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Code optimization techniques in compiler design pdf: >> http://cvm.cloudz.pw/download?file=code+optimization+techniques+in+compiler+design+pdf << (Download)
Code optimization techniques in compiler design pdf: >> http://cvm.cloudz.pw/read?file=code+optimization+techniques+in+compiler+design+pdf << (Read Online)
Note: Complexity depends on the “window size." Optimization. • Machine-dependent issues. • Machine-independent issues. Compiler notes #8, 20070622, Techniques. • Analysis of dependence graphs. • Analysis of basic blocks and flow graphs. • Semantics-preserving transformations. • Algebraic transformations.
leaders: the first instructions in some basic block (instruction just past the end of the intermediate program is not included as a leader). The rules for finding leaders are: 1. The first three-address instruction in the intermediate code. 2. Any instruction that is the target of a conditional or unconditional jump. 3. Any instruction
Compiler can improve loops, procedure calls, and address calculations. – Typically only optimizing compilers include this phase. ? Target code: – Compilers can use registers efficiently. – Peephole transformation can be applied. CS 5300 - SJAllan. Code Optimization. 6. Peephole Optimizations. ? A simple technique for
Intermediate Code &. Local Optimizations. Compiler Design I (2011). 2. Lecture Outline. • Intermediate code. • Local optimizations. Compiler Design I (2011). 3 . Apply across method boundaries. Most compilers do (1), many do (2) and very few do (3). Compiler Design I (2011). 23. Cost of Optimizations. • In practice, a
Trade offs: Effort of implementing a technique + time taken during compilation vs. optimization achieved. For instance, lexical/semantic/code generation phases require linear time in terms of size of programs, whereas certain optimization techniques may require quadratic or cubic order. In many cases simple techniques
161. Code Optimization. Compiler Design, WS 2005/2006. 162. Code Optimization. – Two steps: 1. Analysis (to uncover optimization opportunities). 2. Optimizing transformation. – Optimization: • must be semantically correct. • shall improve program according to some criterion. (program rarely optimal under any measure).
applications, it has become necessary to design high level language compilers for ters. 2. Low level addressing code optimization: code motion and common expression elimination for addressing code. 3. Code consolidation: combining a set of scattered sim- algorithms,2,4,5 are used throughout the compiler for both.
5 –. Datorarkitektur 2006. Machine-Independent Optimizations. Optimizations you should do regardless of processor / compiler. Code Motion. Reduce frequency with which computation performed. If it will always produce same result. Especially moving code out of loop for (i = 0; i < n; i++) for (j = 0; j < n; j++) a[n*i + j] = b[j];.
Aggregated data structure. Arrays, structures. Symbol table. Address calculation for references. 0 Control flows. If-then-else, for-loop, while-loop, switch-case. Labels and simple branches. 0 Procedures. Activation records. Run-time stack. 0 Objects. Object representation. Method dispatching. 5. CODE
Optimization is a program transformation technique, which tries to improve the code by making it consume less resources i. e. CPU, Memory and deliver high speed. In optimization, high-level general programming constructs are replaced by very efficient low-level programming codes. A code optimizing process must follow
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