Start here if you're new to ML. In nineteen problems we'll get from dot products to a working training loop, all in NumPy. Implement the building blocks (sigmoid, softmax, cross-entropy, attention masks), then build a linear layer and work through the backwards passes that make training work.

When you build software for embedded devices (your Wi-Fi router or home automation setup on your Raspberry Pi), there is always the question how to build these images and how to update them.

Last year, I came agross a Linux kernel feature called TCG_TPM2_HMAC. It claims to detect or prevent active and passive interposer attackers.
It all sounds really great. We should care about interposer adversaries. It’s great to use the TPM features that were invented to help us with these problems.

Poettering said that he does have a vision for how all of the security-related pieces of systemd are meant to fit together. He wanted to use his talk to explain ""how the individual security-related parts of systemd actually fit together and why they exist in the first place"".

Achieving high-performance asynchronous Rust projects transcends mere usage of the async/await syntax; it fundamentally relies on a deep understanding of the underlying task scheduling, lock optimization, and architecture design principles.

Rex Wangs blog

Pipes are ubiquitous in Unix --- but how fast can they go on Linux? In this post we'll iteratively improve a simple pipe-writing benchmark from 3.5GiB/s to 65GiB/s, guided by Linux perf.

This is a tutorial on how to build a digital implementation of a 2nd-order, continuously-variable filter (i.e. one where you can change the parameters runtime) that has dynamic behaviour that mimics an analogue filter.

This post can be considered an advanced Zig tutorial. I will be covering some of the more unique
aspects of the language, but won't be explaining the easy part. If you haven't read the Zig
Language Reference, you might start there. Additionally,
we will also learn the foundational trick for implementing relational model.

In this deep dive post, I’ll explain how I used the interning design pattern in Rust to compress this data set by a factor of two thousand! We’ll investigate how to best structure the interner itself, how to tune our data schema to work well with it, and likewise how serialization can best leverage interning.

In a previous post, I’ve shown how to use the rayon framework in Rust to automatically parallelize a loop computation across multiple CPU cores.
In this post, I’ll first explain which profiling tools I used to chase optimizations, before diving into how I built a faster replacement of Rayon for my use case. In the next post, I’ll describe the other optimizations that made my code much faster. Spoiler alert: copying some data sped up my code!

Fuzz testing is a technique for automatically uncovering bugs in software. The problem is that it’s a pain to set up. Read any fuzz testing tutorial, and the first task is an hour of building tools from source and chasing down dependencies upon dependencies.
I recently found that Nix eliminates a lot of the gruntwork from fuzz testing. I created a Nix configuration that kicks off a fuzz testing workflow with a single command.

This guide explains everything you need to know to build stand-alone photovoltaic systems that can power almost anything you want.

Below is a list of some lessons I’ve learned as a distributed systems engineer that are worth being told to a new engineer. Some are subtle, and some are surprising, but none are controversial. This list is for the new distributed systems engineer to guide their thinking about the field they are taking on. It’s not comprehensive, but it’s a good beginning.

In a previous article, I described how to set use Nix and Niv to configure an Elixir dev environment. This setup can be simplified by using Nix flakes instead of Niv.

In this article we build off what we’ve already learned about io_uring and extend that to build an async echo server.

JTAG for Reverse Engineers

The Best Practices for OSS Developers working group is dedicated to raising awareness and education of secure code best practices for open source developers.