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As part of the development of our Precision Time Protocol implementation, Statime, we want to know how it performs compared to other implementations of PTP.

To figure this out, last April we visited VSL, the Dutch National Metrology Institute. There, we performed comparitive precision tests between Statime and Linux PTP.

While using a full-blown filesystem for storing your data in non-volatile memory is common practice, those filesystems are often too big, not to mention annoying to use, for the things I want to do. My solution?

I've been hard at work creating the sequential-storage crate. In this blog post I'd like to go over what it is, why I created it and what it does.

At Tweede golf we're big fans of creating applications on embedded devices with Rust and we've written a lot about it.

But if you're a hardware vendor (be it chips or full devices/systems), should you give your users Rust support in addition to your C support?

In this blog I argue that the answer to the question is yes.

At Tweede golf we are convinced that if software is written in Rust, it will be more robust (compared to legacy languages such as C, C++ or Java), and more efficient (compared to code written in PHP or Python and again, Java).

In order to get more robust software out there, we have to get Rust code running on computers of people who are not themselves Rust developers.

This article is an adaptation of the original, published by Prossimo.

We're happy to announce that the Internet Security Research Group has officially made us the maintainers of the open-source memory-safe implementation of NTP, ntpd-rs. As such, we are now also looking for early adopters.

The implementation includes a server and client, as well as full support for Network Time Security (NTS), which brings encryption and greater integrity to time synchronization. Timing is precise and stable, as reflected by excellent performance in the NTP pool.

While working on the Roc compiler, we regularly dive deep on computer science topics. A recurring theme is speed, both the runtime performance of the code that we generate, as well as the performance of our compiler itself.

One extremely useful technique that we have been playing with is data-oriented design: the idea that the actual data you have should guide how code is structured.

TrustZone-m is a technology by ARM that allows you to create a Trusted Execution Environment (TEE) in your software. You can use it for example to keep your encryption keys secret or to separate a big vulnerable networking stack from your own code.

Over the last three months I've been working on a set of crates (Rust libraries) with the aim of making the usage of TrustZone-m a lot easier.

Our year in Rust

A company-changing year in a short story,
begins with a thank you, for this new-found glory.

We want to be clear in this prelude,
It is to Rust we owe our gratitude.

Google recently published a blog article and paper introducing their SIMD-accelerated sorting algorithm.

SIMD stands for single instruction, multiple data. A single instruction is used to apply the same operation to multiple pieces of data. The prototypical example is addition, where one instruction can do e.g. 4 32-bit additions. A single SIMD addition should be roughly 4 times faster than performing 4 individual additions.

This kind of instruction-level parallelism has many applications in areas with a lot of number crunching, e.g. machine learning, physics simulations, and game engines. But how can this be used for sorting? Sorting does not involve arithmetic, and the whole idea of sorting is that each element moves to its unique correct place in the output. In other words, we don't want to perform the same work for each element, so at first sight it's hard to see where SIMD can help.

To understand the basic concepts, I played around with the ideas from the paper Fast Quicksort Implementation Using AVX Instructions by Shay Gueron and Vlad Krasnov. They provide an implementation in (surprisingly readable) assembly on their github. Let's see how we can make SIMD sort.

Pioneering Rust in the high-tech industry!

Together with High Tech Software Cluster, we organized an event to showcase Rust’s strengths and safety features to tech companies in the Brainport region in the Netherlands.

For the last couple of months we at Tweede golf have been working on implementing a Network Time Protocol (NTP) client and server in Rust.

The project is a Prossimo initiative and is supported by their sponsors, Cisco and AWS. Our first short-term goal is to deploy our implementation at Let's Encrypt. The long-term goal is to develop an alternative fully-featured NTP implementation that can be widely used.

In our last post, we've seen that async can help reduce power consumption in embedded programs. The async machinery is much more fine-grained at switching to a different task than we reasonably could be. Embassy schedules the work intelligently, which means the work is completed faster and we race to sleep. Our application actually gets more readable because we programmers mostly don't need to worry about breaking up our functions into tasks and switching between them. Any await is a possible switching point.

Now, we want to actually start using async in our programs. Sadly there are currently some limitations. In this post, we'll look at the current workarounds, the tradeoffs, and how the limitations might be partially resolved in the near future.