Evidence map›Paper›PMID 30524230›Full record

ArticleFrontiers in neuroscience2018

Low Cost Interconnected Architecture for the Hardware Spiking Neural Networks.

Yuling Luo, Lei Wan, Junxiu Liu, Jim Harkin, Liam McDaid, Yi Cao, Xuemei Ding

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yuling LuoFaculty of Electronic Engineering, Guangxi Normal University, Guilin, China.
Lei WanFaculty of Electronic Engineering, Guangxi Normal University, Guilin, China.
Junxiu LiuFaculty of Electronic Engineering, Guangxi Normal University, Guilin, China.
Jim HarkinSchool of Computing, Engineering and Intelligent Systems, University of Ulster, Londonderry, United Kingdom.
Liam McDaidSchool of Computing, Engineering and Intelligent Systems, University of Ulster, Londonderry, United Kingdom.
Yi CaoManagement Science and Business Economics Group, Business School, University of Edinburgh, Edinburgh, United Kingdom.
Xuemei DingSchool of Computing, Engineering and Intelligent Systems, University of Ulster, Londonderry, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel low cost interconnected architecture (LCIA) is proposed in this paper, which is an efficient solution for the neuron interconnections for the hardware spiking neural networks (SNNs). It is based on an all-to-all connection that takes each paired input and output nodes of multi-layer SNNs as the source and destination of connections. The aim is to maintain an efficient routing performance under low hardware overhead. A Networks-on-Chip (NoC) router is proposed as the fundamental component of the LCIA, where an effective scheduler is designed to address the traffic challenge due to irregular spikes. The router can find requests rapidly, make the arbitration decision promptly, and provide equal services to different network traffic requests. Experimental results show that the LCIA can manage the intercommunication of the multi-layer neural networks efficiently and have a low hardware overhead which can maintain the scalability of hardware SNNs.

Indexed as

arbitration schemeinterconnected architectureNetworks-on-Chipspiking neural networkssystem scalability

Identifiers

PMID30524230
PMCPMC6258738

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.