def _specialize_clusters(cls, clusters, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
sregistry = kwargs['sregistry']
# Optimize MultiSubDomains
clusters = optimize_msds(clusters)
# Toposort+Fusion (the former to expose more fusion opportunities)
clusters = fuse(clusters, toposort=True, options=options)
# Fission to increase parallelism
clusters = fission(clusters)
# Hoist and optimize Dimension-invariant sub-expressions
clusters = cire(clusters, 'invariants', sregistry, options, platform)
clusters = Lift().process(clusters)
# Reduce flops
clusters = extract_increments(clusters, sregistry)
clusters = cire(clusters, 'sops', sregistry, options, platform)
clusters = factorize(clusters)
clusters = optimize_pows(clusters)
# The previous passes may have created fusion opportunities
clusters = fuse(clusters)
# Reduce flops
clusters = cse(clusters, sregistry)
return clusters
def _specialize_clusters(cls, clusters, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
sregistry = kwargs['sregistry']
# Optimize MultiSubDomains
clusters = optimize_msds(clusters)
# Toposort+Fusion (the former to expose more fusion opportunities)
clusters = fuse(clusters, toposort=True)
# Hoist and optimize Dimension-invariant sub-expressions
clusters = cire(clusters, 'invariants', sregistry, options, platform)
clusters = Lift().process(clusters)
# Reduce flops (potential arithmetic alterations)
clusters = extract_increments(clusters, sregistry)
clusters = cire(clusters, 'sops', sregistry, options, platform)
clusters = factorize(clusters)
clusters = optimize_pows(clusters)
# The previous passes may have created fusion opportunities
clusters = fuse(clusters)
# Reduce flops (no arithmetic alterations)
clusters = cse(clusters, sregistry)
# Blocking to improve data locality
clusters = blocking(clusters, options)
return clusters