jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

jlongster

// This function:

function foo() {
  var x = 5;
  var y = 6;
  debugger;
  return x + y;
}

jdegoes

Applied Functional Programming with Scala - Notes

Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.

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

OlivierBlanvillain

Revisiting Tagless Final Interpreters

Tageless Final interpreters are an alternative to the traditional Algebraic Data Type (and generalized ADT) based implementation of the interpreter pattern. This document presents the Tageless Final approach with Scala, and shows how Dotty with it's recently added implicits functions makes the approach even more appealing. All examples are direct translations of their Haskell version presented in the Typed Tagless Final Interpreters: Lecture Notes (section 2).

The interpreter pattern has recently received a lot of attention in the Scala community. A lot of efforts have been invested in trying to address the biggest shortcomings of ADT/GADT based solutions: extensibility. One can first look at cats' Inject typeclass for an implementation of [Data Type à la Carte](http://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesA

GLMeece

Latency Comparison Numbers

Note: "Forked" from Latency Numbers Every Programmer Should Know

Event	Nanoseconds	Microseconds	Milliseconds	Comparison
L1 cache reference	0.5	-	-	-
Branch mispredict	5.0	-	-	-
L2 cache reference	7.0	-	-	14x L1 cache
Mutex lock/unlock	25.0	-	-	-

densh

import scalanative.native._
import SDL._
import SDLExtra._

@extern
@link("SDL2")
object SDL {
  type Window   = CStruct0
  type Renderer = CStruct0

elizarov

import kotlin.coroutines.experimental.*
import kotlin.coroutines.experimental.intrinsics.*

fun main(args: Array<String>) {
    enumerate {
        if (flip("A")) {
            if (flip("B")) 1 else 2
        } else {
            if (flip("C")) 3 else if (flip("D")) 4 else 5
        }

djspiewak

type ∀[F[_]] = scalaz.Forall[F]

/**
 * An unpublished arbitrary type.  May be viewed as a formulation of
 * (∃ α . α).  Thus, we encode a rank-1 universal by means of a rank-2
 * existential.  This encoding is more convenient for our purposes.
 */
sealed trait τ

object τ {

Aerijo

A guide to writing a language grammar (TextMate) in Atom

Tree sitter

• Atom is transitioning to an entirely new way of defining grammars using tree-sitter. This will be enabled by default quite soon now. It is theoretically faster and more powerful than regex based grammars (the one described in this guide), but requires a steeper learning curve. My understanding is that regex based grammars will still be supported however (at least until version 2), so this guide can still be useful. To enable it yourself, go to Settings -> Core and check Use Tree Sitter Parsers

Links for tree-sitter help:

• tree-sitter: the main repo
• tree-sitter-cli: converts a JavaScript grammar to the required C/C++ files
• node-tree-sitter: module to use Tree-sitter parsers in NodeJS
• [My guide on starting a Tree-sitter grammar

Aerijo

Guide to your first Tree-sitter grammar

NOTE: The Tree-sitter API and documentation has changed and improved since this guide was created. I can't guarantee this is up to date.

About

Tree-sitter is the new way Atom is providing language recognition features, such as syntax highlighting, code folding, autocomplete, and more. In contrast to TextMate grammars, which work by regex matching, Tree-sitter will generate an entire syntax tree. But more on that can be found in it's own docs.

Here, we look at making one from scratch.