Tuning the Code in Java

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74 Tuning the Code
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There are many techniques to reduce run-time when a hot spot is found Here are some suggestions which should be applied with care and with regression testing after each to be sure that the code still works Bear in mind that good compilers will do some of these for you, and in fact you may impede their efforts by complicating the program Whatever you try, measure its effect to make sure it helps
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Collect common subexpressions If an expensive computation appears multiple times do it in only one place and remember the result For example in 1 we
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showed a macro that computed a distance by calling s q r t twice in a row with the same values; in effect the computation was
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sqrt(dxwdx
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Compute the square root once and use its value in two places If a computation is done within a loop but does not depend on anything that changes within the loop move the computation outside, as when we replaced
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n = nstarting[c] ; f o r (i 0; i < n; i++) = (
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Replace expensive operations by cheap ones The term reduction in strerzgth refers to optimizations that replace an expensive operation by a cheaper one In olden times, this used to mean replacing multiplications by additions or shifts but that rarely buys much now Division and remainder are much slower than multiplication however, so there may be improvement if a division can be replaced with multiplication by the inverse, or a remainder by a masking operation if the divisor is a power of two Replacing array indexing by pointers in C or C++ might speed things up, although most compilers do this automatically Replacing a function call by a simpler calcula-
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SECTION 74
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TUNING THE CODE
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tion can still be worthwhile Distance in the plane is determined by the formula sqrt(dxadx+dyady) so to decide which of two points is further away would normally involve calculating two square roots But the same decision can be made by comparing the squares of the distances;
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gives the same result as comparing the square roots of the expressions Another instance occurs in textual pattern matchers such as our spam filter or grep If the pattern begins with a literal character, a quick search is made down the input text for that character; if no match is found, the more expensive search machinery is not invoked at all
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Unroll or eliminate loops There is a certain overhead in setting up and running a loop If the body of the loop isn't too long and doesn't iterate too many times it can be more efficient to write out each iteration in sequence Thus, for example
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a [ i l = b[i]
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This eliminates loop overhead, particularly branching, which can slow niodeni processors by interrupting the flow of execution If the loop is longer, the same kind of transformation can be used to amortize the overhead over fewer iterations: f o r (i = 0 ; i < 3an; i++)
a[i] = b[i]
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a [ i + O l = b[i+O] a[i+ll = b[i+l] a[i+21 = b[i+2]
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Note that this works only if the length is a multiple of the step size; otherwise additional code is needed to fix up the ends, which is a place for mistakes to creep in and for some of the efficiency to be lost again
Cachefrequently-used values Cached values don't have to be recomputed Caching takes advantage of loccrlity, the tendency for programs (and people) to re-use recently accessed or nearby items in preference to older or distant data Computing hardware makes extensive use of caches; indeed adding cache memory to a computer can make