Normalize parent array type (#15)

* Reduce required specializations

* Fix `parent` test

* Bump v0.3.3

* Unpack memory when possible

* Bump v0.4.0

* Update Readme

Author: lkdvos

Project.toml

@@ -1,7 +1,7 @@
 name = "StridedViews"
 uuid = "4db3bf67-4bd7-4b4e-b153-31dc3fb37143"
 authors = ["Lukas Devos <lukas.devos@ugent.be>", "Jutho Haegeman <jutho.haegeman@ugent.be>"]
-version = "0.3.2"
+version = "0.4.0"
 
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"

README.md

@@ -50,3 +50,10 @@ subsequent dimensions `i` and `i+1` can only be joined if `stride(A,i+1) ==
 size(A,i)*stride(A,i)`. Instead of overloading `reshape`, Strided.jl provides a separate
 function `sreshape` which returns a `StridedView` over the same parent data, or throws a
 runtime error if this is impossible.
+
+### News
+
+Since StridedViews v0.4.0, the `StridedView` type attempts to generate less specializations
+by normalizing the parent array type. In particular, for `DenseArray` parents we attempt to
+reshape the parent array to a vector, and for `Memory`-based arrays (Julia v1.11+) we unpack
+the `Memory` object directly. This should improve compile times.

src/auxiliary.jl

@@ -45,6 +45,13 @@ function _normalizestrides(size::Dims{N}, strides::Dims{N}) where {N}
     return strides
 end
 
+# 'Normalize' the layout of a DenseArray, in order to reduce the number of required
+# specializations in functions.
+@static if isdefined(Core, :Memory)
+    @inline _normalizeparent(A::Array) = A.ref.mem
+end
+@inline _normalizeparent(A::DenseArray) = reshape(A, length(A))
+
 # Auxiliary methods for `sview`
 #------------------------------
 # Compute the new dimensions of a strided view given the original size and the view slicing

src/stridedview.jl

@@ -34,13 +34,15 @@ end
 
 # Constructors
 #--------------
-function StridedView(parent::A,
+function StridedView(parent::DenseArray,
                      size::NTuple{N,Int}=size(parent),
                      strides::NTuple{N,Int}=strides(parent),
                      offset::Int=0,
-                     op::F=identity) where {A<:DenseArray,N,F}
+                     op::F=identity) where {N,F}
     T = Base.promote_op(op, eltype(parent))
-    return StridedView{T,N,A,F}(parent, size, _normalizestrides(size, strides), offset, op)
+    parent′ = _normalizeparent(parent)
+    strides′ = _normalizestrides(size, strides)
+    return StridedView{T,N,typeof(parent′),F}(parent′, size, strides′, offset, op)
 end
 
 StridedView(a::StridedView) = a

test/runtests.jl

@@ -13,7 +13,7 @@ Random.seed!(1234)
         @test isstrided(A1)
         @test isstrided(B1)
         @test C1 === B1
-        @test parent(B1) === A1
+        @test parent(B1) == reshape(A1, :)
         @test Base.elsize(B1) == Base.elsize(A1)
         for op1 in (identity, conj, transpose, adjoint)
             if op1 == transpose || op1 == adjoint