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

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

nadavrot

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

macintux

• https://ferd.ca/a-distributed-systems-reading-list.html
• http://the-paper-trail.org/blog/distributed-systems-theory-for-the-distributed-systems-engineer/
• https://github.com/palvaro/CMPS290S-Winter16/blob/master/readings.md
• http://muratbuffalo.blogspot.com/2015/12/my-distributed-systems-seminars-reading.html
• http://christophermeiklejohn.com/distributed/systems/2013/07/12/readings-in-distributed-systems.html
• http://michaelrbernste.in/2013/11/06/distributed-systems-archaeology-works-cited.html
• http://rxin.github.io/db-readings/
• http://research.microsoft.com/en-us/um/people/lamport/pubs/pubs.html
• http://pdos.csail.mit.edu/dsrg/papers/
• http://scalingsystems.com/2011/09/07/reading-list-for-distributed-systems/

Avaq

const I  = x => x
const K  = x => y => x
const A  = f => x => f (x)
const T  = x => f => f (x)
const W  = f => x => f (x) (x)
const C  = f => y => x => f (x) (y)
const B  = f => g => x => f (g (x))
const S  = f => g => x => f (x) (g (x))
const S_ = f => g => x => f (g (x)) (x)
const S2 = f => g => h => x => f (g (x)) (h (x))

tylerneylon

-- Two dashes start a one-line comment.

--[[
     Adding two ['s and ]'s makes it a
     multi-line comment.
--]]

----------------------------------------------------
-- 1. Variables and flow control.
----------------------------------------------------

karlgluck

What's this all about?

Digital cryptography! This is a subject I've been interested in since taking a class with Prof. Fred Schneider back in college. Articles pop up on Hacker News fairly often that pique my interest and this technique is the result of one of them.

Specifically, this is about Lamport signatures. There are many signature algorithms (ECDSA and RSA are the most commonly used) but Lamport signatures are unique because they are formed using a hash function. Many cryptographers believe that this makes them resistant to attacks made possible by quantum computers.

How does a Lamport Signature work?

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

gregsh

Here are my attempts to script an IntelliJ-based IDE using javax.script.* API (ex-JSR-223).

The list of available scripting languages and engines:

1. Groovy - built-in, via Groovy jars and <app>/lib/groovy-jsr223-xxx.jar
2. JavaScript (Nashorn) - built-in, via Java Runtime <app>/jbr/... (deprecated and will be removed soon)
3. JavaScript (GraalJS) - https://plugins.jetbrains.com/plugin/12548-intellij-scripting-javascript
4. JPython - https://plugins.jetbrains.com/plugin/12471-intellij-scripting-python
5. JRuby - https://plugins.jetbrains.com/plugin/12549-intellij-scripting-ruby
6. Clojure - https://plugins.jetbrains.com/plugin/12469-intellij-scripting-clojure

kachayev

Channels Are Not Enough

... or Why Pipelining Is Not That Easy

Golang Concurrency Patterns for brave and smart.

By @kachayev

Intro