About

memtrail is a LD_PRELOAD based memory profiler and leak detector for Linux.

There are already many other open-source memory debugging/profiling tools for Linux, several of which are listed on Links section below, and the most powerful arguably being Valgrind. However, I needed a tool that could quantify leaks and identify memory hogs, for long-running and CPU intensive workloads, which simply run too slow under Valgrind's dynamic binary instrumentation, hence this project.

Features

Very little runtime overhead
Will immediately output maxmimum memory allocated and total leaked memory at the end of program execution.
Text trees show callstacks for memory consuption or leaks
Can produce graphs showing flow of memory consumption or leaks

Requirements

Linux
Python 2.7
gzip
libunwind

For best results (performance/stability) configure libunwind and build as
```
  ./configure --disable-cxx-exceptions --disable-debug-frame --disable-block-signals --disable-shared --enable-static --with-pic
```
add set UNWIND_SRC environment variable to where the libunwind source is.
gprof2dot for graph output

Build

make

Usage

Run the application you want to debug as

memtrail record /path/to/application [args...]

and it will generate a record memtrail.data in the current directory.

View results with

memtrail report

It will produce something like

maximum: 5890 bytes

->34.77% (2048B): test_calloc
| ->34.77% (2048B): main
|   ->34.77% (2048B): __libc_start_main
|     ->34.77% (2048B): _start
| 
->17.39% (1024B): test_memalign
| ->17.39% (1024B): main
|   ->17.39% (1024B): __libc_start_main
|     ->17.39% (1024B): _start
| 
->17.39% (1024B): test_malloc
| ->17.39% (1024B): main
|   ->17.39% (1024B): __libc_start_main
|     ->17.39% (1024B): _start
| 
-> 8.69% (512B): TestGlobal::TestGlobal()
| -> 8.69% (512B): __static_initialization_and_destruction_0
|   -> 8.69% (512B): _GLOBAL__sub_I_leaked
|     -> 8.69% (512B): __libc_csu_init
|       -> 8.69% (512B): __libc_start_main
|         -> 8.69% (512B): _start
| 
-> 8.69% (512B): test_cxx
| -> 8.69% (512B): main
|   -> 8.69% (512B): __libc_start_main
|     -> 8.69% (512B): _start
| 
-> 8.69% (512B): test_cxx
| -> 8.69% (512B): main
|   -> 8.69% (512B): __libc_start_main
|     -> 8.69% (512B): _start
| 
-> 4.35% (256B): TestGlobal::TestGlobal()
| -> 4.35% (256B): __static_initialization_and_destruction_0
|   -> 4.35% (256B): _GLOBAL__sub_I_leaked
|     -> 4.35% (256B): __libc_csu_init
|       -> 4.35% (256B): __libc_start_main
|         -> 4.35% (256B): _start
| 
-> 0.02% (1B) in 2 places, all below the 1.00% threshold

memtrail.maximum.json written

You can then use gprof2dot.py to obtain graphs highlighting memory leaks or consumption:

gprof2dot.py -f json memtrail.maximum.json | dot -Tpng -o memtrail.maximum.png

It is also possible to trigger memtrail to take snapshots at specific points by calling memtrail_snapshot from your code:

#include "memtrail.h"

...

   memtrail_snapshot();

Links

Memory debugging: