Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Xiaojin Sui

dblp:228/2723 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0003-0378-566XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 61% Reconfigurable computing and FPGAs · 39%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems › non-volatile memory
multilevel cell storage
0.312018
NVM-Based FPGA Block RAM With Adaptive SLC-MLC Conversion · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2018
Memory systems
non-volatile memory
0.312018
NVM-Based FPGA Block RAM With Adaptive SLC-MLC Conversion · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2018
Reconfigurable computing and FPGAs
FPGA design flow
0.112018
NVM-Based FPGA Block RAM With Adaptive SLC-MLC Conversion · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2018

Methods — techniques the papers use, named apart from their topics

adaptive SLC-MLC conversion · 0.3
YearPublicationVenuePosition
2018 NVM-Based FPGA Block RAM With Adaptive SLC-MLC Conversion
abstract
The capacity of SRAM-based FPGA block RAM (BRAM) is restrained by the low density and high leakage power of the current CMOS technology. In this paper, we propose a nonvolatile memory (NVM)-based BRAM architecture which enables flexible conversions between single-level cell (SLC) and multilevel cell (MLC) states. We show that despite the high per-access latency and power consumption, MLC-based BRAM blocks reduce the routing cost between logic units and on-chip data storages, which potentially leads to a smaller critical path delay and power consumption. Therefore, we propose an NVM BRAM architecture and an EDA framework which adaptively packs data into SLC- or MLC-state BRAMs during FPGA design flow in order to achieve better system performance. This paper illustrates that a simple memory device replacement from SRAM to NVM leads to nonoptimal system performance. On the other hand, compared with operating all NVM BRAM blocks in the SLC state with better per-access latency and power consumption, the proposed hybrid SLC-MLC architecture and design flow improves the critical path delay by 18.51%, with a system power reduction of 25.83% at the same time. Moreover, compared with the traditional “fast” SRAM-based BRAM blocks under the same BRAM area constraint, our hybrid NVM BRAM architecture improves the critical path delay by 8.55% on average, with an average system power reduction of 54.34% at the same time.
Lei Ju 0001, Xiaojin Sui, Shiqing Li, Mengying Zhao, Chun Jason Xue, Jingtong Hu, Zhiping Jia
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.2