2018 · 39 citations · 2 references
EngineeringComputer EngineeringComputer ScienceComputer VisionEmbedded SystemsField-programmable Gate ArraysAccelerator ArchitectureDeep LearningField-programmable Gate Array ArchitectureFpga ArchitectureHardware AccelerationRapid PrototypingAbstractionConvolutional Neural NetworksDeep Learning AccelerationDeep Learning AcceleratorsFpga PrototypingFramework ModificationImage Processing Accelerators
This work presents a self-contained and modifiable framework for fast and easy convolutional neural network prototyping on the Xilinx PYNQ platform. With a Python-based programming interface, the framework combines the convenience of high-level abstraction with the speed of optimised FPGA implementation. Our work is freely available on GitHub for the community to use and build upon.
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Angel-Eye: A Complete Design Flow for Mapping CNN onto Customized Hardware
Kaiyuan Guo, Lingzhi Sui, Jiantao Qiu et al. · 2016 · 72 citations