ENN (Edge Neural Network)
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ENN (Edge Neural Network)

David Ojika

David Ojika

, Florida

ENN is a project that implements DNN on the edge for faster inference compared to a cloud-only approach.

Artificial Intelligence

  • 1 Collaborators

  • 49 Followers

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Description

Nowadays, the training phase of AI -- which is highly compute-intensive -- is being increasingly sped up by cloud computing. However, communicating with the cloud introduces latency during AI inference phase, which leads to poor performance for applications requiring 'hard' real-time responses from an on-premise location. We define "hard real-time" as a microsecond timescale, end-to-end, for a single batch of data communication and data processing. We propose Edge Neural Network (ENN), a distributed architecture for accelerated DNNs on the edge. The main objective of the ENN project is to design and build an AI software and hardware system with real-time inference capabilities for edge applications that exhibit high-speed, massive dataset characteristics wherein communicating with the cloud directly would be impractical or too expensive.

Github: https://github.com/davenso/edgenn

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David O. added photos to project ENN (Edge Neural Network)

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ENN (Edge Neural Network)

Nowadays, the training phase of AI -- which is highly compute-intensive -- is being increasingly sped up by cloud computing. However, communicating with the cloud introduces latency during AI inference phase, which leads to poor performance for applications requiring 'hard' real-time responses from an on-premise location. We define "hard real-time" as a microsecond timescale, end-to-end, for a single batch of data communication and data processing. We propose Edge Neural Network (ENN), a distributed architecture for accelerated DNNs on the edge. The main objective of the ENN project is to design and build an AI software and hardware system with real-time inference capabilities for edge applications that exhibit high-speed, massive dataset characteristics wherein communicating with the cloud directly would be impractical or too expensive.

Github: https://github.com/davenso/edgenn

15934164 1204653962936463 1111344975 o

David O. added photos to project ENN (Edge Neural Network)

Medium c7153c70 d6a9 43d0 aa76 2a418294a2b0

ENN (Edge Neural Network)

Nowadays, the training phase of AI -- which is highly compute-intensive -- is being increasingly sped up by cloud computing. However, communicating with the cloud introduces latency during AI inference phase, which leads to poor performance for applications requiring 'hard' real-time responses from an on-premise location. We define "hard real-time" as a microsecond timescale, end-to-end, for a single batch of data communication and data processing. We propose Edge Neural Network (ENN), a distributed architecture for accelerated DNNs on the edge. The main objective of the ENN project is to design and build an AI software and hardware system with real-time inference capabilities for edge applications that exhibit high-speed, massive dataset characteristics wherein communicating with the cloud directly would be impractical or too expensive.

Github: https://github.com/davenso/edgenn

Medium 15934164 1204653962936463 1111344975 o

David O. created project ENN (Edge Neural Network)

Medium c7153c70 d6a9 43d0 aa76 2a418294a2b0

ENN (Edge Neural Network)

Nowadays, the training phase of AI -- which is highly compute-intensive -- is being increasingly sped up by cloud computing. However, communicating with the cloud introduces latency during AI inference phase, which leads to poor performance for applications requiring 'hard' real-time responses from an on-premise location. We define "hard real-time" as a microsecond timescale, end-to-end, for a single batch of data communication and data processing. We propose Edge Neural Network (ENN), a distributed architecture for accelerated DNNs on the edge. The main objective of the ENN project is to design and build an AI software and hardware system with real-time inference capabilities for edge applications that exhibit high-speed, massive dataset characteristics wherein communicating with the cloud directly would be impractical or too expensive.

Github: https://github.com/davenso/edgenn

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Lakshmanan Meiyappan

119, Avvai Complex,, Kamaraj Road, Tiruppur, Tamil Nadu 641601, India

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Liang Wang

Postdoc Researcher @ Computer Laboratory at Cambridge University

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Vimal Raj V

Undergraduate in Mechanical Engineering with a craze towards computers and technology.

No: 1, Head Quarters Road, Upplipalayam Coimbatore - 641 018, Tamil Nadu, India, Head Quarters Rd, Gopalapuram, Coimbatore, Tamil Nadu 641018, India

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Debdyut Hajra

Electronics Engineering Student, B. P. Poddar Institute of Management and Technology.

Uttarpara Kotrung, West Bengal, India

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Uğur Ünlü

İstanbul, Istanbul, Türkiye

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Omkar Patil

Hi Omkar here. I'm pursuing degree in Electronics and Telecommunications Engineering.

Mumbai, Maharashtra, India

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Mark Csizmadia

An undergraduate student on Electrical Engineering MEng at the University of Manchester, Manchester, United Kingdom.

Manchester, UK

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