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March 16, 2007
Standard compiler optimization is no longer sufficient for competitive high performance computing. Here we discuss interprocedural analysis (IPA) or whole program analysis, its costs and benefits, and how it affects programmers.
Performance-sensitive programmers are accustomed to building their applications with compiler optimizations enabled. In the past, this might have been as simple as setting the -O option on the command line. Decades of research and experience on compiler analysis and code improvement have produced mature, reliable techniques, the vast majority of which focus on optimizing a single procedure at a time, using redundancy elimination, loop restructuring, register allocation, instruction scheduling, and so on. But it is not enough.
Current highly optimizing compilers all use some form of interprocedural or whole program analysis for best performance. At compile time, the compiler summarizes each procedure in the program; when all procedures are available, the compiler invokes an interprocedural analysis module to collect all the procedure summaries and propagates information from caller to callee and back. While this seems to break the advantages of separate compilation, it is done at link time. The procedures are then optimized using the new interprocedural information. Early implementations used programming environments or special build programs to manage the procedure summaries, which made it hard to migrate from traditional tools, such as make. Current methods are almost invisible, except for the extra time spent at the link step to generate better code using the extra information.
The importance of interprocedural analysis is demonstrated by looking at the SPEC CPU results page (http://www.spec.org/); the base flags for the various compilers all include IPA:
IBM -O5 (implies -qipa)
Intel -fast (implies -ipo)
Pathscale -Ofast (implies -ipa)
PGI -fast -Mipa=fast,inline
SGI -Ofast=ip35 (implies -IPA)
Sun -fast -xcrossfile
We ran the SPEC CPU2000 test suite using the PGI compiler with and without IPA. The performance improvements ranged up to 130 percent speedup, with a 7 percent speedup in the overall geometric mean, demonstrating that IPA is useful and critical to the performance of some applications.
One of the most useful and common benefits of IPA is automatic inlining of procedures, even across source files. Since the compiler has the whole program at link time, it can take a procedure from one object and inline it at a call site in another procedure. This typically reduces the cost of the procedure call, and allows the code for the inlined procedure to be better optimized since the calling context is explicit.
This can also be used to inline or generate special code for calls to system or math libraries. Until link time, it isn't always known what library a particular procedure will come from. Once it is known that fmax is resolved from libm.a, for instance, the compiler can replace the procedure call by fast inline code.
A less common technique is to create two or more versions of a procedure, each version optimized for a particular calling context. For instance, IPA may generate one version or clone to be optimized for the case when two C pointer arguments are known to be distinct, allowing more vectorization (for instance), and another version for the more general case. The compiler can be directed to replace some calls to the more optimized version where appropriate.
IPA can help optimize around procedure calls even when the call isn't inlined. IPA may be able to determine that the function is "pure," meaning that it does no I/O and doesn't read or write global variables. Code around calls to such functions can be moved above or below the call, since the call won't interfere with any other code in the caller. This gives the compiler more freedom when scheduling instructions or allocating registers.
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