I have a friendly competition with couple of guys in the field of programming and recently we have become so interested in writing efficient code. Our challenge was to try to optimize the code (in sense of cpu time and complexity) at any cost (readability, reusability, etc).
The problem is, now we need to compare our codes and see which approach is better comparing to the others but we don't know any tools for this purpose.
My question is, are there some (any!) tools that takes a piece of code as input and calculates the number of flops or cpu instructions necessary for running it? Is there any tool can measure the optimacy of a code?
P.S. The target language is c++ but would be nice to know if such tools exists also for java.
Here's a little C++11 stopwatch I like to roll out when I need to time something:
#include <chrono>
#include <ctime>
template <typename T> class basic_stopwatch
{
typedef T clock;
typename clock::time_point p;
typename clock::duration d;
public:
void tick() { p = clock::now(); }
void tock() { d += clock::now() - p; }
void reset() { d = clock::duration::zero(); }
template <typename S> unsigned long long int report() const
{
return std::chrono::duration_cast<S>(d).count();
}
unsigned long long int report_ms() const
{
return report<std::chrono::milliseconds>();
}
basic_stopwatch() : p(), d() { }
};
struct c_clock
{
typedef std::clock_t time_point;
typedef std::clock_t duration;
static time_point now() { return std::clock(); }
};
template <> unsigned long long int basic_stopwatch<c_clock>::report_ms() const
{
return 1000. * double(d) / double(CLOCKS_PER_SEC);
}
typedef basic_stopwatch<std::chrono::high_resolution_clock> stopwatch;
typedef basic_stopwatch<c_clock> cstopwatch;
Usage:
stopwatch sw;
sw.tick();
run_long_code();
sw.tock();
std::cout << "This took " << sw.report_ms() << "ms.\n";
On any decent implementation, the default high_resolution_clock should give very accurate timing information.
There is the std::clock() function from <ctime> which returns how much CPU time was spent on the current process (that means it doesn't count the time the program was idling because the CPU was executing other tasks). This function can be used to accurately measure execution times of algorithms. Use the constant std::CLOCKS_PER_SEC (also from <ctime>) to convert the return value into seconds.
From the inline-assembly, you can use rdtsc instruction to get 32-bit(least significant part) counter into eax and 32-bit(highest significant part) to edx. If your code is too small, you can check total-approimate cpu-cycles with just eax register. If count is more than max. of 32-bit value, edx increments per max-32-bit value cycle.
int cpu_clk1a=0;
int cpu_clk1b=0;
int cpu_clk2a=0;
int cpu_clk2b=0;
int max=0;
std::cin>>max; //loop limit
__asm
{
push eax
push edx
rdtsc //gets current cpu-clock-counter into eax&edx
mov [cpu_clk1a],eax
mov [cpu_clk1b],edx
pop edx
pop eax
}
long temp=0;
for(int i=0;i<max;i++)
{
temp+=clock();//needed to defy optimization to actually measure something
//even the smartest compiler cannot know what
//the clock would be
}
__asm
{
push eax
push edx
rdtsc //gets current cpu-clock-counter into aex&edx
mov [cpu_clk2a],eax
mov [cpu_clk2b],edx
pop edx
pop eax
}
std::cout<<(cpu_clk2a-cpu_clk1a)<<std::endl;
//if your loop takes more than ~2billions of cpu-clocks, use cpu_clk1b and 2b
getchar();
getchar();
Output: 74000 cpu-cycles for 1000 iterations and 800000 cpu-cycles for 10000 iterations on my machine. Because clock() is time-consuming.
Cpu-cycle resolution on my machine: ~1000 cycles. Yes, you need more than several thousands of addition/subtraction(fast instructions) to measure it relatively correct.
Assuming cpu working frequency being constant, 1000 cpu-cycles is nearly equal to 1 micro-seconds for a 1GHz cpu. You should warm your cpu up before doing this.
It is quite difficult to calculate the detailing number of cpu time from a block of code. The normal way to do this is to design the worse / average / best input data as test cases. And do a timing profiling based on your real code with these test cases. There is no any tool can tell you the flops when it is without the detailing input test data and conditions.
There are pieces of software called profilers which exactly do what you want.
An example for Windows is AMD code analyser and gprof for POSIX.
Measuring the number of CPU instructions is pretty useless.
Performance is relative to bottleneck, depending on the problem at hand the bottleneck might be the network, disk IOs, memory or CPU.
For just a friendly competition, I would suggest timing. Which implies providing test cases that are big enough to have meaningful measures, of course.
On Unix, you can use gettimeofday for relatively precise measures.
Best for your purposes is valgrind/callgrind
来源：https://stackoverflow.com/questions/12340824/how-to-compare-performance-of-two-pieces-of-codes