On Monday, 7 December 2020 at 12:28:39 UTC, data pulverizer wrote:
On Monday, 7 December 2020 at 02:14:41 UTC, 9il wrote:
I don't know. Tensors aren't so complex. The complex part is a
design that allows Mir to construct and iterate various kinds
of lazy tensors of any complexity and have quite a universal
API, and all of these are boosted by the fact that the
user-provided kernel(lambda) function is optimized by the
compiler without the overhead.
I agree that a basic tensor is not hard to implement, but the
specific design to choose is not always obvious. Your
benchmarks shows that design choices have a large impact on
performance, and performance is certainly a very important
consideration in tensor design.
For example I had no idea that your ndslice variant was using
more than one array internally to achieve its performance - it
wasn't obvious to me.
ndslice tensor type uses exactly one iterator. However, the
iterator is generic and lazy iterators may contain any number of
other iterators and pointers.
