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TH-iSSD: Design and Implementation of a Generic and Reconfigurable Near-Data Processing Framework by Jiwu Shu; Kedong Fang; Youmin Chen; Shuo Wang is a Computer Science article available to read on EtoBox.

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We present the design and implementation of TH-iSSD, a near-data processing framework to address the data movement problem. TH-iSSD does not pose any restriction to the hardware selection and is highly reconfigurable—its core components, such as the on-device compute unit (e.g., FPGA, embedded CPUs) and data collectors (e.g., camera, sensors), can be easily replaced to adapt to different use cases. TH-iSSD achieves this goal by incorporating highly flexible computation and data paths. In the data path, TH-iSSD adopts an efficient device-level data switch that exchanges data with both host CPUs and peripheral sensors; it also enables direct accesses between the sensing, computation, and storage hardware components, which completely eliminates the redundant data movement overhead, and thus delivers both high performance and energy efficiency. In the computation path, TH-iSSD provides an abstraction of __filestream__ for developers, which abstracts a collection of data along with the related computation task as a file. Since existing applications are familiar with POSIX-like interfaces, they can be ported on top of our platform with minimal code modification. Moreover, TH-iSSD also in

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Author

Jiwu Shu; Kedong Fang; Youmin Chen; Shuo Wang

Publisher

ACM

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)