Everybody knows how useful time profilers are for speeding up programs. They are particularly useful because people are notoriously bad at predicting where are the bottlenecks in their programs.

But the story is different for heap profilers. Some programming languages, particularly lazy functional languages like Haskell, have quite sophisticated heap profilers. But there are few tools as powerful for profiling C and C++ programs.

Why is this? Maybe it's because C and C++ programmers must think that they know where the memory is being allocated. After all, you can see all the calls to malloc() and new and new[], right? But, in a big program, do you really know which heap allocations are being executed, how many times, and how large each allocation is? Can you give even a vague estimate of the memory footprint for your program? Do you know this for all the libraries your program uses? What about administration bytes required by the heap allocator to track heap blocks -- have you thought about them? What about the stack? If you are unsure about any of these things, maybe you should think about heap profiling.

Massif can tell you these things.

Or maybe it's because it's relatively easy to add basic heap profiling functionality into a program, to tell you how many bytes you have allocated for certain objects, or similar. But this information might only be simple like total counts for the whole program's execution. What about space usage at different points in the program's execution, for example? And reimplementing heap profiling code for each project is a pain.

Massif can save you this effort.

First off, as for normal Valgrind use, you probably want to compile with debugging info (the -g flag). But, as opposed to Memcheck, you probably do want to turn optimisation on, since you should profile your program as it will be normally run.

Then, run your program with valgrind --tool=massif in front of the normal command line invocation. When the program finishes, Massif will print summary space statistics. It also creates a graph representing the program's heap usage in a file called massif.pid.ps, which can be read by any PostScript viewer, such as Ghostview.

It also puts detailed information about heap consumption in a file massif.pid.txt (text format) or massif.pid.html (HTML format), where pid is the program's process id.

To gather heap profiling information about the program prog, type:

% valgrind --tool=massif prog

The program will execute (slowly). Upon completion, summary statistics that look like this will be printed:

==27519== Total spacetime:   2,258,106 ms.B
==27519== heap:              24.0%
==27519== heap admin:         2.2%
==27519== stack(s):          73.7%

All measurements are done in spacetime, i.e. space (in bytes) multiplied by time (in milliseconds). Note that because Massif slows a program down a lot, the actual spacetime figure is fairly meaningless; it's the relative values that are interesting.

Which entries you see in the breakdown depends on the command line options given. The above example measures all the possible parts of memory:

As well as printing summary information, Massif also creates a file representing a spacetime graph, massif.pid.hp. It will produce a file called massif.pid.ps, which can be viewed in a PostScript viewer.

Massif uses a program called hp2ps to convert the raw data into the PostScript graph. It's distributed with Massif, but came originally from the Glasgow Haskell Compiler. You shouldn't need to worry about this at all. However, if the graph creation fails for any reason, Massif will tell you, and will leave behind a file named massif.pid.hp, containing the raw heap profiling data.

Here's an example graph:

The graph is broken into several bands. Most bands represent a single line of your program that does some heap allocation; each such band represents all the allocations and deallocations done from that line. Up to twenty bands are shown; less significant allocation sites are merged into "other" and/or "OTHER" bands. The accompanying text/HTML file produced by Massif has more detail about these heap allocation bands. Then there are single bands for the stack(s) and heap admin bytes.

Note: it's the height of a band that's important. Don't let the ups and downs caused by other bands confuse you. For example, the read_alias_file band in the example has the same height all the time it's in existence.

The triangles on the x-axis show each point at which a memory census was taken. These aren't necessarily evenly spread; Massif only takes a census when memory is allocated or deallocated. The time on the x-axis is wallclock time, which is not ideal because you can get different graphs for different executions of the same program, due to random OS delays. But it's not too bad, and it becomes less of a problem the longer a program runs.

Massif takes censuses at an appropriate timescale; censuses take place less frequently as the program runs for longer. There is no point having more than 100-200 censuses on a single graph.

The graphs give a good overview of where your program's space use comes from, and how that varies over time. The accompanying text/HTML file gives a lot more information about heap use.

The information should be pretty accurate. Some approximations made might cause some allocation contexts to be attributed with less memory than they actually allocated, but the amounts should be miniscule.

The heap admin spacetime figure is an approximation, as described above. If anyone knows how to improve its accuracy, please let us know.