Text

Automated Software language and Software engineering

Digitalisation

Heterogeneous systems - hardware software co-design

Industrial Software Engineering

Formal Modelling and Analysis of Embedded Systems

Model-Based Engineering of Embedded Systems

Information Design

Product and Production Development

PREVIVE

Real-Time Systems Design

Renewable Energy

Political Science

Resource efficiency

Sustainable lifestyle and health from a public health perspective

Software Testing Laboratory

DeepMaker: Deep Learning Accelerator on Commercial Programmable Devices

DeepMaker aims to provide a framework to generate synthesizable accelerators of Deep Neural Networks (DNNs) that can be used for different FPGA fabrics.

Concluded

Start

2018-02-15

Conclusion

2021-02-15

Project manager at MDH

No partial template found

DeepMaker aims to provide a framework to generate synthesizable accelerators of Deep Neural Networks (DNNs) that can be used for different FPGA fabrics. DeepMaker enables effective use of DNN acceleration in commercially available devices that can accelerate a wide range of applications without a need of costly FPGA reconfigurations.

 

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