Profile-guided optimization lets you optimize an output file, where the optimizer uses data from test runs of the .exe or .dll file. The data represents how the program is likely to perform in a production environment.
Profile-guided optimizations are only available for x86 or x64 native targets. Profile-guided optimizations are not available for output files that run on the common language runtime. Even if you produce an assembly with mixed native and managed code (by using the /clr compiler option), you cannot use profile-guided optimization on just the native code. If you attempt to build a project with these options set in the IDE, a build error results.
Information that is gathered from profiling test runs overrides optimizations that would otherwise be in effect if you specify /Ob, /Os, or /Ot. For more information, see /Ob (Inline Function Expansion) and /Os, /Ot (Favor Small Code, Favor Fast Code).
Steps to optimize your app
To use profile-guided optimization, follow these steps to optimize your app:
Compile one or more source code files with /GL.
Each module built with /GL can be examined during profile-guided optimization test runs to capture run-time behavior. Every module in a profile-guided optimization build does not have to be compiled with /GL. However, only those modules compiled with /GL are instrumented and later available for profile-guided optimizations.
Using both /LTCG and /GENPROFILE or /FASTGENPROFILE creates a .pgd file when the instrumented app is run. After test-run data is added to the .pgd file, it can be used as input to the next link step (creating the optimized image). When specifying /GENPROFILE, you can optionally add a PGD=filename argument to specify a nondefault name or location for the .pgd file. The combination of /LTCG and /GENPROFILE or /FASTGENPROFILE linker options replaces the deprecated /LTCG:PGINSTRUMENT linker option.
Profile the application.
Each time a profiled EXE session ends or a profiled DLL is unloaded, a appname!#.pgc file is created. A .pgc file contains information about a particular application test run. # is a number starting with 1 that is incremented based on the number of other appname!#.pgc files in the directory. You can delete a .pgc file if the test run does not represent a scenario you want to optimize.
During a test run, you can force closure of the currently open .pgc file and the creation of a new .pgc file with the pgosweep utility (for example, when the end of a test scenario does not coincide with application shutdown).
Your application can also directly invoke a PGO function, PgoAutoSweep, to capture the profile data at the point of the call as a .pgc file. This can give you finer control over the code covered by the captured data in your .pgc files. For an example of how to use this function, see the PgoAutoSweep documentation.
When you create your instrumented build, by default, data collection is done in non-thread-safe mode, which is faster but may not be completely accurate. By using the EXACT argument to /GENPROFILE or /FASTGENPROFILE, you can specify data collection in thread-safe mode, which is more accurate but slower. This option is also available if you set the deprecated PogoSafeMode environment variable, or the deprecated /POGOSAFEMODE linker option, when you create your instrumented build.
Link using /LTCG and /USEPROFILE.
Use both the /LTCG and /USEPROFILE linker options to create the optimized image. This step takes as input the .pgd file. When you specify /USEPROFILE, you can optionally add a PGD=filename argument to specify a non-default name or location for the .pgd file. You can also specify this name by using the deprecated /PGD linker option. The combination of /LTCG and /USEPROFILE replaces the deprecated /LTCG:PGOPTIMIZE and /LTCG:PGUPDATE linker options.
It is even possible to create the optimized output file and later determine that additional profiling would be useful to create a more optimized image. If the instrumented image and its .pgd file are available, you can do additional test runs and rebuild the optimized image with the newer .pgd file, by using the same /LTCG and /USEPROFILE linker options.
Optimizations performed by PGO
The following is a list of the profile-guided optimizations:
Inlining - For example, if there exists a function A that frequently calls function B, and function B is relatively small, then profile-guided optimizations will inline function B in function A.
Virtual Call Speculation - If a virtual call, or other call through a function pointer, frequently targets a certain function, a profile-guided optimization can insert a conditionally-executed direct call to the frequently-targeted function, and the direct call can be inlined.
Register Allocation - Optimizing with profile data results in better register allocation.
Basic Block Optimization - Basic block optimization allows commonly executed basic blocks that temporally execute within a given frame to be placed in the same set of pages (locality). This minimizes the number of pages used, thus minimizing memory overhead.
Size/Speed Optimization - Functions where the program spends a lot of time can be optimized for speed.
Function Layout - Based on the call graph and profiled caller/callee behavior, functions that tend to be along the same execution path are placed in the same section.
Conditional Branch Optimization - With the value probes, profile-guided optimizations can find if a given value in a switch statement is used more often than other values. This value can then be pulled out of the switch statement. The same can be done with if/else instructions where the optimizer can order the if/else so that either the if or else block is placed first depending on which block is more frequently true.
Dead Code Separation - Code that is not called during profiling is moved to a special section that is appended to the end of the set of sections. This effectively keeps this section out of the often-used pages.
EH Code Separation - The EH code, being exceptionally executed, can often be moved to a separate section when profile-guided optimizations can determine that the exceptions occur only on exceptional conditions.
Memory Intrinsics - The expansion of intrinsics can be decided better if it can be determined if an intrinsic is called frequently. An intrinsic can also be optimized based on the block size of moves or copies.
If you use Visual Studio 2013, you can use the automated Profile Guided Optimization Plug-In for Visual C++ in the Performance and Diagnostics Hub to simplify and streamline the optimization process within Visual Studio. This plug-in is not available in later versions of Visual Studio.
Read more about these environment variables, functions, and tools you can use in profile-guided optimizations:
Environment Variables for Profile-Guided Optimizations
These variables can be used to specify run-time behavior of testing scenarios. They have been deprecated in favor of new linker options; read this to help you move from the environment variables to the linker options.
A function you can add to your app to provide fine-grained .pgc file data capture control.
A command-line utility that writes all profile data to the .pgc file, closes the .pgc file, and opens a new .pgc file.
A command-line utility that adds profile data from one or more .pgc files to the .pgd file.
How to: Merge Multiple PGO Profiles into a Single Profile Examples of pgomgr usage.