denguir

How to install CUDA / cuDNN / TensorRT on Ubuntu

Install NVIDIA drivers

Update & upgrade

sudo apt update && sudo apt upgrade

Remove previous NVIDIA installation

LostKobrakai

defmodule NestedWeb.FormLive do
  use NestedWeb, :live_view
  require Logger

  defmodule Form do
    use Ecto.Schema
    import Ecto.Changeset

    embedded_schema do
      field :name, :string

jmatsushita

###
### [2023-06-19] UPDATE: Just tried to use my instructions again on a fresh install and it failed in a number of places. 
###.   Not sure if I'll update this gist (though I realise it seems to still have some traffic), but here's a list of 
###.   things to watch out for:
###      - Check out the `nix-darwin` instructions, as they have changed.
###      - There's a home manager gotcha https://github.com/nix-community/home-manager/issues/4026
###

# I found some good resources but they seem to do a bit too much (maybe from a time when there were more bugs).
# So here's a minimal Gist which worked for me as an install on a new M1 Pro.

seanmor5

Genetic Algorithm in Nx

Preface

After writing Genetic Algorithms in Elixir, I had no real hopes or expectations that numerical computing would become a focus for Elixir. However, to my surprise, the Nx project developed rather quickly, and proved that Elixir could be used for practical machine learning and numerical computing applications. While I don't have any plans (yet) of reworking the examples in my book to take advantage of the acceleration enabled by Nx, EXLA, and other projects, I feel it's necessary to show how you could go about rewriting your genetic algorithms to take advantage of Elixir's new numerical computing libraries.

Introduction

Nx is a numerical computing library for Elixir which supports the creation and manipulation of multi-dimensional arrays (called tensors in the API), automatic differentiation, and just-in-time (JIT) compilation to CPU, GPU, and other accelerators via pluggable backends and compilers. Nx opens up a realm of possibilities for Elixir dev

mcrumm

// assets/js/app.js

// ...
import Pickr from "./pickr"

const hooks = {
  Pickr
}

// ...

m-root

import talib
import statsmodels.api as sm
import pandas as pd

def initialize(context):
    context.security = symbol('AAPL')
    #set_universe(universe.DollarVolumeUniverse(floor_percentile=98.0,ceiling_percentile=100.0))
    
def bar_data(OHLC_type, bars_nr):
    bar_data_func = (history((bars_nr + 1), '1d', OHLC_type).iloc[0]).astype('float')

trestrantham

defmodule MyApp.Periodically do
  use GenServer

  def start_link do
    GenServer.start_link(__MODULE__, %{})
  end

  def init(state) do
    Process.send_after(self(), :work, 2 * 60 * 60 * 1000) # In 2 hours
    {:ok, state}

cawhitworth

import random

add = lambda a,b: a+b
sub = lambda a,b: a-b
mul = lambda a,b: a*b
div = lambda a,b: a/b if a % b == 0 else 0/0

operations = [ (add, '+'),
               (sub, '-'),
               (mul, '*'),

mprymek

# This is an example of metaprogramming in the Elixir language.
# 
# We will define a domain specific language (DSL) for the definition
# of a service which is watched by several sensors.
# Each sensor watches some property/functionality of the service and
# returns the result of the check.
# 
# To determine if the service is functioning properly, we need functions
# to run all the sensors' code and gather the returned data.
# 

rjkat

import Data.Complex
import Control.Arrow
import Control.Monad

fft :: [Complex Double] -> [Complex Double]
fft = fft' . pad

-- perform a fast fourier transform
fft' :: [Complex Double] -> [Complex Double]
fft' [x] = [x]