'Goto l2' presentation slideshows

Lecture 11: Code Optimization

Lecture 11: Code Optimization. CS 540 George Mason University. Code Optimization. REQUIREMENTS: Meaning must be preserved (correctness) Speedup must occur on average. Work done must be worth the effort. OPPORTUNITIES: Programmer (algorithm, directives) Intermediate code Target code.

585 views • 58 slides

Intermediate Representations (Chapter 4)

Intermediate Representations (Chapter 4). Outline. Issues in IR design High-Level IRs Medium-Level IRs Low-Level IRs Multi-Level IRs MIR, HIR, and LIR ICAN (Informal Compiler Algorithm Notation) Representations Other IRs Conclusions. Issues in IR Design. Portability

765 views • 54 slides

Code generation and Instruction Selection

Code generation and Instruction Selection. Intermediate Code generator. Front end. output code must be correct output code must be of high quality code generator should run efficiently. Code generator. input. output. Symbol table. Issues in the design of code generator.

566 views • 43 slides

620 views • 40 slides

Code generation and data types

Code generation and data types. Translation and Address Calculation. Outline. Intermediate codes 3-address code P-code Code generation, using attribute grammar Data types Primitive data types Arrays and Strings Records Address calculation. Intermediate Codes. 3-address code P-code.

408 views • 38 slides

15-820A Proving Software with PVS

15-820A Proving Software with PVS. Edmund Clarke Daniel Kroening Carnegie Mellon University. Outline. Modeling Software with PVS Complete Example for Sequential Software, including proof The Magic GRIND Modularization. Modeling Software with PVS. int a[10]; unsigned i; int main() {

499 views • 35 slides

15-820A Proving Software with PVS

15-820A Proving Software with PVS. Edmund Clarke Daniel Kroening Carnegie Mellon University. Outline. Modeling Software with PVS Complete Example for Sequential Software, including proof The Magic GRIND Modularization. Modeling Software with PVS. int a[10]; unsigned i; int main() {

355 views • 35 slides

Intermediate representation

Intermediate representation. Goals: encode knowledge about the program facilitate analysis facilitate retargeting facilitate optimization. HIR. semantic analysis. HIR. intermediate code gen. scanning parsing. LIR. LIR. code gen. optim. Intermediate representation. Components

524 views • 27 slides

Intermediate representation

Intermediate representation. Goals: encode knowledge about the program facilitate analysis facilitate retargeting facilitate optimization. HIR. semantic analysis. HIR. intermediate code gen. scanning parsing. LIR. LIR. code gen. optim. Intermediate representation. Components

312 views • 27 slides

Recitation 3

Outline Recursive procedure Complex data structures Arrays Structs Unions Function pointer Reminders Lab 2: Wed. 11:59PM Lab 3: start early. Minglong Shao E-mail: shaoml+213@cs.cmu.edu Office hours: Thursdays 5-6PM Wean Hall 1315. Recitation 3.

333 views • 20 slides

TARGET CODE GENERATION

Prepared By: DHEERAJ KUMAR JAIN-04CS3015. TARGET CODE GENERATION. INTRODUCTION. FACTORS EFFECTING THE GENERATION OF TARGET CODE. Form of Input-How Complex/Simple is the IMC Absolute code Relocatable code Hardware facility to do the translation Compiler book marking Assembly code

332 views • 13 slides