diff --git a/lib/JLArrays/src/JLArrays.jl b/lib/JLArrays/src/JLArrays.jl
index bf671ff2..4d2dad41 100644
--- a/lib/JLArrays/src/JLArrays.jl
+++ b/lib/JLArrays/src/JLArrays.jl
@@ -134,7 +134,7 @@ mutable struct JLSparseVector{Tv, Ti} <: GPUArrays.AbstractGPUSparseVector{Tv, T
         new{Tv, Ti}(iPtr, nzVal, len, length(nzVal))
     end
 end
-SparseArrays.nnz(x::JLSparseVector)          = x.nnz 
+SparseArrays.nnz(x::JLSparseVector)          = x.nnz
 SparseArrays.nonzeroinds(x::JLSparseVector)  = x.iPtr
 SparseArrays.nonzeros(x::JLSparseVector)     = x.nzVal
 
@@ -181,7 +181,7 @@ end
 function JLSparseMatrixCSR(rowPtr::JLArray{Ti, 1}, colVal::JLArray{Ti, 1}, nzVal::JLArray{Tv, 1}, dims::NTuple{2,<:Integer}) where {Tv, Ti <: Integer}
     return JLSparseMatrixCSR{Tv, Ti}(rowPtr, colVal, nzVal, dims)
 end
-function SparseArrays.SparseMatrixCSC(x::JLSparseMatrixCSR) 
+function SparseArrays.SparseMatrixCSC(x::JLSparseMatrixCSR)
     x_transpose = SparseMatrixCSC(size(x, 2), size(x, 1), Array(x.rowPtr), Array(x.colVal), Array(x.nzVal))
     return SparseMatrixCSC(transpose(x_transpose))
 end
@@ -230,12 +230,12 @@ GPUArrays.sparse_array_type(::Type{<:JLSparseMatrixCSR}) = JLSparseMatrixCSR
 GPUArrays.sparse_array_type(sa::JLSparseVector) = JLSparseVector
 GPUArrays.sparse_array_type(::Type{<:JLSparseVector}) = JLSparseVector
 
-GPUArrays.dense_array_type(sa::JLSparseVector) = JLArray 
-GPUArrays.dense_array_type(::Type{<:JLSparseVector}) = JLArray 
-GPUArrays.dense_array_type(sa::JLSparseMatrixCSC) = JLArray 
-GPUArrays.dense_array_type(::Type{<:JLSparseMatrixCSC}) = JLArray 
-GPUArrays.dense_array_type(sa::JLSparseMatrixCSR) = JLArray 
-GPUArrays.dense_array_type(::Type{<:JLSparseMatrixCSR}) = JLArray 
+GPUArrays.dense_array_type(sa::JLSparseVector) = JLArray
+GPUArrays.dense_array_type(::Type{<:JLSparseVector}) = JLArray
+GPUArrays.dense_array_type(sa::JLSparseMatrixCSC) = JLArray
+GPUArrays.dense_array_type(::Type{<:JLSparseMatrixCSC}) = JLArray
+GPUArrays.dense_array_type(sa::JLSparseMatrixCSR) = JLArray
+GPUArrays.dense_array_type(::Type{<:JLSparseMatrixCSR}) = JLArray
 
 GPUArrays.csc_type(sa::JLSparseMatrixCSR) = JLSparseMatrixCSC
 GPUArrays.csr_type(sa::JLSparseMatrixCSC) = JLSparseMatrixCSR
@@ -246,14 +246,14 @@ Base.similar(Mat::JLSparseMatrixCSR, T::Type) = JLSparseMatrixCSR(copy(Mat.rowPt
 Base.similar(Mat::JLSparseMatrixCSC, T::Type, N::Int, M::Int) =  JLSparseMatrixCSC(JLVector([zero(Int32)]), JLVector{Int32}(undef, 0), JLVector{T}(undef, 0), (N, M))
 Base.similar(Mat::JLSparseMatrixCSR, T::Type, N::Int, M::Int) =  JLSparseMatrixCSR(JLVector([zero(Int32)]), JLVector{Int32}(undef, 0), JLVector{T}(undef, 0), (N, M))
 
-Base.similar(Mat::JLSparseMatrixCSC{Tv, Ti}, N::Int, M::Int) where {Tv, Ti} = similar(Mat, Tv, N, M) 
-Base.similar(Mat::JLSparseMatrixCSR{Tv, Ti}, N::Int, M::Int) where {Tv, Ti} = similar(Mat, Tv, N, M) 
+Base.similar(Mat::JLSparseMatrixCSC{Tv, Ti}, N::Int, M::Int) where {Tv, Ti} = similar(Mat, Tv, N, M)
+Base.similar(Mat::JLSparseMatrixCSR{Tv, Ti}, N::Int, M::Int) where {Tv, Ti} = similar(Mat, Tv, N, M)
 
-Base.similar(Mat::JLSparseMatrixCSC, T::Type, dims::Tuple{Int, Int}) = similar(Mat, T, dims...) 
-Base.similar(Mat::JLSparseMatrixCSR, T::Type, dims::Tuple{Int, Int}) = similar(Mat, T, dims...) 
+Base.similar(Mat::JLSparseMatrixCSC, T::Type, dims::Tuple{Int, Int}) = similar(Mat, T, dims...)
+Base.similar(Mat::JLSparseMatrixCSR, T::Type, dims::Tuple{Int, Int}) = similar(Mat, T, dims...)
 
-Base.similar(Mat::JLSparseMatrixCSC, dims::Tuple{Int, Int}) = similar(Mat, dims...) 
-Base.similar(Mat::JLSparseMatrixCSR, dims::Tuple{Int, Int}) = similar(Mat, dims...) 
+Base.similar(Mat::JLSparseMatrixCSC, dims::Tuple{Int, Int}) = similar(Mat, dims...)
+Base.similar(Mat::JLSparseMatrixCSR, dims::Tuple{Int, Int}) = similar(Mat, dims...)
 
 JLArray(x::JLSparseVector)    = JLArray(collect(SparseVector(x)))
 JLArray(x::JLSparseMatrixCSC) = JLArray(collect(SparseMatrixCSC(x)))
@@ -323,9 +323,11 @@ StridedJLVector{T} = StridedJLArray{T,1}
 StridedJLMatrix{T} = StridedJLArray{T,2}
 StridedJLVecOrMat{T} = Union{StridedJLVector{T}, StridedJLMatrix{T}}
 
-Base.pointer(x::StridedJLArray{T}) where {T} = Base.unsafe_convert(Ptr{T}, x)
-@inline function Base.pointer(x::StridedJLArray{T}, i::Integer) where T
-    Base.unsafe_convert(Ptr{T}, x) + Base._memory_offset(x, i)
+# Pointer access is only available for callers that explicitly want a pointer.
+Base.pointer(x::JLArray{T}) where {T} =
+    convert(Ptr{T}, pointer(x.data[])) + x.offset
+@inline function Base.pointer(x::JLArray{T}, i::Integer) where T
+    pointer(x) + (i - 1) * sizeof(T)
 end
 
 # anything that's (secretly) backed by a JLArray
@@ -342,8 +344,10 @@ Base.elsize(::Type{<:JLArray{T}}) where {T} = sizeof(T)
 Base.size(x::JLArray) = x.dims
 Base.sizeof(x::JLArray) = Base.elsize(x) * length(x)
 
-Base.unsafe_convert(::Type{Ptr{T}}, x::JLArray{T}) where {T} =
-    convert(Ptr{T}, pointer(x.data[])) + x.offset
+# Reject implicit conversions to a pointer, i.e., by passing to a CPU ccall.
+function Base.unsafe_convert(::Type{Ptr{T}}, x::JLArray{T}) where {T}
+    error("Illegal conversion of a JLArray to a Ptr")
+end
 
 
 ## interop with Julia arrays
@@ -378,7 +382,7 @@ function JLSparseMatrixCSC(xs::SparseMatrixCSC{Tv, Ti}) where {Ti, Tv}
     copyto!(nzVal,  convert(Vector{Tv}, xs.nzval))
     return JLSparseMatrixCSC{Tv, Ti}(colPtr, rowVal, nzVal, (xs.m, xs.n))
 end
-JLSparseMatrixCSC(xs::SparseVector) = JLSparseMatrixCSC(SparseMatrixCSC(xs)) 
+JLSparseMatrixCSC(xs::SparseVector) = JLSparseMatrixCSC(SparseMatrixCSC(xs))
 Base.length(x::JLSparseMatrixCSC) = prod(x.dims)
 Base.size(x::JLSparseMatrixCSC) = x.dims