Doug Hoyte > Algorithm-Networksort-Chooser-0.100 > algorithm-networksort-chooser

# NAME

algorithm-networksort-chooser - Helper utility for Algorithm::Networksort

# SYNOPSIS

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 --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 comparators```

# DESCRIPTION

This 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 trim the sorting networks into median or selection networks.

You can then choose to 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: 12```

For 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 `eval`able 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-----o```

The `--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

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: 15```

# FUTURE IDEAS

Also optimise by average swaps

Algorithm::Networksort::Validate::XS

Introduction To Sorting Networks

Algorithm-Networksort-Chooser github repo

John Gamble's Algorithm-Networksort github repo

# AUTHOR

Doug Hoyte, `<doug@hcsw.org>`