-* Writing performant .NET and Mono applications
+* Writing better performing .NET and Mono applications
+
+<center>
+Miguel de Icaza (miguel@novell.com)<br>
+Ben Maurer (bmaurer@users.sourceforge.net)
+</center>
The following document contains a few hints on how to improve
the performance of your Mono/.NET applications.
These are just guidelines, and you should still profile your
code to find the actual performance problems in your
- application.
+ application. It is never a smart idea to make a change with the
+ hopes of improving the performance of your code without first
+ measuring. In general, these guidelines should serve as ideas
+ to help you figure out `how can I make this method run faster'.
+
+ It is up to you to figure out, `Which method is running slowly.'
** Using the Mono profiler
+
+ So, how does one measure what method are running slowly? A profiler
+ helps with this task. Mono includes a profiler that is built
+ into the runtime system. You can invoke this profiler on your program
+ by running with the --profile flag.
- To obtain memory consumption and measure the time spent on
- functions and the number of times a function is called in
- Mono, you can invoke the runtime with the --profile flag, like this:
-
-<pre>
+<pre class="shell">
mono --profile program.exe
</pre>
for profiling. The default Mono profiler will record the time
spent on a routine, the number of times the routine called,
the memory consumed by each method broken down by invoker, and
- the total amount of memory consumed, this is what it looks
- like:
-<pre>
+ the total amount of memory consumed.
+
+ It does this by asking the JIT to insert a call to the profiler
+ every time a method is entered or left. The profiler times the
+ amount of time elapsed between the beginning and the end of the
+ call. The profiler is also notified of allocations.
+
+ When the program has finished executing, the profiler prints the
+ data in human readable format. It looks like:
+
+<pre class="shell">
Total time spent compiling 227 methods (sec): 0.07154
Slowest method to compile (sec): 0.01893: System.Console::.cctor()
Time(ms) Count P/call(ms) Method name
Total memory allocated: 448 KB
</pre>
+ At the top, it shows each method that is called. The data is sorted
+ by the total time that the program spent within the method. Then
+ it shows how many times the method was called, and the average time
+ per call.
+
+ Below this, it shows the top callers of the method. This is very useful
+ data. If you find, for example, that the method Data::Computate () takes
+ a very long time to run, you can look to see if any of the calls can be
+ avoided.
+
+ Two warnings must be given about the method data. First,
+ the profiler has an overhead associated with it. As such,
+ a high number of calls to a method may show up as consuming
+ lots of time, when in reality they do not consume much time
+ at all. If you see a method that has a very high number of
+ calls, you may be able to ignore it. However, do consider
+ removing calls if possible, as that will sometimes help
+ performance. This problem is often seen with the use
+ of built in collection types.
+
+ Secondly, due to the nature of the profiler, recursive calls
+ have extremely large times (because the profiler double counts
+ when the method calls itself). One easy way to see this problem
+ is that if a method is shown as taking more time than the Main
+ method, it is very likely recursive, and causing this problem.
+
+ Below the method data, allocation data is shown. This shows
+ how much memory each method allocates. The number beside
+ the method is the total amount of memory. Below that, it
+ is broken down into types. Then, the caller data is given. This
+ data is again useful when you want to figure out how to eliminate calls.
+
You might want to keep a close eye on the memory consumption
and on the method invocation counts. A lot of the
performance gains in MCS for example came from reducing its
- memory usage, as opposed to changes in the execution path.
+ memory usage, as opposed to changes in the execution path.
+
+** Profiling without JIT instrumentation
+
+ You might also be interested in using mono --aot to generate
+ precompiled code, and then use a system like `oprofile' to
+ profile your programs.
** Memory Management in the .NET/Mono world.
is a great productivity gain, but if you create thousands of
objects, that will make the garbage collector do more work,
and it might slow down your application.
+
+ Remember, each time you allocate an object, the GC is forced
+ to find space for the object. Each object has an 8 byte overhead
+ (4 to tell what type it is, then 4 for a sync block). If
+ the GC finds that it is running out of room, it will scan every
+ object for pointers, looking for unreferenced objects. If you allocate
+ extra objects, the GC then must take the effort to free the objects.
+
+ Mono uses the Boehm GC, which is a conservative collector,
+ and this might lead to some memory fragmentation and unlike
+ generational GC systems, it has to scan the entire allocated
+ memory pool.
+
+*** Boxing
+ The .NET framework provides a rich hierarchy of object types.
+ Each object not only has value information, but also type
+ information associated with it. This type information makes
+ many types of programs easier to write. It also has a cost
+ associated with it. The type information takes up space.
+
+ In order to reduce the cost of type information, almost every
+ Object Oriented language has the concept of `primitives'.
+ They usually map to types such as integers and booleans. These
+ types do not have any type information associated with them.
+
+ However, the language also must be able to treat primitives
+ as first class datums -- in the class with objects. Languages
+ handle this issue in different ways. Some choose to make a
+ special class for each primitive, and force the user to do an
+ operation such as:
+<pre class="shell">
+// This is Java
+list.add (new Integer (1));
+System.out.println (list.get (1).intValue ());
+</pre>
+
+ The C# design team was not satisfied with this type
+ of construct. They added a notion of `boxing' to the language.
+
+ Boxing preforms the same thing as Java's <code>new Integer (1)</code>.
+ The user is not forced to write the extra code. However,
+ behind the scenes the <em>same thing</em> is being done
+ by the runtime. Each time a primitive is cast to an object,
+ a new object is allocated.
+
+ You must be careful when casting a primitive to an object.
+ Note that because it is an implicit conversion, you will
+ not see it in your code. For example, boxing is happening here:
+
+<pre class="shell">
+ArrayList foo = new ArrayList ();
+foo.Add (1);
+</pre>
+
+ In high performance code, this operation can be very costly.
-** foreach
+*** Using structs instead of classes for small objects
+
+ For small objects, you might want to consider using value
+ types (structs) instead of object (classes).
+
+ However, you must be careful that you do not use the struct
+ as an object, in that case it will actually be more costly.
+
+ As a rule of thumb, only use structs if you have a small
+ number of fields (totaling less than 32 bytes), and
+ need to pass the item `by value'. You should not box the object.
+
+*** Assisting the Garbage Collector
+
+ Although the Garbage Collector will do the right thing in
+ terms of releasing and finalizing objects on time, you can
+ assist the garbage collector by clearing the fields that
+ points to objects. This means that some objects might be
+ eligible for collection earlier than they would, this can help
+ reduce the memory consumption and reduce the work that the GC
+ has to do.
+
+** Common problems with <tt>foreach</tt>
The <tt>foreach</tt> C# statement handles various kinds of
different constructs (about seven different code patterns are
like ArrayList is more efficient than using the ArrayList
indexer, the pressure introduced due to the extra memory
requirements and the demands on the garbage collector make it
- more inneficient.
+ more inefficient.
There is no straight-forward rule on when to use foreach, and
when to use a manual loop. The best thing to do is to always
use foreach, and only when profile shows a problem, replace
foreach with for loops.
-
-*** Using structs instead of classes for small objects
-
- For small objects, you might want to consider using value
- types (structs) instead of object (classes).
-
-** Assisting the Garbage Collector
-
- Although the Garbage Collector will do the right thing in
- terms of releasing and finalizing objects on time, you can
- assist the garbage collector by clearing the fields that
- points to objects. This means that some objects might be
- elegible for collection earlier than they would, this can help
- reduce the memory consumption and reduce the work that the GC
- has to do.
projects / mono.git / blobdiff