`gprof` GNU Profile tool

GNU Profile (gprof) is a performance analysis tool that helps developers identify code bottlenecks and optimize their programs. It provides detailed information about the execution time and call frequency of functions within a program.

gprof can be used to:

Detect performance bottlenecks in your code
Identify which functions consume the most execution time
Analyze the call graph of your program
Help prioritize optimization efforts

Usage

Build

Enable the following configuration in NuttX:

CONFIG_SYSTEM_GPROF

Using in NuttX

Start profiling:
```
nsh> gprof start
```
Stop profiling:
```
nsh> gprof stop
```
Dump profiling data:
```
nsh> gprof dump /tmp/gmon.out
```

Analyzing on Host

Pull the profiling data to host:
```
adb pull /tmp/gmon.out ./gmon.out
```

Analyze the data using gprof tool:

The saved file format complies with the standard gprof format.
For detailed instructions on gprof command usage, please refer to the GNU gprof manual:
https://ftp.gnu.org/old-gnu/Manuals/gprof-2.9.1/html_mono/gprof.html

arm-none-eabi-gprof ./nuttx/nuttx gmon.out -b

Example output:

```
arm-none-eabi-gprof nuttx/nuttx gmon.out -b
Flat profile:

Each sample counts as 0.001 seconds.
  %   cumulative   self              self     total
 time   seconds   seconds    calls   s/call   s/call  name
 66.41      3.55     3.55       43     0.08     0.08  sdelay
 33.44      5.34     1.79       44     0.04     0.04  delay
  0.07      5.34     0.00                             up_idle
  0.04      5.34     0.00                             nx_start
  0.02      5.34     0.00                             fdtdump_main
  0.02      5.34     0.00                             nxsem_wait
  0.00      5.34     0.00        1     0.00     5.34  hello_main
  0.00      5.34     0.00        1     0.00     0.00  singal_handler

```

This output shows the performance profile of the program,
including execution time and call counts for each function.
The flat profile table provides a quick overview of where the program spends most of its time.
In this example, `sdelay` and `delay` functions consume the majority of execution time.
This information can be used to identify performance bottlenecks and optimize critical parts of the code.