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@bagheriali2001
bagheriali2001 / systemc_v2.3.3_installation_guide.md
Last active March 16, 2024 23:56
How to Install SystemC in Linux (Ubuntu, Debian, ...)
@isedgar
isedgar / ray-casting.js
Created June 4, 2021 00:38
Check if a 2D point is inside 2D simple polygon. It works with convex and concave polygons.
function ray_casting(point, polygon){
var n=polygon.length,
is_in=false,
x=point[0],
y=point[1],
x1,x2,y1,y2;
for(var i=0; i < n-1; ++i){
x1=polygon[i][0];
x2=polygon[i+1][0];
# IDA (disassembler) and Hex-Rays (decompiler) plugin for Apple AMX
#
# WIP research. (This was edited to add more info after someone posted it to
# Hacker News. Click "Revisions" to see full changes.)
#
# Copyright (c) 2020 dougallj
# Based on Python port of VMX intrinsics plugin:
# Copyright (c) 2019 w4kfu - Synacktiv

Delving into the why's of AXI

**Note: In all below, slave can also mean interconnect

  • Do we really need back-pressure?
    • Yes, you absolutely need backpressure. What happens when two masters want to access the same slave? One has to be blocked for some period of time. Some slaves may only be able to handle a limited number of concurrent operations and take some time to produce a result. As such, backpressure is required.
    • B and R channel backpressure is required in the case of contention towards the master. If a master makes burst read requests against two different slaves, one of them is gonna have to wait.
      • Shouldn't a master be prepared to receive the responses for any requests it issues from the moment it makes the request? Aside from the clock crossing issue someone else brought up, and the interconnect issue at the heart of the use of IDs, why should an AXI master ever stall R or B channels?
  • The master should be prepared, but it only has one R and one B input, so it can't re
@JoeyBurzynski
JoeyBurzynski / 55-bytes-of-css.md
Last active May 15, 2024 20:11
58 bytes of css to look great nearly everywhere

58 bytes of CSS to look great nearly everywhere

When making this website, i wanted a simple, reasonable way to make it look good on most displays. Not counting any minimization techniques, the following 58 bytes worked well for me:

main {
  max-width: 38rem;
  padding: 2rem;
  margin: auto;
}
@eamartin
eamartin / notebook.ipynb
Last active November 6, 2022 18:53
Understanding & Visualizing Self-Normalizing Neural Networks
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FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.


Effective Engineer - Notes

What's an Effective Engineer?

@leonardofed
leonardofed / README.md
Last active May 15, 2024 11:28
A curated list of AWS resources to prepare for the AWS Certifications


A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.


@karpathy
karpathy / pg-pong.py
Created May 30, 2016 22:50
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym
# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward