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Profiling code in 2017.8 — Gideros Forum

Profiling code in 2017.8

hgy29hgy29 Maintainer
edited August 2017 in Step by step tutorials
Gideros 2017.8 comes with an integrated native lua profiler.

For those who don't know what is a code profiler, it is a tool that measure effectiveness of the code and outputs statistics about the CPU usage: number of times each function was called, how much time it took to execute, and where was it called from. Gideros nows provide four functions to manage a profiling session:
- Core.profilerStart(), which instructs gideros start collecting profiling data
- Core.profilerStop(), which pause collecting
- Core.profilerReset(), which clears collected data
- Core.profilerReport(), which returns a table containing collected profiling data

To ease report generation, I've made a small lua file which convert the collected data into a more readable log. My profiler has just two functions: Profiler.start(): start profiling, Profiler.stop(): stop profiling and outputs data on console.

Ok, but what is it for ?

So suppose you are running the following code:
local function myFunction1(a)
	local function c(a) return math.cos(a*math.pi/180) end
	return c(a)+c(a+1)
end
and happen to use it very often. It is far from being optimized (on purpose, right) and turns out to be slow, but how can we do better ?

Lets ask the profiler how does it run, say we want to run it 1000000 times:
local function profile(myFunction)
	Profiler.start()
	for i=1,1000000 do myFunction(i) end
	Profiler.stop()
end
 
profile(myFunction1)
This code outputs:
<	[  6]	  3768	100%	1000000	 <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:22
=	[  1]	  3768	 36%	1000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:1
>	[  2]	  2424	 64%	2000000	c <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:2
--------------------------------
<	[  1]	  2424	100%	2000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:1
=	[  2]	  2424	 63%	2000000	c <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:2
>	[  3]	   892	 37%	2000000	cos =[C] 6E416930
--------------------------------
<	[  2]	   892	100%	2000000	c <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:2
=	[  3]	   892	100%	2000000	cos =[C] 6E416930
--------------------------------
=	[  4]	     0	 -1%	     0	 =[C] 00456FA0
--------------------------------
=	[  5]	     0	 -1%	     0	stop <a href="https://forum.gideros.rocks/profile/profiler" rel="nofollow">@profiler</a>.lua:7
--------------------------------
=	[  6]	     0	 -1%	     0	 <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:22
>	[  1]	  3768	  1%	1000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:1
--------------------------------
=	[  7]	     0	 -1%	     0	 <a href="https://forum.gideros.rocks/profile/profiler" rel="nofollow">@profiler</a>.lua:2
--------------------------------
=	[  8]	     0	 -1%	     0	profilerStop =[C] 004536A0
--------------------------------
This is a list of all functions ran by the code sorted by CPU usage (highest first). The first chunk is:
<	[  6]	  3768	100%	1000000	 <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:22 (This is the function that called this one)
=	[  1]	  3768	 36%	1000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:1 (This is the considered function)
>	[  2]	  2424	 64%	2000000	c <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:2 (This is the function that was called by this function)
So the function 'myFunction' took most of the time. Figures tell us that it was called 1000000 times and consumed 3768ms on CPU. We also learn that it was called from function [6], located at main.lua:22, and that all the time (100%) spent in myFunction was due to being called by main.lua:22.
More interesting, we discover that 64% of the time (2424ms) was spent in calls to function [2], named 'c' and located at main.lua:2, and that c was called 2000000 times (twice per call).

The second chunk, about function [2], that is c@main.lua:2 shows us that 37% of the time was spent in math.cos(), and 63% in the function itself.

We now that calling a function is expensive, and that 'c' function is rather simple. Lets try to inline it:
local function myFunction2(a)
	return math.cos(a*math.pi/180)+math.cos((a+1)*math.pi/180)
end
Now profiler report looks like this: (truncated)
<	[  5]	   912	100%	1000000	 <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:22
=	[  1]	   912	 76%	1000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:6
>	[  2]	   215	 24%	2000000	cos =[C] 6E416930
--------------------------------
<	[  1]	   215	100%	2000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:6
=	[  2]	   215	100%	2000000	cos =[C] 6E416930
myFunction is already faster: 912ms now where we had 3768ms before.
We still call math.cos two times. Lets make it (and math.pi) local.
local function myFunction3(a)
	local cos=math.cos
	local pi=math.pi
	return cos(a*pi/180)+cos((a+1)*pi/180)
end
and profiler report:
<	[  6]	   798	100%	1000000	 <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:22
=	[  1]	   798	 73%	1000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:10
>	[  2]	   216	 27%	2000000	cos =[C] 6E416930
We saved time in myFunction, while cos() took the same time.

What if we use new gideros deg to rad operator instead of math.pi and 180 constant ?
local function myFunction4(a)
	local cos=math.cos
	return cos(^<a)+cos(^<(a+1))
end
and profiler report:
<	[  5]	   741	100%	1000000	 <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:22
=	[  1]	   741	 71%	1000000	myFunction <a href="https://forum.gideros.rocks/profile/main" rel="nofollow">@main</a>.lua:16
>	[  2]	   216	 29%	2000000	cos =[C] 6E416930
We saved a few more precious milliseconds!

As you can see, the profiler is an useful tool to spot CPU bottlenecks in your app, and some times a few minor changes in the code can make big differences: avoid table access, avoid function calls, avoid duplicate computations.
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