FPGAs are an attractive choice for DNNs since they offer a programmable substrate for acceleration and are becoming available across different market segments.

DNNWEAVER provides a comprehensive and automated solution to make FPGAs available to a broader community of. DNN application developers who use a wide range of ...

Deep Neural Networks: A Move. Towards Artificial Intelligence. Video Categorization. Page 3. Programmability is a First-Order Concern. CPUs. FPGAs. ASICs. GPUs.

FPGAs are an attractive choice for DNNs since they offer a programmable substrate for acceleration and are becoming available across different market segments.

Caffe is a widely used open-source deep learning framework that takes the DNN specification as input and computes the given model on the CPU and GPU platforms.

ABSTRACT. Deep Neural Networks (DNNs) are compute-intensive learning models with growing applicability in a wide range of domains. FPGAs are an attractive ...

DnnWeaver is devised, a framework that automatically generates a synthesizable accelerator for a given DNN, FPGA pair from a high-level specification in ...

This work tackles these challenges by devising DnnWeaver, a framework that automatically generates a synthesizable accelerator for a given (DNN, FPGA) pair ...

Feb 2, 2023 · I've found many posts here and there that claim that FPGAs are better suited than GPUs to accelerate Deep Learning/AI workloads.

In this work, we propose new power models based on neural networks that predict the power consumed by digital operators implemented on Field Programmable Gate ...