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- 1. Code Optimization in Compiler Design • Last Updated: 04 Sep, 2024 • Enhancing performance and efficiency of executable code
- 2. Introduction to Code Optimization • Improves execution time • Minimizes resource usage • Enhances overall system performance • Applied during compilation without altering program functionality
- 3. Objectives of Code Optimization • Must preserve program meaning • Increase program speed and performance • Keep compilation time reasonable • Avoid compile-time delays
- 4. When and Why to Optimize? • Performed at development end-stage • May reduce readability • Used to: • - Reduce space and increase compilation speed • - Automate tedious optimization tasks • - Promote code reusability
- 5. Types of Code Optimization • 1. Machine Independent: • - Improves intermediate code • - No CPU/memory-specific details • 2. Machine Dependent: • - Optimizes target code • - Utilizes registers, absolute memory
- 6. Ways to Optimize Code • 1. Compile Time Evaluation • 2. Variable Propagation • 3. Constant Propagation • 4. Constant Folding • 5. Copy Propagation • 6. Common Sub Expression Elimination • 7. Dead Code Elimination • 8. Unreachable Code Elimination
- 7. Examples of Optimization • Compile Time Eval: • A = 2*(22.0/7.0)*r (computed at compile time) • Constant Folding: • x = 2 * 5 -> x = 10 • Copy Propagation: • Replace x with a if x = a
- 8. Unreachable Code Example • Before: • cout << "GFG!"; • return 0; • cout << num; • After: • cout << "GFG!"; • return 0;
- 9. Function Optimization Techniques • Function Inlining • Function Cloning (e.g., Overloading) • Strength Reduction: • a = a * 16 -> a = a << 4
- 10. Loop Optimization Techniques • 1. Code Motion • 2. Loop Jamming • 3. Loop Unrolling
- 11. Example: Loop Jamming • Before: • for(...) x = ...; • for(...) y = ...; • After: • for(...) { x = ...; y = ...; }
- 12. Where to Apply Optimization? • Source Program: Algorithm, loops • Intermediate Code: Address transformations • Target Code: Registers, select/move instructions
- 13. Optimization Levels • Local: Basic blocks (e.g., Value Numbering) • Regional: Extended blocks (e.g., Loop Unrolling) • Global: Functions and loops (e.g., Live Var Analysis) • Interprocedural: Across procedures (e.g., Inline Substitution)
- 14. Advantages of Code Optimization • Better performance and speed • Reduced code size and power usage • Improved portability • Easier maintenance
- 15. Disadvantages of Code Optimization • Increases compilation time • Adds complexity • Risk of bugs • Hard to assess benefits
- 16. Conclusion • Code optimization is vital for efficient compiler design • Includes various techniques (loops, dead code, folding) • Leads to faster, smaller, and efficient code