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Driven by the insatiable needs to process ever larger amount of data withmore complex models, modern computer processors and accelerators are beginningto offer half precision floating point arithmetic support, and extremelyoptimized special units such as NVIDIA TensorCore on GPU and Google TensorProcessing Unit (TPU) that does half precision matrix-matrix multiplicationexceptionally efficiently. In this paper we present a large scale mixedprecision linear least square solver that achieves high accuracy using the lowprecision TensorCore GPU. The mixed precision system consists of bothinnovative algorithms and implementations, and is shown to be up to 14x fasterthan single precision cuSOLVER at QR matrix factorization at large scale withslightly lower accuracy, and up to 10x faster than double precision direct QRleast square solver with comparable accuracy.

High Accuracy Low Precision QR Factorization and Least Square Solver on GPU with TensorCore