Alexandr Nikitin alexandrnikitin

Cloud GPUs: Servers, Providers & Everything You Would Ever Need

Your company's GPU computing strategy is essential whether you engage in 3D visualization, machine learning, AI, or any other form of intensive computing.

There was a time when businesses had to wait for long periods of time while deep learning models were being trained and processed. Because it was time-consuming, costly, and created space and organization problems, it reduced their output.

This problem has been resolved in the most recent GPU designs. Because of their high parallel processing efficiency, they are well-suited for handling large calculations and speeding up the training of your AI models.

When it comes to deep learning, good Cloud GPUs can speed up the training of neural networks by a factor of 250 compared to CPUs, and the latest generation of cloud GPUs is reshaping data science and other emerging technologies by delivering even greater performance

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

High-Performance Matrix Multiplication

This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).

Intro

Matrix multiplication is a mathematical operation that defines the product of

Usage

sed -E -f solver.sed input where input is a file containing the maze.

For best results, resize your terminal to match the height of the maze. To disable animations, delete the lines containing p.

Maze format

The solver assumes the following:

The maze only contains the characters # \nSE
Every line has the same number of characters
There is only one start (S) and end (E)

WannaCry|WannaDecrypt0r NSA-Cyberweapon-Powered Ransomware Worm

Virus Name: WannaCrypt, WannaCry, WanaCrypt0r, WCrypt, WCRY
Vector: All Windows versions before Windows 10 are vulnerable if not patched for MS-17-010. It uses EternalBlue MS17-010 to propagate.
Ransom: between $300 to $600. There is code to 'rm' (delete) files in the virus. Seems to reset if the virus crashes.
Backdooring: The worm loops through every RDP session on a system to run the ransomware as that user. It also installs the DOUBLEPULSAR backdoor. It corrupts shadow volumes to make recovery harder. (source: malwarebytes)
Kill switch: If the website www.iuqerfsodp9ifjaposdfjhgosurijfaewrwergwea.com is up the virus exits instead of infecting the host. (source: malwarebytes). This domain has been sinkholed, stopping the spread of the worm. Will not work if proxied (source).

update: A minor variant of the viru

Applied Functional Programming with Scala - Notes

1. Mastering Functions

A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.

val square : Int => Int = x => x * x

ProcessBuilder

Signature	Proposed Name	Scaladoc
`!(log: ProcessLogger): Int`	exitValue	Starts the process represented by this builder, blocks until it exits, and returns the exit code.
`!: Int`	exitValue	Ibid.
`!<(log: ProcessLogger): Int`	exitValueStdIn	Ibid.

	//
	// See https://github.com/louthy/language-ext
	//

	using System;
	using System.IO;
	using System.Linq;
	using System.Threading.Tasks;
	using LanguageExt;
	using static LanguageExt.Prelude;

	import scala.util.{Success, Failure}

	val seq=Seq(Success(1), Failure(new Exception("bang")), Success(2))

	// all emit List(1, 2)

	seq.map(_.toOption).flatten
	seq.flatMap(_.toOption)
	seq.filter(_.isSuccess).map(_.get)
	seq.collect{case Success(x) => x}