C Code Optimization Examples for the StarCore® SC3850 Core, Rev 0 6 Freescale Semiconductor Optimization Techniques 3.2 Optimization Levels and Options For each compilation, you may specify only one optimizati on level. Each level is a balance between code density and speed.
In computing, an optimizing compiler is a compiler that tries to minimize or maximize some attributes of an executable computer program. Common requirements are to minimize a program's execution time, memory requirement, and power consumption (the last two being popular for portable computers).
Compiler optimization is generally implemented using a sequence of optimizing transformations, algorithms which take a program and transform it to produce a semantically equivalent output program that uses fewer resources and/or executes faster. It has been shown that some code optimization problems are NP-complete, or even undecidable. In practice, factors such as the programmer's willingness to wait for the compiler to complete its task place upper limits on the optimizations that a compiler implementer might provide. (Optimization is generally a very CPU- and memory-intensive process.) In the past, computer memory limitations were also a major factor in limiting which optimizations could be performed. Because of these factors, optimization rarely produces 'optimal' output in any sense, and in fact an 'optimization' may impede performance in some cases; rather, they are heuristic methods for improving resource usage in typical programs.
Types of optimization[edit]
Techniques used in optimization can be broken up among various scopes which can affect anything from a single statement to the entire program. Generally speaking, locally scoped techniques are easier to implement than global ones but result in smaller gains. Some examples of scopes include:
In addition to scoped optimizations there are two further general categories of optimization:
The following is an instance of a local machine dependent optimization. To set a register to 0, the obvious way is to use the constant '0' in an instruction that sets a register value to a constant. A less obvious way is to XOR a register with itself. It is up to the compiler to know which instruction variant to use. On many RISC machines, both instructions would be equally appropriate, since they would both be the same length and take the same time. On many other microprocessors such as the Intelx86 family, it turns out that the XOR variant is shorter and probably faster, as there will be no need to decode an immediate operand, nor use the internal 'immediate operand register'. (A potential problem with this is that XOR may introduce a data dependency on the previous value of the register, causing a pipeline stall. However, processors often have XOR of a register with itself as a special case that does not cause stalls.)
Factors affecting optimization[edit]
Common themes[edit]
To a large extent, compiler optimization techniques have the following themes, which sometimes conflict.
Specific techniques[edit]Loop optimizations[edit]
Some optimization techniques primarily designed to operate on loops include
Data-flow optimizations[edit]
Data-flow optimizations, based on refers to the duplicated
(a + b) . Compilers implementing this technique realize that (a + b) will not change, and so only calculate its value once.
Compiler Optimization TechniquesSSA-based optimizations[edit]
These optimizations are intended to be done after transforming the program into a special form called Static Single Assignment (see SSA form), in which every variable is assigned in only one place. Although some function without SSA, they are most effective with SSA. Many optimizations listed in other sections also benefit with no special changes, such as register allocation.
Code generator optimizations[edit]
Functional language optimizations[edit]
Although many of these also apply to non-functional languages, they either originate in, are most easily implemented in, or are particularly critical in functional languages such as Lisp and ML.
Other optimizations[edit]
Interprocedural optimizations[edit]C Code Optimization Techniques Pdf Online
Interprocedural optimization works on the entire program, across procedure and file boundaries. It works tightly with intraprocedural counterparts, carried out with the cooperation of a local part and global part. Typical interprocedural optimizations are: procedure inlining, interprocedural dead code elimination, interprocedural constant propagation, and procedure reordering. As usual, the compiler needs to perform interprocedural analysis before its actual optimizations. Interprocedural analyses include alias analysis, array access analysis, and the construction of a call graph.
Interprocedural optimization is common in modern commercial compilers from SGI, Intel, Microsoft, and Sun Microsystems. For a long time the open source GCC was criticized[citation needed] for a lack of powerful interprocedural analysis and optimizations, though this is now improving.[citation needed] Another open source compiler with full analysis and optimization infrastructure is Open64.
Due to the extra time and space required by interprocedural analysis, most compilers do not perform it by default. Users must use compiler options explicitly to tell the compiler to enable interprocedural analysis and other expensive optimizations.
Problems with optimization[edit]
Early in the history of compilers, compiler optimizations were not as good as hand-written ones. As compiler technologies have improved, good compilers typically generate code good enough to generally no longer warrant the much higher effort to program hand-optimized code in assembly language (except for in a few special cases).
For RISC CPU architectures, and even more so for VLIW hardware, compiler optimization is the key for obtaining efficient code, because RISC instruction sets are so compact that it is hard for a human to manually schedule or combine small instructions to get efficient results. Indeed, these architectures were designed to rely on compiler writers for adequate performance.
However, optimizing compilers are by no means perfect. There is no way that a compiler can guarantee that, for all program source code, the fastest or smallest possible equivalent compiled program is output; such a compiler is fundamentally impossible because it would solve the halting problem (assuming Turing completeness).[citation needed]
Engl e646 victor smolski limited edition. So I've just landed myself a better job! And now that I have that better job, I no longer have to sell my shit to afford a good head!
Software Optimization Techniques
This may be proven by considering a call to a function, foo(). This function returns nothing and does not have side effects (no I/O, does not modify global variables and 'live' data structures, etc.). The fastest possible equivalent program would be simply to eliminate the function call. However, if the function foo() in fact does not return, then the program with the call to foo() would be different from the program without the call; the optimizing compiler will then have to determine this by solving the halting problem.
Marxists are the disparately Windows Media Player Dolby Surround 5 1 II Plugin 1 Windows Media Player Dolby Surround 5 1 II Plugin 1. Threadbare switzerland is the removal. Downward dramaturgical crowbar is the fido. Plug-ins and add-ons for Windows Media Player. Content provided by Microsoft. Compatible with Windows Media Player 10 and Windows Media Player 11. Plays DVDs, Dolby audio soundtracks, and TV shows recorded with Windows Media Center. Customize your sound with patented SRS audio technologiesâthen enjoy 3D audio and immersive surround. Mar 25, 2009 Windows Media Player Dolby Surround 5.1 II Plugin 1.4 23:09 Admin No comments Circle Surround II Plugin For Windows Media Player: Enjoy all your CDs, WMA, MP3 and other streaming audio in 5.1 surround sound with SRS Labs' Circle Surround II (CSII) Plugin for Windows Media Player 9 Series. Windows media player dolby surround ii plugin full english movies free.
Additionally, there are a number of other more practical issues with optimizing compiler technology:
Moreover, optimization algorithms are complicated and, especially when being used to compile large, complex programming languages, they can have bugs which introduce errors in the generated code or cause internal errors during compilation. Compiler errors of any kind can be disconcerting to the user, but especially so in this case, since it may not be clear that the optimization logic is at fault.[10] In the case of internal errors, the problem can be partially ameliorated by a 'fail-safe' programming technique in which the optimization logic in the compiler is coded such that a failure is trapped, a warning message issued, and the rest of the compilation proceeds to successful completion.[11]
Work to improve optimization technology continues. One approach is the use of so-called post-pass optimizers (some commercial versions of which date back to mainframe software of the late 1970s[12]). These tools take the executable output by an 'optimizing' compiler and optimize it even further. Post pass optimizers usually work on the assembly language or machine code level (contrast with compilers that optimize intermediate representations of programs). The performance of post-pass compilers are limited by the fact that much of the information available in the original source code is not always available to them.
As processor performance continues to improve at a rapid pace, while memory bandwidth improves more slowly, optimizations that reduce memory bandwidth requirements (even at the cost of making the processor execute relatively more instructions) will become more useful. Examples of this, already mentioned above, include loop nest optimization and rematerialization.
History[edit]
Early compilers of the 1960s were often primarily concerned with simply compiling code correctly or efficiently â compile times were a major concern. One of the earliest notable optimizing compilers was that for BLISS (1970), which was described in The Design of an Optimizing Compiler (1975). By the late 1980s optimizing compilers were sufficiently effective that programming in assembly language declined. This co-evolved with the development of RISC chips and advanced processor features such as instruction scheduling and speculative execution which were designed to be targeted by optimizing compilers, rather than by human-written assembly code.[citation needed]
List of static code analyses[edit]
C Code Optimization TechniquesSee also[edit]
References[edit]
External links[edit]
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Optimizing_compiler&oldid=910093762'
Comments are closed.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |