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ATLAS (Automatically Tuned Linear Algebra Software) project is an ongoing research effort focusing on applying empirical techniques in order to provide portable performance.
ATLAS provides C and Fortran77 interfaces to a portably efficient BLAS implementation, as well as a few routines from LAPACK.
Whats New in 3.7.37 Development Release:
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AI::FuzzyLogic is a Perl module for Fuzzy Set Operations and Tools.

SYNOPSIS

use AI::FuzzyLogic;

$i = new AI::FuzzyLogic $unittype, @numbers; # new set with one subset
$i = new AI::FuzzyLogic age, 0, 0.1, 0.2, 0.1, 0; # same thing

$i = new AI::FuzzyLogic $subset1, $subset2, $subset3; # new set with several subsets

# another syntax for building a set with several subsets:
$i = AI::FuzzyLogic->new(
AI::FuzzyLogic->new(distance, 0.0, 0.1, 0.1, 0.5, 0.8, 0.6, 0.3, 0.0),
AI::FuzzyLogic->new(time, 0.3, 0.3, 0.1, 0.1, 0.1, 0.2, 0.3, 0.3),
AI::FuzzyLogic->new(heat, 0.0, 0.1, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2),
);

# constructors for explicit combinational behavior:
$i = new AI::FuzzyLogic::Correlator speed, 0.1, 0.3, 0.2, 0.1, 0.1;
$i = new AI::FuzzyLogic::Permutator speed, 0.1, 0.3, 0.2, 0.1, 0.1;
$i = new AI::FuzzyLogic::Discriminator speed, 0.1, 0.3, 0.2, 0.1, 0.1;
$i = new AI::FuzzyLogic::Abstractor speed, 0.1, 0.3, 0.2, 0.1, 0.1;

# change combinational behavior:
$set->as_correlator(); # operations work on matching subsets of same type
$set->as_permutator(); # operations work across all subsets of each set
$set->as_discriminator(); # operations best matching subset from right for each on left
$set->as_abstractor(); # operations return one set with one subset summerizing fit

$i->add_subsets($j); # combine subsets or other sets in

abs($i) # defuzzify to integer (centroid - curve middle, x axis)
0+$i # defuzzify to integer (mean - average curve height, y axis)

$a & $b # intersection of sets
$a | $b # union of sets
$i++ # normalize curve to 1.0
$i-- # stretch curve to edges
~$i # negate set
$i ** 0.5 # dialation
"$i" # convert subsets to ASCII graphs

$a + $b # sum sets
$a - $b # subtract sets
$a * $b # multiply sets - useful for sensitivity control
$a / $b # divide sets - useful for sensitivity control

$h->larger($a) # boolean: does $h completely encompass $a?

$a ^ $b # xor: same as ~($a | $b)
$a < $b # compare volume: is $a smaller?
$a > $b # compare volume: is $a larger?

@sets = $a->unwrap(); # get subsets as list of AI::FuzzyLogic::Subset objects
@sets = $a->query_type(type); # get subsets of type type as a list of AI::FuzzyLogic::Subset objects
$a->change_type(fromtype, to); # change type of subsets of type fromtype to to

Performs all basic operations on Fuzzy Sets. Use English-like, intentionally vague objects representing concepts with which to make inferences. The inferences might be approximate reasoning about precise knowledge, or precise reasoning about approximate knowledge. This vagueness allows the capture and application of human expert knowledge.

Overloads Perl operators to perform operations on Fuzzy Sets.