Sigil is a profiling tool that can extract communication patterns within a workload independent of hardware characteristics.
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docs
examples
postprocessing
setup
valgrind-3.10.1
README
run_sigil.sh

README

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--------------------
===== Overview =====
--------------------

Sigil is a Valgrind tool designed to help the HW/SW partitioning problem.
By analyzing a user's unmodified binary executable, Sigil generates callgraph
and dependency data. This data identifies the 'true cost' of your functions.
We include sample post-processing scripts to demonstrate the utility of this
information.

The tool is implemented as a run-time profiler and works on the 
application binary directly to produce platform-independent data. It does 
not need any source code changes or any prior knowledge of the application. 

For a better grasp on Sigil, please read the Valgrind, Cachegrind,
and Callgrind overviews.

If our tool is valuable to your research, please cite our Sigil paper:
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6704685

Additionally please see our 'docs' folder for more information.


--------------------------
===== Building Sigil =====
--------------------------

We offer a setup script to automatically detect missing package
dependencies and build the tool. 

   cd setup
   ./deb_pre_setup_sigil.sh (if applicable)
   ./setup_sigil.sh

If you would rather build the tool manually, you can run the following:
   
   cd valgrind-3.10.1
   ./autogen.sh
   ./configure
   ./make check


-------------------------
===== Running Sigil =====
-------------------------

An included script will run sigil with the most common options. Note that
the user must first edit this script with some default paths to let it know
where is the sigil directory. Make sure your binary is compiled with debug
flags.

   ./run_sigil.sh <user binary>

This results in a file called "sigil.total.out.<thread_number>"
For example if I wanted to get sigil results for the 'ls' command:

   ./run_sigil.sh ls -lah

However my results would probably not be very useful because 'ls' was probably
not compiled with debug flags

More information about running the tool and its options can be found in the
provided documentation.


--------------------------
===== Postprocessing =====
--------------------------

Sigil's raw output is not very readable and must be post processed.

A Python post-processing script is available to run through the results 
and present them in a more readable format. This is found in the accompanying
'postprocessing' folder. The postprocessing script comes with its own README.

   postprocessing/aggregate_costs_gran.py <inputfile> <printcallees?=yes|no> <percentofinst=0-100>

The post-processing script prints inclusive costs of each function in each
unique context, in a calltree fashion similar to callgrind itself. 

See the documentation for more information


--------------------------
===== Restrictions =====
--------------------------

Sigil is a Valgrind tool, and as such, is 
only officially supported in LINUX.

What programs can be profiled by the tool? (Restrictions/Known issues)

As the tool incurs slowdown already, some restrictions were placed
purposefully on the user program, so that writing optimized code would be 
somewhat easier and the memory behavior of the tool is more determinate.

The restrictions are as follows:

   1. Each function name must be unique across the application. 
      The user program must not have overloaded function. This 
      can cause the post-processing script to get confused.
      We are working on a solution to this problem.

   2. The maximum depth of the calltree in the user program (after main) 
      must not exceed the <number> - 10, specified in the
      --separate-callers=<number> option

      The default for <number> in the wrapper script is 400, but it can 
      simply be the maximum depth of the calltree in the user program + 10. 
      The additional 10 is just a buffer for the functions before main() 
      and after exit().

   3. The number of callees for each function in the user program should at 
      most be 1000. (These are hardcoded)

   4. The number of functions in the program must not exceed 10,000. 
      (Also hardcoded)

   5. Sigil cannot handle address values above 256G currently. 

   6. Applications with a large memory footprint can cause Sigil to exceed 
      memory bounds set by Valgrind or the system. 

      If such an error is encountered, we recommend running with smaller 
      input sets.

   7. Applications with very large call depth can also cause Sigil to exceed 
      memory bounds. Currently, there is no workaround for this, but we are 
      working on a long term solution that could mean tighter integration 
      with Callgrind.