chitchcock

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

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

elizabrock

Great Papers in Computer Science

19th Century

Lovelace, Ada Augusta (1842) "Notes on the Analytical Engine"

1930's

Aiken, Howard (1937) "Proposed Automatic Calculating Machine"

marcan

#!/boot/bzImage

# Linux kernel userspace initialization code, translated to bash
# (Minus floppy disk handling, because seriously, it's 2017.)
# Not 100% accurate, but gives you a good idea of how kernel init works
# GPLv2, Copyright 2017 Hector Martin <marcan@marcan.st>
# Based on Linux 4.10-rc2.

# Note: pretend chroot is a builtin and affects the current process
# Note: kernel actually uses major/minor device numbers instead of device name

henrytill

(** "Landin's Knot" - implements recursion by backpatching *)
let landins_knot f =
  let r = ref (fun x -> assert false) in
  let fixedpoint = f (fun x -> !r x) in
  r := fixedpoint;
  fixedpoint

let factorial =
  let g f x =
    if x = 0 then

brson

Edit: This list is now maintained in the rust-anthology repo.

• Introduction
  • Understanding Over Guesswork
  • An Alternative Introduction to Rust
  • Rust and CSV Parsing
• Ownership
  • Where Rust Really Shines
  • Rust Means Never Having to Close a Socket
• The Problem with Single-threaded Shared Mutability

acolyer

A collection of The Morning Paper posts relating to containers, operating systems etc.

In order of first appearance in The Morning Paper.

• On the duality of operating system structures
• Why threads are a bad idea
• Why events are a bad idea
• Unikernels: library operating systems for the cloud
• The scalable commutativity rule: designing scalable software for multicore processors
• Jitsu: just-in time summoning of unikernels

MattPD

Program Analysis Resources

(draft; work in progress)

See also:

• Compilers
  • correctness
• Program analysis:
• Dynamic analysis - instrumentation, translation, sanitizers

pervognsen

/*
transpose_ij (10000x5000): gmemops=0.23, min=0.436734, avg=0.455368, relerr=3.42%
transpose_ji (10000x5000): gmemops=0.28, min=0.356635, avg=0.363628, relerr=2.55%
transpose_ij_ij (10000x5000): gmemops=1.53, min=0.065207, avg=0.069465, relerr=6.07%
transpose_rec1 (10000x5000): gmemops=1.44, min=0.069258, avg=0.075378, relerr=8.96%
transpose_rec2 (10000x5000): gmemops=1.37, min=0.072819, avg=0.079644, relerr=8.77%

transpose_ij (100000x100): gmemops=1.70, min=0.011731, avg=0.014102, relerr=9.99%
transpose_ji (100000x100): gmemops=0.23, min=0.086909, avg=0.095706, relerr=3.37%
transpose_ij_ij (100000x100): gmemops=1.73, min=0.011543, avg=0.013170, relerr=6.96%

pervognsen

void parse_expr(Value *dest);

Sym *parse_ident(void) {
    if (tok != TOK_IDENT) {
        error("Expected identifier");
    }
    Sym *ident = tok_sym;
    next();
    return ident;
}