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  • šŸ‘‹ Hi, Iā€™m @asadalam
  • šŸ‘€ Iā€™m interested in RTL based design and implementation of signal processing algorithms and deep neural network architectures
  • šŸŒ± Iā€™m currently learning how to design a hardware architecture of a quantized deep neural network and researching on Winograd short convolutions
  • šŸ’žļø Iā€™m looking to collaborate on quantized deep neural networks and novel ways to implement them
  • šŸ“« alam dot asad at gmail.com

Syed Asad Alam's Projects

caffe icon caffe

Caffe: a fast open framework for deep learning.

caffetutorials_example icon caffetutorials_example

Some caffe tutorials that I am following to increase my hands on working of it. Mostly are just copy-pasted from other sources, but soon enough I'll contribute something original

finn icon finn

Dataflow compiler for QNN inference on FPGAs

finn_matrixvector_rtl icon finn_matrixvector_rtl

Repository for work on on Xilinx's matrix vector activation unit's RTL implementation. Documentation available at: https://asadalam.github.io/FINN_MatrixVector_RTL/

microblog icon microblog

The flask mega tutorial by Miguel Grinberg. None of the code is mine, I only followed the blog to learn about flask. I have skipped a few sections which were not of interest to me. It also contains a docker file to deploy the whole app with just one command.

sysverilog_naturaldocs icon sysverilog_naturaldocs

A template repository showing how a System Verilog can have automatic documentation generated using Natural Docs along with Integration with Travis-CI

wincnn icon wincnn

Winograd minimal convolution algorithm generator for convolutional neural networks.

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