Memory Safe Computations with XLA Compiler. (arXiv:2206.14148v1 [cs.LG])

Software packages like TensorFlow and PyTorch are designed to support linear
algebra operations, and their speed and usability determine their success.
However, by prioritising speed, they often neglect memory requirements. As a
consequence, the implementations of memory-intensive algorithms that are
convenient in terms of software design can often not be run for large problems
due to memory overflows. Memory-efficient solutions require complex programming
approaches with significant logic outside the computational framework. This
impairs the adoption and use of such algorithms. …

arxiv lg memory