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Hello...


As you have noticed i am a white arab, and i am a more serious computer
programmer and i am also an "inventor" of many scalable algorithms and 
there implementations, here is my new invention:

I have just "invented" a "highly" scalable Parallel Sort library
for shared memory architectures that supports a highly scalable 
Mergesort and a highly scalable Quicksort and a highly scalable 
Heapsort. I think that this new invention of mine is the "best" one in 
shared memory architectures because it also uses my other inventions of 
a fully scalable FIFO queue and a fully scalable Threadpool. So i think 
i will sell it to Google or to Microsoft or to Embarcadero or such big 
software companies.

Also i have have just invented the following Parallel Sort Library that
supports a new and more efficient Parallel merge algorithms that 
improves the worst-case performance:

My algorithm of finding the median of Parallel merge of my  Parallel 
Sort Library that you will find here in my website:

https://sites.google.com/site/scalable68/parallel-sort-library

Is O(log(min(|A|,|B|))), where |A| is the size of A, since the binary 
search is performed within the smaller array and is O(lgN). But the new 
algorithm of finding the median of parallel merge of my Parallel Sort 
Library is O(log(|A|+|B|)), which is slightly worse. With further 
optimizations the order was reduced to O(log(2*min(|A|,|B|))), which is 
better, but is 2X more work, since both arrays may have to be searched. 
All algorithms are logarithmic. Two binary searches were necessary to 
find an even split that produced two equal or nearly equal halves. 
Luckily, this part of the merge algorithm is not performance critical. 
So, more effort can be spent looking for a better split. This new 
algorithm in the parallel merge balances the recursive binary tree of 
the divide-and-conquer and improve the worst-case performance of 
parallel merge sort.


So stay tuned !


Thank you,
Amine Moulay Ramdane.

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Read again.. Horizon68 <horizon@horizon.com> - 2019-03-25 17:01 -0700

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