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From Hardware to Software Synthesis of Linear Feedback Shift Registers

Authors: Cédric Lauradoux;

From Hardware to Software Synthesis of Linear Feedback Shift Registers

Abstract

Linear feedback shift registers (LFSRs) have always received considerable attention in computer science especially in coding theory and in cryptography. The scope of applications of LFSRs is wide: data scrambling, spread spectrum, build in self tests (BISTs). They have to be implemented either in hardware or in software. Unlike hardware, software applications have not been very popular. The main reason is that, even if the LFSR synthesis in software is very similar to the LFSR synthesis on Xilinx FPGA, the overall processing is parallel in hardware while it is almost sequential in software, leading to low throughput implementations. If the naive LFSR implementation is in favor of hardware, increasing the number of LFSR steps computed at the same time can considerably improve software implementation. For instance, we obtain a 103 speedup factor for a 128-bit LFSR on 64-bit processors. Unfortunately, this cannot be obtain for all LFSRs. We here describe how LFSR parameters must be chosen to obtain an efficient implementation.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Average
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