Hello..



About the sorting algorithms..

So I invite you to read the following interesting article:

Beating Up on Qsort

https://travisdowns.github.io/blog/2019/05/22/sorting.html


And more about sorting algorithms..

I have just read the following webpage:

In-depth: Smoothsort vs. Timsort

https://www.gamasutra.com/view/news/172542/Indepth_Smoothsort_vs_Timsort.php


I think that since it is very "rare" that the Data that is given is
sorted or reversed, so then you can notice in the above webpage that
Timsort does in reality has a small improvement on the partially sorted
data, so then i will choose to use my powerful Parallel Sort Library
that is efficient, read about it below:

My Parallel Sort Library that is more efficient version 4.1 is here..

Notice also in the source code that my Mergesort uses also insertion
sort like in a Timsort manner, so it is very efficient.

You can download it from my website here:

https://sites.google.com/site/scalable68/parallel-sort-library-that-is-more-efficient


And my EasyList for Delphi and Freepascal was updated to version 1.53..

I have now documented all the methods.

You can read about and download my EasyList version 1.53 from my website
here:

https://sites.google.com/site/scalable68/easylist-for-delphi-and-freepascal

More precision about my software Libraries..

About scalable higher-order functions like Map, Reduce and Filter..

MapReduce is a pattern introduced in 2004 in the paper “MapReduce:
Simplified Data Processing on Large Clusters,” by Jeffrey Dean and
Sanjay Ghemawat
(https://research.google.com/archive/mapreduce-osdi04.pdf), so here is
my new invention in form of a Library: I will soon implement parallel
and scalable higher-order functions like Map, Reduce and Filter, so it
will be a very powerful library.

And i have already implemented a serial(i mean not parallel) Library
of higher-order functions like Map, Reduce and Filter:

You can read about it and download it from my website here:

https://sites.google.com/site/scalable68/delphi-library-that-implements-higher-order-functions-like-map-reduce-and-filter

About my Threadpool with priorities that scales very well..

And you can also use my serial Library of higher-order functions like
Map, Reduce and Filter with my following invention of my Threadpool with priorities that scales very well (that also supports a ParallelFor()
that scales very well), so read about it here:

https://sites.google.com/site/scalable68/an-efficient-threadpool-engine-with-priorities-that-scales-very-well

Also i have already invented and implemented my following powerful
parallel sort library, you can read about it and download it from my
website here:

https://sites.google.com/site/scalable68/parallel-sort-library-that-is-more-efficient

I have just tested my above parallel sort library that is more
efficient, and i have just noticed that it works well with my serial
Library of higher-order functions like Map, Reduce and Filter, i mean
you can pass it the generic TArray<pointer> by casting it.


Thank you,
Amine Moulay Ramdane.

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