PPT-Code Tuning and Optimizations

When and How to Improve Code Performance Ivaylo Bratoev Telerik Corporation wwwtelerikcom Actual vs Perceived Performance Example Vistas file copy performance is noticeably worse than Windows XP . 49 BelAir 103 Levis Qc Canada G6V 6K9 mrueltopcontrolcom Keywords Process Control Optimization Oscilla tion Model PID Control Closed L oop Open Loop Stiction Backlash Non linearity Pseudorandombinary Sequence Generalized Binary Noise ABSTRACT Tradit Lo Susan J Eggers Henry M Levy Sujay S Parekh and Dean M Tullsen Dept of Computer Science and Engineering Box 352350 University of Washington Seattle WA 981952350 jlo sparekh eggers levycswashingtonedu Dept of Computer Science and Engineering Univer Every SQL Programmer Should Know. Kevin Kline. . Director of Engineering Services at SQL . Sentry. . Microsoft MVP since 2003. . Facebook, LinkedIn, Twitter at KEKLINE. . KEKline@sqlsentry.com. . and Evolution - . CSSE 375. Code Tuning. Shawn . and Steve. Left. – Even tuning an ancient instrument like a violin involves multiple steps. Here is fine tuning, being done after coarse tuning has been accomplished using the pegs on the other end.. Kadin Tseng. Boston University. Scientific Computing and Visualization. Serial Performance gain. Due to memory access. Due to caching. Due to vector . representations. Due to compiler. Due to other . 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. in . Dyninst. Andrew . Bernat. , Matthew Legendre. Instrumentation is Complicated. User perspective: . “Insert some new code here, here, and here.”. Dyninst’s. perspective:. Relocation. – Move code to make space for instrumentation. and High-Coverage Tests. Presented by Yoni Leibowitz. EXE & KLEE. Automatically Generating Inputs of Death. David Dill. Vijay . Ganesh. Cristian Cadar. Dawson Engler. Peter Pawlowski. KLEE. EXE. Unassisted & Automatic Generation of High-Coverage Tests for Complex System Programs. (aka: the complier). Dr. Mark . Brehob. EECS 470. Announcements. Milestone 2 due . t. oday. 1 page memo, don’t spend more than . 30 minutes . (sum of everyone) on it. . Not graded. Meet on Friday. Most already signed up. Prof. O. . Nierstrasz. Lecture notes by Marcus . Denker. © Marcus . Denker. Optimization. Roadmap. Introduction. Optimizations in the Back-end. The Optimizer. SSA Optimizations. Advanced Optimizations. Kaushik Datta. Dissertation Talk. December 4, 2009. Motivation. Multicore revolution has produced wide variety of architectures. Compilers alone fail to fully exploit multicore resources. Hand-tuning has become infeasible. Kadin Tseng. Boston University. Scientific Computing and Visualization. Outline. Introduction. Timing. Example Code. Profiling. Cache. Tuning. Parallel Performance. Code Tuning and Optimization. 2. Introduction. The Tuning Process. Benefits of Tuning. Why Tuning is Different. What is Tuning?. A collaborative, faculty-driven . process that . “harmonizes” curricula around defining what a . student should know and be able to do in a chosen . 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.