PPT-On Tuning Microarchitecture

for Programs Daniel Crowell Wenbin Fang and Evan Samanas Summary A flexible framework for microarchitecture adaptivity which separates software policies from hardware mechanism C ase study adaptive cache. Presented . by:. . Rastislav Vajdák. . Senior Test Engineer. . . Oxymat. -Slovakia, s.r.o.. Fine tuning and setting PSA. OC input / output parameters. Tools. Start . o. f system to test . 6.375 Final Project. Ming Liu, . Shuotao. . Xu. Motivation. Today’s Database Management Systems (DBMS): software running on a standard operating system on a general purpose CPU. DBMS frequently used in analytics and scientific computing, but bottlenecked by:. When and How to Improve Code Performance?. Ivaylo Bratoev. Telerik Corporation. www.telerik.com. Actual . vs. Perceived Performance. Example: . “Vista's file copy performance is noticeably worse than Windows XP” . la microarchitecture. !. Burton Smith. Microsoft. Verities. Parallelism is now our lifeblood. We must be able to use all varieties of it. Locality is still important, especially spatial. Pollack’s Rule (AKA AT. By Hilary . Janysek. What’s the difference?. Intonation: . . (noun) The correct or accurate pitching (placement) of intervals; the capacity to play or sing in tune.. Tuning: . . (verb) to adjust to the correct or given standard of pitch. . Kadin Tseng. Boston University. Scientific Computing and Visualization. Log on with your BU userid and Kerboros . password . If you don’t have BU userid, then use this:. userid: . tuta1 . . . tuta18 . ©Chad Kersey and Sudhakar Yalamanchili unless otherwise noted. Objectives. Detailed look at the implementation of a SIMT GPU. Example of the type of information propagated down the pipeline. Basis for the next assignment and the default project. Photoinduced. Fields. L. C. Basset, F. . J. . . Heremans. , C. G. Yale, B. B. Buckley, and A. . Awschalom. PRL 107, 266403 (2011). Motivation. NV centers are sensitive to their local environment -> sample . Mehrzad Samadi. 1. , Janghaeng Lee. 1. , D. Anoushe Jamshidi. 1. , Amir Hormati. 2. , and Scott Mahlke. 1. University of Michigan. 1. , Google . Inc.. 2. December 2013. Compilers creating custom processors. ©Chad Kersey and Sudhakar Yalamanchili unless otherwise noted. Objectives. Detailed look at the implementation of a SIMT GPU. Example of the type of information propagated down the pipeline. Basis for the next assignment and the default project. Objectives. Detailed look at the implementation of a SIMT GPU. Example of the type of information propagated down the pipeline. Basis for the next assignment and the default project. Reading. C. Kersey, “HARP Instruction Set Manual”. 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 . Required. : PM. : . Ch. 8.1-3, . pgs. 109-114. Code: . Ch. 17, . pgs. 206-237. Recommended. : . Wiki. : Microarchitecture. . Wiki. : . Addressing_mode. . Wiki. : Three-state . logic. Lab.