Memory sub-system resource management Method for big-data workloads

摘要

The present invention relates to an optimization method for preventing a competition situation of a memory subsystem resource shared and used in an environment where latency-critical big-data workload and batch-processing big-data workload are performed together. A memory sub-system resource management method comprises: (a) determining a cache size capable of maintaining a service level objective (SLO) required by latency-critical big-data workload, isolating a cache memory in a determined size, assigning the cache memory to the latency-critical big-data workload, and assigning the remaining cache memory to batch-processing big-data workload; and (b) determining a memory bandwidth capable of the SLO required by the latency-critical big-data, isolating the memory bandwidth in a determined size, assigning the memory bandwidth to the latency-critical big-data workload, and assigning the remaining memory bandwidth to the batch-processing big-data workload. The SLO as a performance target of the latency-critical big-data workload is ensured by reducing the competition situation in a shared memory resource, and the server utilization rate as a performance target of the batch-processing big-data workload is increased.