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| From: | Kaz Kylheku <157-073-9834@kylheku.com> |
| Newsgroups: | comp.compilers |
| Date: | Tue, 20 Mar 2018 16:16:02 +0000 (UTC) |
| Organization: | Aioe.org NNTP Server |
| References: | <6effed5e-6c90-f5f4-0c80-a03c61fd2127@gkc.org.uk> 18-03-042 18-03-047 18-03-075 18-03-077 |
| Injection-Info: | gal.iecc.com; posting-host="news.iecc.com:2001:470:1f07:1126:0:676f:7373:6970"; logging-data="25981"; mail-complaints-to="abuse@iecc.com" |
| Keywords: | design, performance |
| Posted-Date: | 20 Mar 2018 12:36:58 EDT |
On 2018-03-19, Gene Wirchenko <genew@telus.net> wrote:
> On Mon, 19 Mar 2018 11:04:20 +0000, Martin Ward <martin@gkc.org.uk>
> wrote:
>
> [snip]
>
>>Faster machines and larger memories mean that it becomes more
>>important to use the best algorithms.
>
> How does that follow?
>
> One could argue exactly the opposite as there are resources to
> waste.
Clever algorithms had to be used when machines were slow even on small
data and the data and code had to fit into small memories.
Clever algorithms have to be used when data sets are large.
In between there is a large territory where the machines are powerful,
but the problems (or sub-problems) being solved are reasonably small.
Here we use interpreted languages instead of compiled, linked lists
instead of more specific data structures, hashes instead of vectors and
N-dimensional data even when it isn't sparse and so on.
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