pksunkara

[user]
	name = Pavan Kumar Sunkara
	email = pavan.sss1991@gmail.com
	username = pksunkara
[init]
	defaultBranch = master
[core]
	editor = nvim
	whitespace = fix,-indent-with-non-tab,trailing-space,cr-at-eol
	pager = delta

cander

#!/bin/sh
#
#
# From: allbery@ncoast.UUCP (allbery@ncoast.UUCP)
# Subject: bournebasic
# Newsgroups: comp.sources.misc
# Date: 1987-08-18 18:54:12 PST
# 
# Here's a useful BASIC interpreter written in Bourne shell.
# There's no manual but this demo shows the most salient features:

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

klange

Since this is on Hacker News and reddit...

• No, I don't distribute my résumé like this. A friend of mine made a joke about me being the kind of person who would do this, so I did (the link on that page was added later). My actual résumé is a good bit crazier.
• I apologize for the use of _t in my types. I spend a lot of time at a level where I can do that; "reserved for system libraries? I am the system libraries".
• Since people kept complaining, I've fixed the assignments of string literals to non-const char *s.
• My use of type * name, however, is entirely intentional.
• If you're using an older compiler, you might have trouble with the anonymous unions and the designated initializers - I think gcc 4.4 requires some extra braces to get them working together. Anything reasonably recent should work fine. Clang and gcc (newer than 4.4, at le

arvearve

Mathematics: What do grad students in math do all day?

by Yasha Berchenko-Kogan

A lot of math grad school is reading books and papers and trying to understand what's going on. The difficulty is that reading math is not like reading a mystery thriller, and it's not even like reading a history book or a New York Times article.

The main issue is that, by the time you get to the frontiers of math, the words to describe the concepts don't really exist yet. Communicating these ideas is a bit like trying to explain a vacuum cleaner to someone who has never seen one, except you're only allowed to use words that are four letters long or shorter.

What can you say?

dergachev

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

quchen

13:15 <xQuasar>      | HASKELL IS FOR FUCKIN FAGGOTS. YOU'RE ALL A BUNCH OF 
                     | FUCKIN PUSSIES
13:15 <xQuasar>      | JAVASCRIPT FOR LIFE FAGS
13:16 <luite>        | hello
13:16 <ChongLi>      | somebody has a mental illness!
13:16 <merijn>       | Wow...I suddenly see the error of my ways and feel 
                     | compelled to write Node.js!
13:16 <genisage>     | hi
13:16 <luite>        | you might be pleased to learn that you can compile 
                     | haskell to javascript now

jgoosey

--Haskell Quine
--Implementation 1
import Control.Monad
import Control.Monad.Instances
main = (putStr . ap (++) show)
  "--Haskell Quine\n--Implementation 1\nimport Control.Monad\nimport Control.Monad.Instances\nmain = (putStr . ap (++) show) "

--Implementation 2
--main = putStrLn (s ++ show s) where s =
--  "--Haskell Quine\n--Implementation 2\nmain = putStrLn (s ++ show s) where s ="

willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

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