Wear-Leveling Aware Data Allocation for Chip Multiprocessors with Non-Volatile Memory

Non-Volatile Memory (NVM) has many advantages that provide new choice for embedded storage systems. However, the NVM has a limited number of writes and the overhead of write operation is greater than read operation. In order to overcome these drawbacks, it is necessary to reduce the read and write overhead of the NVM and make the NVM wear-leveling. In this paper, we use Iterational Optimal Data Allocation (IODA) algorithm to achieve the global minimum read and write overhead data allocation, and then, we propose Greedy and Global Balance Optimization Allocation (GBOA) algorithm to allocate NVM data into blocks to achieve NVM wear-leveling at the software-level. Experimental results show that the lifetime of NVM based on the Greedy algorithm is improved by 37.96% and the GBOA is improved by 49.52% compared to the Random algorithm on average, while we can obtain the global minimum read and write overhead.

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