Understanding the C/C++ memory model

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Software is Crap

I know that a lot of people struggle with understanding the memory model introduced in C11/C++11. In a recent conversation I was alerted to the existence of this blog post, which while correct (by my understanding) is in my opinion aimed at those who already have a good understanding of some of the underlying concepts. I’m going to try to set out my understanding of the model, which is hopefully correct, in more straightforward terms and with a more “ground up” explanation.

Introduction: Program order versus memory order

You have your C/C++ program and it stores values (sets a variable or stores a value through a pointer) and it loads values (reads a variable or reads a value through a pointer). The order that your program specifies these loads and stores is the “program order”. However, there are a number of things that can cause the order in which…

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Kaggle Learn review: there is a deep learning track and it is worth your time

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Tech and Mortals

Right from my undergrad days when I was starting out with machine learning to this date, my admiration for Kaggle continues to grow. In addition to being synonymous with and popularizing data science competitions, the platform has served as a launching pad and breeding ground for countless data science and machine learning practitioners around the world, including yours truly. In fact, skills I’d picked up from the platform are part of the reason that I recently got to join SocialCops, a company I’d admired for years. However, I hadn’t been on the platform in 2017 as much as I would have liked. So when I saw Ben Hamner‘s tweet launching Kaggle Learn, a set of interactive data science tutorials, I made up my mind to give it a shot.

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A practitioner’s guide to reading programming languages papers

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the morning paper

Last week I jokingly said that POPL papers must pass an ‘intellectual intimidation’ threshold in order to be accepted. That’s not true of course, but it is the case that programming languages papers can look especially intimidating to the practitioner (or indeed, the academic working in a different sub-discipline of computer science!). They are full of dense figures with mathematical symbols, and phrases thrown around such as “judgements”, “operational semantics”, and the like. There are many subtle variations in notation out there, but you can get a long way towards following the gist of a paper with an understanding of a few basics. So instead of covering a paper today, I thought I’d write a short practitioner’s guide to decoding programming languages papers. I’m following Pierce’s ‘Types and Programming Languages’ as my authority here.

Syntax

Let’s start from a place of familiarity: syntax. The syntax tells us what…

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One model to learn them all

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the morning paper

One model to learn them all Kaiser et al., arXiv 2017

You almost certainly have an abstract conception of a banana in your head.

Suppose you ask me if I’d like anything to eat. I can say the word ‘banana’ (such that you hear it spoken), send you a text message whereby you see (and read) the word ‘banana,’ show you a picture of a banana, and so on. All of these different modalities (the sound waves, the written word, the visual image) tie back to the same concept – they are different ways of ‘inputting’ the banana concept. Your conception of bananas is independent of the way the thought popped into your head. Likewise, as an ‘output’ I could ask you to say the word banana, write the word banana, draw a picture of a banana, and so on. We are able to reason about such concepts independently of…

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