parallel-computing

julia> typeof(E)
Symbolics.Arr{Num, 2}

julia> typeof(d)
Vector{Num} (alias for Array{Num, 1})

julia> ex2 = d' * inv(E) * d
ERROR: MethodError: *(::Adjoint{Num, Vector{Num}}, ::Symbolics.Arr{Num, 2}) is ambiguous. Candidates:
  *(A::AbstractMatrix, B::Symbolics.Arr{<:Any, 2}) in Symbolics at /home/mbesancon/.julia/packages/Symbolics/DCeQ3/src/wrapper-types.jl:128
  *(x::Adjoint{T, <

The standard accelerate test suite, used by all the backends, can be quite slow. Several of the tests are significantly slower than the others, for example segmented folds and scans, which I believe is because the reference implementations are very inefficient. Writing some more efficient reference implementations (e.g. using Data.Vector.Unboxed) should help speed things up.

When computing the isosurface, when 4 simplex edges crosses the isosurface, we add 2 triangles to the isosurface triangulation.

Right now we add these arbitrarily (in these 3 lines) but we should add them so that the curvature is minimized.

The current state o

• core
• mpi