mctensor
MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point
Yu, Tao, Guo, Wentao, Li, Jianan Canal, Yuan, Tiancheng, De Sa, Christopher
In this paper, we introduce MCTensor, a library based on PyTorch for providing general-purpose and high-precision arithmetic for DL training. MCTensor is used in the same way as PyTorch Tensor: we implement multiple basic, matrix-level computation operators and NN modules for MCTensor with identical PyTorch interface. Our algorithms achieve high precision computation and also benefits from heavily-optimized PyTorch floating-point arithmetic. We evaluate MCTensor arithmetic against PyTorch native arithmetic for a series of tasks, where models using MCTensor in float16 would match or outperform the PyTorch model with float32 or float64 precision.
Country:
- North America > United States > Maryland > Baltimore (0.04)
- North America > United States > California > Alameda County > Berkeley (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)