CSR: Small: Cache Design for Solid-State Drives and Its Application in Data-intensive Applications

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Solid-State Drives (SSDs) are capable of providing much higher data access bandwidth than the hard disk drives (HDDs). However, the typical configuration of SSDs as emulating HDDs in computer systems significantly limits their impact for data-intensive applications. The objective of this research is to develop new use paradigms of SSDs in data-intensive applications on a Reconfigurable Polymorphous Processing Architecture (RPPA). RPPA consists of three major components: (1) heterogeneous processors such as CPUs and custom processing units, (2) data storage devices such as SSDs and DRAMs, and (3) a reconfigurable interconnect. The interconnect can be adaptively reconfigured as desired to fit the data communication and access pattern between the processors and the data storage devices to maximize the performance for various applications such as image processing and image registration. The direct output of this research has two folds. First, novel and application-specific use paradigms of SSD for various data-intensive applications are demonstrated. Second, the methodology and the infrastructure to develop the RPPA for exploiting the performance potentials of SSDs are established. The results of this project can transform the way SSDs are used in future computer systems for data-intensive applications. The integration of research results into several related CSE courses, such as computer organization and embedded system, provides hands-on experience in application-specific platform design to undergraduates, especially minority and women students.