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Modellbaserad konstruktion av inbäddade system

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.

Start

2018-02-15

Planerat avslut

2021-02-15

Huvudfinansiering

KK-stiftelsen

Samarbetspartners

Saab AB, Avionics Systems och Unibap AB

Projektansvarig

Universitetslektor

Masoud Daneshtalab

+4621103111

masoud.daneshtalab@mdh.se

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.