4 citations · 7 across the 4 of their papers we have counts for
3 papers · 1 filter
Quality Scalable Quantization Methodology for Deep Learning on Edge
Salman Abdul Khaliq, Rehan Hafiz
Deep Learning Architectures employ heavy computations and bulk of the computational energy is taken up by the convolution operations in the Convolutional Neural Networks. The objec…
Systimator: A Design Space Exploration Methodology for Systolic Array based CNNs Acceleration on the FPGA-based Edge Nodes
Hazoor Ahmad, Muhammad Tanvir, Muhammad Abdullah Hanif +3
The evolution of IoT based smart applications demand porting of artificial intelligence algorithms to the edge computing devices. CNNs form a large part of these AI algorithms. Sys…
MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks
Muhammad Abdullah Hanif, Rachmad Vidya Wicaksana Putra, Muhammad Tanvir +3
The state-of-the-art accelerators for Convolutional Neural Networks (CNNs) typically focus on accelerating only the convolutional layers, but do not prioritize the fully-connected…