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If nothing else, the term "tensor" is shorter than "vectors and matrices," and then has the added benefit of representing n-dimensional arrays.
by ralusek 3y ago
If nothing else, the term "tensor" is shorter than "vectors and matrices," and then has the added benefit of representing n-dimensional arrays.
- layer8 3y agoHow is that an added benefit if the hardware doesn’t actually support n-dimensional arrays (other the n = 1 and 2)? And, strictly speaking, a vector can be considered a 1xn (or nx1) matrix, so Matrix Processing Unit would have been fine.
- thatguysaguy 3y agoAt the end of the day all the arrays are 1 dimensional and thinking of them as 2 dimensional is just an indexing convenience. A matrix multiply is a bunch of vector dot products in a row. Higher tensor contractions can be built out of lower-dimensional ones, so I don't think it's really fair to say the hardware doesn't support it.
- whimsicalism 3y agoit’s an abstraction, just like 2d arrays
- layer8 3y agoI’d say it’s more like calling an ALU that can perform unary and binary operations (so 1 or 2 inputs) an “array processing unit” because it’s like it can process 1- and 2-element arrays. ;)
- whimsicalism 3y agowhat? the ml framework can support n-dimensional arrays. that’s what i mean by an abstraction