Abstract
Near-data processing (NDP) architecture is promised to break the bottleneck of data movement in many scenarios (e.g., databases and recommendation systems), which limits the efficiency of data processing. Different from traditional SSD, NDP-based SSD not only needs to handle normal I/Os (e.g., read and write), but also needs to handle NDP requests that contain data processing operations. NDP and normal I/O requests share some function units of NDP-based SSD, such as flash chips and embedded processors. However, existing works ignore the resource competition between normal I/Os and NDP requests, which drastically degrades the performance. In this article, we propose a novel scheduling technique called Horae, which can efficiently schedule hybrid NDP-normal I/O requests in NDP-based SSD to improve performance. Horae exploits the critical paths on critical resources to maximize the parallelism of multiple stages of requests. The experimental results on typical workloads show that Horae can significantly improve the performance of hybrid NDP-normal I/O requests over the state-of-the-art scheduling algorithms of NDP-based SSDs.
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More From: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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