The computational SSD ( CompSSD ), with high computing capabilities, can function not only as a storage device but also as a computing node. The data cache of the CompSSD device stores both the output data from host-side tasks and the input data for tasks executed on the CompSSD . However, current cache management strategies are optimized for traditional SSDs and are incompatible with the unique requirements of CompSSD . To address the issue of cache management for CompSSD , this article proposes a novel cache division scheme, to dynamically divide the cache into two parts, for separately buffering output data from host-side tasks and input data used by CompSSD -side tasks. To this end, we construct a mathematical model that periodically estimate an optimal cache division ratio, by considering the factors of the ratios of read/write data amount, the cache hits, and the overhead of data transfer between the storage device and the host. Besides, we propose a scheme of proactive data flushing to write the output data to the underlying flash arrays, without impacts on I/O responsiveness. The trace-driven experiments show that our scheme can improve the overall I/O latency by 35.4% on average, in contrast to existing cache management schemes for CompSSD devices.

High computational capabilities enable modern solid-state drives (SSDs) to be computing nodes, not just faster storage devices, and the SSD having such capability is generally called as the computational SSD (CompSSD). Then, the DRAM data cache of CompSSD should hold not only the output data of the tasks running at the host side, but also the input data of the tasks executed at the SSD side. To boost the use efficiency of the cache inside CompSSD, this paper proposes an adaptive cache division scheme, to dynamically split the cache space for separately buffering the output data running at the host and the input data running at the CompSSD. Specifically, we construct a mathematical model running at flash translation layer of CompSSD, to periodically determine the cache proportion of the workloads running at the host side and the CompSSD side, by considering the factors of the ratios of read/write data amount, the cache hits, and the overhead of data transfer between the storage device and the host. Then, both the output data and the input data can be buffered in their own private cache parts, so that the overall I/O performance can be enhanced. Trace-driven simulation experiments show that our proposal can reduce the overall I/O latency by 27.5 % on average, in contrast to existing cache management schemes.