A unified schedule policy of distributed machine learning framework for CPU-GPU cluster
With the widespread using of GPU hardware facilities, more and more distributed machine learning applications have begun to use CPU-GPU hybrid cluster resources to improve the efficiency of algorithms.However, the existing distributed machine learning scheduling framework either only considers task scheduling on CPU resources or only considers task