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TL;DR: Reference Counting is a frequent topic of discussion in the D community. The motivations aren't always clear. In the context of machine learning, reference counting is valuable due to the low memory capacity of graphics cards, and the need to free unused memory as quickly as possible.
Every year, especially at DConf, there's a lot of talk about various approaches and difficulties regarding Reference Counting. Without context, there's plenty of pros and cons associated with it (https://en.wikipedia.org/wiki/Garbage_collection_%28computer_science%29#Reference_counting), however, the reasons to go with reference counting over tracing or escape analysis weren't very clear to me.
However, in the course of my work, I came across a clear use-case that others might find illuminating. The context is machine learning, where large numbers of partial derivatives of an error function, in the context of hundreds of thousands, if not millions, of parameters. Due to the high number of matrix operations involved, this work is primarily vectorized and executed on graphics cards.
Towards this end, I came across this snippet in a paper on a well known machine learning library called PyTorch (https://pytorch.org/).
https://openreview.net/pdf?id=BJJsrmfCZ
>Memory management The main use case for PyTorch is training machine learning models on
GPU. As one of the biggest limitations of GPUs is low memory capacity, PyTorch takes great care to
make sure that all intermediate values are freed as soon as they become unneeded. Indeed, Python is
well-suited for this purpose, because it is reference counted by default (using a garbage collector only
to break cycles).
PyTorch’s Variable and Function must be designed to work well in a reference counted regime.
For example, a Function records pointers to the Function which consumes its result, so that a
Function subgraph is freed when its retaining output Variable becomes dead. This is opposite of the
conventional ownership for closures, where a closure retains the closures it invokes (a pointer to the
Function which produces its result.)
I hope this provides some clarity and insight to others.