Consider this code: x = 2 ^ (16 - (y And 15)) You can, however, use lookup tables for the same effect. If you don't have a single constant value, but a set of alternating values, you can't use the loop invariant techniques described above. You can pre-calculate the value as a constant like this: Const z = Not 192Īgain, your compiler might do this for you, so check it out. What's wrong? You possibly evaluate Not 192 on every execution. Consider this simple innocent-looking expression: x = y And Not 192 Replace invariant expressions with pre-calculated values (constants). This technique is a special case of loop invariants. The performance is the same, you're lucky since you don't need to Compile both examples and measure the performance. Your compiler might optimize loop invariants for you. To make the loop faster, move the invariant out of the inner loop: For y = 0 to Height-1

Widthĭoesn't change during the loop, nor does y change within the Inner loop, even though its value is always the same. In the following example, y*Width is evaluated on every iteration of the Move loop invariants out of the loopĪ loop invariant is an expression whose value doesn't change during the loop. Loop if the loop should be skipped sometimes (executed zero times). It also makes sense if evaluating the loop condition takes a considerable amount of time.īe sure not to overuse this technique. When to use this trick? It makes sense if the loop is nested inside another loop and execution enters the loop a large number of times. Loop #1Įvaluates its condition n+1 times, but loop #2 evaluates only Save one evaluation! Assume the loop runs n times. Here's the optimization trick: If the loop should execute at As far as optimization is concerned, the idea is the same. Note on loop #2: In some languages, such as Pascal, the post-condition loop mustīe written with an 'until' condition such as repeat.until condition=false. The other is the post-condition loop where the condition is at the end. One is the pre-condition loop where your loop condition is at the start of the loop. Most programming languages have at least two types of loops. Operators and picking the fastest data types. Miracles by eliminating unnecessary statements, choosing the right Makes a difference as it executes a million times. One that executes the largest number of times.

With nested loops, put your efforts on the innermost loop. What can we do about it? Focus on the inner loop As it happens, the program runs at a snail's pace. The inner code runs through each pixel, a total of x* y times, to process the pixels one after the other. A typical piece of code looks like this: For y = 0 to Height-1 This is done in two nested loops: the y direction and Save the images, it needs to process the arrays element by element, In simple arrays such as Data(x,y) or data. IntroductionĬonsider an imaging application as an example. Loops are often where the problems lie in. Key to speed up the program is to make the loops run faster. Loops are often the performance bottlenecks of an application.

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