PPT-Generating Compiler Optimizations from Proofs

Ross Tate Michael Stepp Sorin Lerner University of California San Diego Optimizing by Hand Original for i 0 i lt 50 i for j 0 j lt 50 j imgi50 j fi j. ucsdedu Abstract We present an automated technique for generating compiler op timizations from examples of concrete programs before and after improvements have been made to them The key technical insight of our technique is that a proof of equivalenc WEATHERIZATION ENERGY AUDITOR SINGLE FAMILY. WEATHERIZATION ASSISTANCE PROGRAM STANDARDIZED CURRICULUM – . December 2012. By attending this session, participants will be able to:. Formulate solutions to handle typical barriers to weatherization resources.. Chapter 1, Part III: Proofs. Summary. Proof Methods. Proof Strategies. Introduction to Proofs. Section 1.7. Section Summary. Mathematical Proofs. Forms of Theorems. Direct Proofs. Indirect Proofs. Proof of the . Learner Objective: I will calculate midpoints of segments and complete proofs 
 requiring that more than one pair of triangles be shown congruent.. Advanced Geometry. Learner Objective: I will calculate midpoints of segments and complete proofs 
 requiring that more than one pair of triangles be shown congruent.. First points:. This is written for mathematical proofs. Unless you are doing math econ, formal game theory, or statistical/econometric development (not application) you may not do formal mathematical proofs.. By Namita Dave. Overview. What are compiler optimizations?. Challenges with optimizations. Current Solutions. Machine learning techniques. Structure of Adaptive compilers. Introduction. O. ptimization . Generating Permutations. Many different algorithms have been developed to generate the n! permutations of this set.. We will describe one of these that is based on the . lexicographic . (or . dictionary. 1. NP-Completeness . Proofs. Presentation for use with the textbook, . Algorithm Design and Applications. , by M. T. Goodrich and R. Tamassia, Wiley, 2015. © 2015 Goodrich and Tamassia . NP-Completeness Proofs. . Iddo Tzameret. Royal Holloway, University of London . Joint work with Fu Li (Tsinghua) and Zhengyu Wang (Harvard). . Sketch. 2. Sketch. : a major open problem in . proof complexity . stems from seemingly weak results. Chapter 1, Part III: Proofs. Summary. Proof Methods. Proof Strategies. Introduction to Proofs. Section 1.7. Section Summary. Mathematical Proofs. Forms of Theorems. Direct Proofs. Indirect Proofs. Proof of the . Ross Tate. Michael Stepp. Sorin Lerner. University of California, San Diego. Optimizing by Hand. Original. for (i = 0; i < 50; i ). . for (j = 0; j < 50; j ). . img[i*50 j] = f(i, j);. T. Chen, T. Moreau, Z. Jiang, L. Zheng, S. Jiao, E. Yan, H. Shen, M. Cowan, L. Wang, Y. Hu, L. . Ceze. , C. . Guestrin. , and A. Krishnamurthy . Presentation by Grzegorz . Preconditions . for . Compiler Optimizations. Nuno Lopes. Advisor. : José Monteiro. Automatic. . Synthesis. . of. . Weakest. . Preconditions. for . Compiler. . Optimizations. Expectations for Compilers. Nuno Lopes . and. José Monteiro. Deriving preconditions by hand is hard; WPs are often non-trivial. WPs derived by hand are often wrong!. Weaker preconditions expose more optimization opportunities.