Abstract: An adaptive, large graph-oriented unified memory management method is proposed; according to the order of priorities of different types of graph data structure in a graph computing application, whether the current GPU memory is full is sequentially determined by means of GPU memory checking; whether the size of current graph data exceeds the available memory capacity of the GPU is determined by means of data overflow checking; and then a unified memory management policy is configured; the method uses different graph algorithms based on the characteristics of graph data structure and the size of the available GPU memory; the method can significantly improve the performance of processing large graphs, which exceed the video memory capacity under a unified memory architecture, including improving GPU bandwidth utilization, reducing the number of page faults and the overhead of processing page faults, and speeding up the execution of graph computing programs.

Abstract: An adaptive, large graph-oriented unified memory management method is proposed; according to the order of priorities of different types of graph data structure in a graph computing application, whether the current GPU memory is full is sequentially determined by means of GPU memory checking; whether the size of current graph data exceeds the available memory capacity of the GPU is determined by means of data overflow checking; and then a unified memory management policy is configured; the method uses different graph algorithms based on the characteristics of graph data structure and the size of the available GPU memory; the method can significantly improve the performance of processing large graphs, which exceed the video memory capacity under a unified memory architecture, including improving GPU bandwidth utilization, reducing the number of page faults and the overhead of processing page faults, and speeding up the execution of graph computing programs.

Abstract: This application is related to a data recovery system. The data recovery system includes processing circuitry which receives a restore request. The restore request includes a restore target time. When backup data corresponding to the restore target time is determined to be available, the processing circuitry creates a temporary database service instance and determines information of the temporary database service instance. The processing circuitry further obtains the backup data corresponding to the restore target time and writes the backup data into the temporary database service instance according to the information of the temporary database service instance. The processing circuitry executes a formal restoration operation on the temporary database service instance, in which the backup data is written, according to a received processing request.

Abstract: This application is related to a data recovery system. The data recovery system includes processing circuitry which receives a restore request. The restore request includes a restore target time. When backup data corresponding to the restore target time is determined to be available, the processing circuitry creates a temporary database service instance and determines information of the temporary database service instance. The processing circuitry further obtains the backup data corresponding to the restore target time and writes the backup data into the temporary database service instance according to the information of the temporary database service instance. The processing circuitry executes a formal restoration operation on the temporary database service instance, in which the backup data is written, according to a received processing request.