Understanding The Effectiveness of Lossy Compression in Machine Learning Training Sets

arXiv:2403.15953v1 Announce Type: new
Abstract: Learning and Artificial Intelligence (ML/AI) techniques have become increasingly prevalent in high performance computing (HPC). However, these methods depend on vast volumes of floating point data for training and validation which need methods to share the data on a wide area network (WAN) or to transfer it from edge devices to data centers. Data compression can be a solution to these problems, but an in-depth understanding of how lossy compression affects model quality is needed. …

abstract artificial artificial intelligence arxiv become compression computing cs.ai cs.lg data floating point high performance computing however hpc intelligence machine machine learning network performance training type understanding validation vast