RadarSSD: A Computational Storage for Radar Signal Processing

Radar signals contain a multitude of small data items with multidimensional characteristics and various types of errors. It is challenging to store and recognize radar signals in real-time. Traditional computer architectures require data to be moved from storage to the host for processing, resulting in a "storage wall" problem. This problem is caused by low storage bandwidth, long I/O stacks, and excessive data transfers, which significantly reduce the efficiency of radar signal recognition. In this paper, we propose RadarSSD address these challenges by utilizing near-data processing (NDP) architecture to recognize radar signals within the solid-state drive (SSD), through which the high overhead of data movements can be avoided. To support efficient data I/O operations, we design a stripe-like data layout for storing radar signals taking advantage of their time sequential feature. We present a task slicing mechanism to reduce I/O blocking from in-storage data processing, and a dedicated interface for providing highly-efficient direct SSD access. We implement RadarSSD in a real computational SSD platform. Extensive experimental results show that RadarSSD can reduce power consumption while improving I/O and recognize performance, with a maximum improvement of 12.4x, 11.5x, and 4.1x recognize speed compared to the systems that manage radar signals using MySQL, MongoDB, and Ext4.