITIAL_VALUE, INCREMENT);
// Compute the execution time when using inline code within the loop (expected same as baseline)
duration_sum[1].second = duration_sum[1].second + inline_computation(INITIAL_VALUE, INCREMENT);
// Compute the execution time when using lambda code within the loop (expected same as baseline)
duration_sum[2].second = duration_sum[2].second + labda_computation(INITIAL_VALUE, INCREMENT);
// Compute the duration when using a define macro
duration_sum[3].second = duration_sum[3].second + define_computation(INITIAL_VALUE, INCREMENT);
// Compute the execution time when calling a function within the loop passing variables values
duration_sum[4].second = duration_sum[4].second + function_values_computation(INITIAL_VALUE, INCREMENT);
// Compute the execution time when calling a function within the loop passing variables pointers
duration_sum[5].second = duration_sum[5].second + function_pointers_computation(INITIAL_VALUE, INCREMENT);
// Compute the execution time when calling a function within the loop without passing variables
duration_sum[6].second = duration_sum[6].second + function_void_computation(INITIAL_VALUE, INCREMENT);
// Compute the duration when using a method of the object where data is stored without passing variables
duration_sum[7].second = duration_sum[7].second + object_members_computation(INITIAL_VALUE, INCREMENT);
// Compute the duration when using a method of the object where data is stored passing variables
duration_sum[8].second = duration_sum[8].second + object_values_computation(INITIAL_VALUE, INCREMENT);
}
double average_baseline_duration = 0.0;
// Print out results
for ( int i = 0; i < NUMBER_OF_ALGORITHM; i++) {
// compute averave from sum
average_baseline_duration = ((double)duration_sum[i].second/AVERAGING_LENGTH)/1000.0;
// Print the result
cout << duration_sum[i].first << average_baseline_duration << "ms n";
}
return 0;
}
如果代码足够短，则可以将其声明为内联，编译器会将其内联。如果不是，那么重复它可能不会有帮助。
但是，老实说，无论如何，这是最无效的优化形式。关注高效的算法并缓存高效的数据结构。
正如其他人建议的那样inline关键字可以做到这一点，但存在限制(每个编译器不同)，有些人不喜欢内部循环等......因此，如果你里面有编译器不喜欢的东西，那么该函数根本不会内联......
因此，如果您想要更好的解决方案，不受限制(对于更复杂的代码)始终有效，我通常为此使用#define：
// definition
#define code_block1(operands) { code ... }
#define code_block2(operands) { code ...
code ...
code ...
code ...
code ... }
// usage:
code ...
code_block1(); // this is macro so the last ; is not needed but I like it there ...
code_block2();
code ...
code_block2();
code ...
code_block1();
code ...
code_block2();
code_block1();
...
// undefinition so tokens do not fight with latter on code
#undef code_block1
#undef code_block2
所以你只是简单地用宏(#define)的形式定义你的代码，而不是函数......它可以使用全局变量和局部变量...不需要{ }，但这是一个好主意，因此宏的行为方式与单个表达式相同。一旦你开始使用这样的东西，这将防止后者头痛：
for (i=0;i<100;i++) code_block1();
如果没有宏内部的{ }，代码将中断，因为只有宏内的第一个表达式会在循环内......从快速浏览代码来看，这并不明显。
对于短代码，您可以将内容写入单行，但如果代码很长，则可以使用将定义划分为多行。当心不要在定义行中使用注释//因为那样会在代码中使用宏后注释掉所有内容，甚至是代码......所以如果你必须有评论，请使用/* ... */代替。
(operands)部分是可选的，没有操作数，它只是
#define code_block1 { code ... }
#undef部分是可选的，具体取决于您是否希望在整个代码中使用此类宏，或者仅在某些函数、类、文件中本地使用此类宏......此外，正如您所看到的，宏中只使用了令牌名称，根本没有操作数。
我经常使用它，例如请参阅：
- 如何从图像中检测机器人方向？
并寻找loop_beg和loop_end...它是一个循环宏，用法：
loop_beg custom_code; loop_end
这就是为什么它没有{}，因为{在loop_beg，而}在loop_end.