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Milan Nedić milannedic

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;; -*- mode: emacs-lisp -*-
;; This file is loaded by Spacemacs at startup.
;; It must be stored in your home directory.
(defun dotspacemacs/layers ()
"Layer configuration:
This function should only modify configuration layer settings."
(setq-default
;; Base distribution to use. This is a layer contained in the directory
;; `+distribution'. For now available distributions are `spacemacs-base'
Ovde ispratiti uputstvo za instalaciju SystemC-a:
https://howto.tech.blog/2016/11/27/installing-systemc-2-3-1/
Izbaciti environment varijable u prostor zavisno od lokacije instalacije SystemC-a:
export LD_LIBRARY_PATH="/usr/local/systemc-2.3.1/lib-linux64"
export SYSTEMC="/usr/local/systemc-2.3.1/"
# 1. Add these into your .bashrc
alias colormake='~/colormake.sh'
alias make='colormake'
alias gcc='COLORMAKE_COMMAND=gcc colormake'
alias clang='COLORMAKE_COMMAND=clang colormake'
# 2. source ~/.bashrc
# https://github.com/renatosilva/colormake/blob/master/colormake.sh
1# Install ghdl tool using this command:
sudo dpkg --install ghdl_0.33-1jessie1_amd64.deb
First you need to find it and download it from here (there are other versions as well):
https://sourceforge.net/projects/ghdl-updates/files/Builds/ghdl-0.33/debian/
Ubuntu 16.04 Fix: https://github.com/ghdl/ghdl/issues/166#issuecomment-482078983
----------------
Had to manually download and Install dependencies:
sudo dpkg -i gnat-4.8-base_4.8.2-8ubuntu3_amd64.deb
@milannedic
milannedic / sim.sh # GHDL environment
Last active June 4, 2019 20:21
Automation of VHDL compile/simulate process using GHDL and GTKWave. This script simulates testbench file, dumps .ghw file and runs GTKWave with it.
# call this like:
# ./sim.sh psds_v2 2_1 top_level_tb 1000ns wave.gtkw
# params:
# 1 - lesson dir
# 2 - problem folder, e.g 2_2
# 3 - model to test
# 4 - time interval to simulate
# 5 - gtkw setup file
@milannedic
milannedic / Keras2TensorBoard.py
Last active March 5, 2021 11:48
Steps needed to export Keras model .h5 file to .pb file used by Tensorboard in order to display network graph.
# How to use this:
#
# Step 1. You need to export Keras model to .h5 file
# which includes network architecture:
# https://github.com/amir-abdi/keras_to_tensorflow
# You can do this by including (**) line below your model definition
# for example, in my case:
# inception_v3 = keras.applications.inception_v3.InceptionV3(
# include_top=True,