algorithm-networksort-chooser - Helper utility for Algorithm::Networksort
The algorithm-networksort-chooser script helps you find the best sorting network for your particular use-case.
$ algorithm-networksort-chooser 9 ## find best sorting network for array size 9
$ algorithm-networksort-chooser 9 --all ## show all candiate networks
$ algorithm-networksort-chooser 9 --algorithms=batcher,bitonic ## only consider batcher and bitonic algos
$ algorithm-networksort-chooser 9 --opt=comparators ## optimise for comparators (default)
$ algorithm-networksort-chooser 9 --opt=stages ## optimise for stages
$ algorithm-networksort-chooser 9 --opt=swaps ## optimise for average swaps
$ algorithm-networksort-chooser 9 --median ## best median network
$ algorithm-networksort-chooser 9 --selection=4 ## also best median network
$ algorithm-networksort-chooser 9 --selection=0,1,2 ## top-3 elements selection net
$ algorithm-networksort-chooser 9 --validate ## run 0-1 validation test
$ algorithm-networksort-chooser 9 --show ## show network as ASCII diagram
$ algorithm-networksort-chooser 9 --raw ## show network as raw comparatorsThis module uses Algorithm::Networksort to experiment with sorting networks.
Introduction To Sorting Networks
By default this script examines the output of all implemented algorithms and the currently best known special-cases, and chooses the one that best meets your specified criteria.
This module allows you to trim sorting networks into median or selection networks.
You can then choose the optimal net based on comparators (total number of operations) or on stages (number of operations considering parallelism).
Normally the output is something like this:
$ algorithm-networksort-chooser --median 22
Network size: 22
Network type: Median network
Optimisation criteria: stages
Optimal network:
Algorithm "best":
Comparators: 86
Stages: 12For the description of the various algorithms and best-known special cases, see Algorithm::Networksort's documentation and source code.
In order to use this output in another program, there is a --raw switch. Its output is evalable perl and is valid JSON:
$ algorithm-networksort-chooser --median 7 --raw
[[0,4],[1,5],[2,6],[0,2],[1,3],[4,6],[2,4],[3,5],[0,1],[2,3],[4,5],[1,4],[3,6],[3,4]]Algorithm::Networksort's ASCII output can be seen with --show:
$ algorithm-networksort-chooser --median 7 --show
Network size: 7
Network type: Median network
Optimisation criteria: comparators
Optimal network:
Algorithm "batcher":
Comparators: 14
Stages: 6
o--^--------^-----^-----------------o
| | |
o--|--^-----|--^--v--------^--------o
| | | | |
o--|--|--^--v--|--^-----^--|--------o
| | | | | | |
o--|--|--|-----v--|--^--v--|--^--^--o
| | | | | | | |
o--v--|--|--^-----v--|--^--v--|--v--o
| | | | | |
o-----v--|--|--------v--v-----|-----o
| | |
o--------v--v-----------------v-----oThe --all switch shows all networks that were considered.
Sometimes which algorithm or which best special-case network is surprising. For instance, selecting the top-3 elements in a size-9 array is best done by adapting Hibbard's algorithm, even though there is a special best (by comparators) network for size 9:
$ algorithm-networksort-chooser 9 --selection=0,1,2 --all
Network size: 9
Network type: Selection network: 0,1,2
Optimisation criteria: comparators
Optimal network:
Algorithm "hibbard":
Comparators: 18
Stages: 7
Additional candidate networks:
Algorithm "batcher":
Comparators: 20
Stages: 8
Algorithm "bosenelson":
Comparators: 22
Stages: 10
Algorithm "best":
Comparators: 23
Stages: 9
Algorithm "bitonic":
Comparators: 24
Stages: 8
Algorithm "bubble":
Comparators: 36
Stages: 15Algorithm::Networksort::Validate::XS
Introduction To Sorting Networks
Algorithm-Networksort-Chooser github repo
John Gamble's Algorithm-Networksort github repo
Doug Hoyte, <[email protected]>
Copyright 2013-2016 Doug Hoyte.
This module is licensed under the same terms as perl itself.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent