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- Xilinx (United States)US5 papers
- Norwegian University of Science and TechnologyNO4 papers
- Fermi National Accelerator LaboratoryUS2 papers
- Northwestern UniversityUS2 papers
- The University of SydneyAU2 papers
- University of California, BerkeleyUS2 papers
- University of California San DiegoUS2 papers
- Association for Computing MachineryUS1 paper
- Birla Institute of Technology and Science, PilaniIN1 paper
- Cerebras Systems (United States)1 paper
- Coburg University of Applied SciencesDE1 paper
- Columbia UniversityUS1 paper
5 papers · 1 filter
Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs
Yifan Yang, Qijing Huang, Bichen Wu +8
Using FPGAs to accelerate ConvNets has attracted significant attention in recent years. However, FPGA accelerator design has not leveraged the latest progress of ConvNets. As a res…
FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs
Vladimir Rybalkin, Alessandro Pappalardo, Muhammad Mohsin Ghaffar +3
It is well known that many types of artificial neural networks, including recurrent networks, can achieve a high classification accuracy even with low-precision weights and activat…
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic
Michaela Blott, Thomas B. Preusser, Nicholas Fraser +4
Convolutional Neural Networks have dramatically improved in recent years, surpassing human accuracy on certain problems and performance exceeding that of traditional computer visio…
BISMO: A Scalable Bit-Serial Matrix Multiplication Overlay for Reconfigurable Computing
Yaman Umuroglu, Lahiru Rasnayake, Magnus Sjalander
Matrix-matrix multiplication is a key computational kernel for numerous applications in science and engineering, with ample parallelism and data locality that lends itself well to…
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices
Thomas B. Preußer, Giulio Gambardella, Nicholas Fraser +1
Neural networks have established as a generic and powerful means to approach challenging problems such as image classification, object detection or decision making. Their successfu…