As the following 10 rules only reflect my experience on a high level, I would be happy to get feedbackto extend my list. Let take a web portal as an example where the pages are generated from a web application that retrieves data from a database. So caching is one of the things you have to keep in mind when you want to get performance. Sometimes it can also be interesting to look at specialized programming languages like. Ces Cookies (petits fichiers texte) permettent de suivre votre navigation, actualiser votre panier, vous reconnaitre lors de votre prochaine visite et sécuriser votre connexion. Pour en savoir plus et paramétrer les traceurs. Logical Approaches: Use Lookup Tables ul li Table lookups can be much faster than following a logical computation diagram of logical values: /li /ul 1 1 B A. Other Tuning: Recoding in Low-Level Language ul li Rewrite sections of code in lower-level (and probably much more efficient) language language depends on starting level - C - assembler only be done at bottlenecks can vary greatly /li /ul. Tuning Loops: Sentinel Values ul li Test value placed after end of array to guarantee termination false; (!found) (i n) (ai testval) true; (found) /Value found an; testval; (ai!
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Tuning Loops: Minimizing Interior Work ul li Move repeated computation outside (i0; i n; i) balancei primecard pcentpay; (primecard pcentpay; (i0; i n; i) newamt; balancei*payrate; /li /ul. Logical Approaches: Lazy Evaluation ul li Idea: wait to compute until youre sure you need the value you never actually use the value! Tuning Loops: Jamming ul li Combine two loops (i0; i n; i).0; (i0; i n; i).03; (i0; i n; i).0;.03; /li /ul. Horizontal scalability (or scale out ) means to run the application on more than one box. Try to get an expert who has experience with the type of application you want to build. Without a tool you are tuning a blackbox! This said, developers have to learn about Threads, Concurrency, Locking etc. Tuning Loops: Unrolling ul li Do more work inside loop for fewer iterations unroll: no more loop done by compilers (if recognizable) (i0; i n; i) i; (i0; i (n-1 i2) i; i1; (i n-1) n-1;.
Yes, I know you did this to have less effort to replace the database if neededbut believe me, this will not happen in the next 10 years and if it happens you will have other problems. Code Tuning, upcoming SlideShare, loading in 5, like this presentation? Define the requirements, it sounds obvious that a team should know what the requirements for performance, scalability and availability are, but in more than 90 of my engagements they didnt. Is 8 second fast? Performance requirements should be defined. Transforming Data: Use Caching ul li Store data instead of (re-)computing store length of an array (ended by sentinel) once computed repeated computation in loop in storing data is offset by accesses to same computation of initial computation. Define the possible optimizations and prioritize them by balancing possible optimization and effort/risk of the change. Therefore I would recommend to automate the process of analyzing performance. Nervous managers often think that having lots of developers optimize code will lead to better performance. See rule 5 for a tip when to stop. So stop tuning when the requirements are met even if you have the ambition to optimize the application to the limit. The answer is: When the requirements are not met (see first tip).
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