Fri, 24 Mar 2017 20:51:20 +0000 (UTC)

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How to Optimize a Black Box seimarao@gmail.com (Seima Rao) (2017-03-24) |

Re: How to Optimize a Black Box 336-986-7787@kylheku.com (Kaz Kylheku) (2017-03-24) |

Re: How to Optimize a Black Box gneuner2@comcast.net (George Neuner) (2017-03-24) |

From: | Kaz Kylheku <336-986-7787@kylheku.com> |

Newsgroups: | comp.compilers |

Date: | Fri, 24 Mar 2017 20:51:20 +0000 (UTC) |

Organization: | Aioe.org NNTP Server |

References: | 17-03-010 |

Injection-Info: | miucha.iecc.com; posting-host="news.iecc.com:2001:470:1f07:1126:0:676f:7373:6970"; logging-data="39077"; mail-complaints-to="abuse@iecc.com" |

Keywords: | code, optimize |

Posted-Date: | 27 Mar 2017 22:36:58 EDT |

On 2017-03-24, Seima Rao <seimarao@gmail.com> wrote:

*> My question is how do we start at all in optimizing a black box ?*

If the black box behaves as a function (a pure mapping from some inputs

to some outputs) and that function appears to be expensive, one way to

begin is to look at caching: don't call the black box more than once on

the same combination of inputs. That is, obtain the benefits of the

black box being called M times, with N < M actual calls to the

blackbox, and M - N being canned answers from the cache.

If you can determine some properties of the blackbox without actually

cracking it open, you can exploit them. It could be that, say, outside

of some range of the parameter space, the function has some trivial

result that can be short-circuited; yet the blackbox wastes cycles on

it. A wrapper around it could take a shortcut, bypassing the blackbox.

Like say we have a black-box which calculates the area under the normal

distribution density function, between zero and some x. Suppose the

black box is badly implemented and does lots of expensive calculations

for large magnitudes of x, where the answer just comes out to be the

obvious 0.5 or nearly so. (The "long tail" that outside of x contributes

next to nothing to the area).

We can just put in some logic around it like

(fabs(x)) >= THRESHOLD) ? 0.5 : expensive_blackbox(x);.

In this same vein, we could use a black box side-by-side with a crude

approximation of the black-box. Say we have a black-box which gives

an academically answer for every domain value of some function.

But suppose that in our engineering or scientific application,

most of the time, a "rule of thumb" approximation is completely

satisfactory. We can evaluate the parameters to determine whether the

simple, cheap approximation applies, or whether the blackbox needs

to be invoked because the conditions are such that its superior

model is critically relevant.

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