Mir vs. Numpy: Reworked!

[9il]

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.