yes. However the delegation only happens if you use the numpy.linalg module, or if numpy has chosen internally to call the numpy.linalg module (i.e. logic in nu

yes. However the delegation only happens if you use the numpy.linalg module, or if numpy has chosen internally to call the numpy.linalg module (i.e. logic in numpy.dot will call out for large ndarrays) Our vectorizing JIT can use SIMD semantics on all numpy looping calls. For instance, non-matrix multiply A*B or for ndarray + scalar calls While many numpy users are in the habit of manipulating large square matrices, there is a significant number of users who use small arrays, or process RGB pixels