Liquid Silicon: A Data-Centric Reconfigurable Architecture enabled by RRAM Technology

Abstract

This paper presents a data-centric reconfigurable architecture, namely Liquid Silicon, enabled by emerging non-volatile memory, i.e., RRAM. Compared to the heterogeneous architecture of commercial FPGAs, Liquid Silicon is inherently a homogeneous architecture comprising a two-dimensional (2D) array of identical ‘tiles’. Each tile can be configured into one or a combination of four modes: TCAM, logic, interconnect, and memory. Such flexibility allows users to partition resources based on applications? needs, in contrast to the fixed hardware design using dedicated hard IP blocks in FPGAs. In addition to better resource usage, its ‘memory friendly’ architecture effectively addresses the limitations of commercial FPGAs i.e., scarce on-chip memory resources, making it an effective complement to FPGAs. Moreover, its coarse-grained logic implementation results in shallower logic depth, less inter-tile routing overhead, and thus smaller area and better performance, compared with its FPGA counterpart. Our study shows that, on average, for both traditional and emerging applications, we achieve 62% area reduction, 27% speedup and 31% improvement in energy efficiency when mapping applications onto Liquid Silicon instead of FPGAs.

Publication
Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, ser. FPGA ‘18, Monterey, California, USA, Feb, 2018

(Acceptance Rate*: underline24%, Ranked **#1** among 100+ submissions)

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Yue Zha
PhD Candidate

Has explored the full system for reconfigurable computing and processing-in-memory.