C++ Memory Model: Migrating from x86 to ARM
Estimated reading time: 18 minutes
Over the past years, we have seen a shift in processors from the previously dominant x86 architecture to the more energy-efficient (and often cheaper) ARM architecture. This trend is true for both consumer hardware, e.g., Apple’s M1 SoC and also server hardware, e.g. AWS’s Gravitron processor. Given that the ARM architecture has a more relaxed memory model, this might have some subtle impact on C++ programs…
With the introduction of multi-threaded execution in C++11, the standard also introduced a memory model. For many developers, this memory model is one of the least well-understood parts of the C++ standard and a common source of confusion. While an in-depth explanation of the C++ memory model is beyond this blog post’s scope, we will cover some basics and take a brief look at two of the most common hardware memory models and how the C++ memory model maps to these hardware models.
But first, let’s take a step back and consider why we need a memory model in the first place.
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ArangoDB allows running user-defined JavaScript code in the database. This can be used for more complex, stored procedures-like database operations. Additionally, ArangoDB’s Foxx framework can be used to make any database functionality available via an HTTP REST API. It’s easy to build data-centric microservices with it, using the scripting functionality for tasks like access control, data validation, sanitation etc.
We often get asked how the scripting functionality is implemented under the hood. Additionally, several people have asked how ArangoDB’s JavaScript functionality relates to node.js.
This post tries to explain that in detail.
Compile ArangoDB Source: Step-by-Step Guide | ArangoDB Blog
Though we provide a lot of pre-built packages for the stable versions of ArangoDB here, it is often more interesting to play with the bleeding edge development version. New ArangoDB features are normally added to the devel branch, where they can be tested, documented and improved. When a feature matures, it is either backported to a stable branch or will eventually be released when the next stable branch is forked from devel.
Contributing to the core of ArangoDB is also much easier with a ready-to-go devel version. This post explains how to set one up from scratch.
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