#multi-threading

#multi-threading

In the fintech industry we can link latency directly to profit and money. If I have lower latency than the competition, I can get to the better deals, I can make the better deals.

The Vec class implements 2D vectors, providing essential operations like addition, subtraction, scaling, and normalization, which are fundamental for all geometric calculations in the simulation.

You'll explore how I/O-bound programs face latency, which concurrency patterns to use, the differences between threading, asyncio, and multiprocessing, and how the Global Interpreter Lock (GIL) affects Python programs.

While the codebase is fresh and grows fast under the umbrella of the local environment, we tend to rely on debugging tools, which were created specifically for that purpose. The app is half-baked, and the code is split open. We observe it through the lens of our IDE and with the speed of our brain. Everything is possible; we may pause execution for minutes, and the whole system is a white box - an open book for us.

Which Algorithm Is This? If you step back, this maps almost perfectly to the Top K Frequent Elements problem.We usually solve it for integers in a list. Here, the "elements" are audience profiles age and body-type combinations. First, define what an audience profile looks like: case class Profile(age: Int, height: Int, weight: Int) What we want is a function like this:

The Xeon 600 lineup spans the gamut between 12 and 86 performance cores (no cut-down efficiency cores here), with support for between four and eight channels of DDR5 and 80 to 128 lanes of PCIe 5.0 connectivity. Compared to its aging W-3500-series chips, Intel is claiming a 9 percent uplift in single threaded workloads and up to 61 percent higher performance in multithreaded jobs, thanks in no small part to an additional 22 processor cores this generation.

With pthread's rwlock (reader-writer lock) implementation, I got 23.4 million reads in five seconds. With read-copy-update (RCU), I had 49.2 million reads, a one hundred ten percent improvement with zero changes to the workload.

Christopher shares an article titled "The Uselessness of 'Fast' and 'Slow' in Programming." It digs into how the different aspects of software performance span a wide range of orders of magnitude, and how developers can obsess over irrelevant performance details, often losing more time working in suboptimal environments than building what they need with tools they already know. We also discuss an article about why uv is fast, which explains how most of its speed comes from engineering decisions rather than just being written in Rust.

This quiz sharpens your intuition for Python's asyncio module. You'll decide when async is the right tool, see how the event loop schedules work, and understand how coroutines pause and resume around I/O.

If there's one universal experience with AI-powered code development tools, it's how they feel like magic until they don't. One moment, you're watching an AI agent slurp up your codebase and deliver a remarkably sharp analysis of its architecture and design choices. And the next, it's spamming the console with "CoreCoreCoreCore" until the scroll-back buffer fills up and you've run out of tokens.

JDK 26, the first non-LTS release since JDK 25, has reached its second release candidate as declared by Mark Reinhold, Chief Architect, Java Platform Group at Oracle. The main-line source repository, forked to the JDK stabilization repository in early-December 2025 (Rampdown Phase One), defines the feature set for JDK 26. Critical bugs, such as regressions or serious functionality issues, may be addressed, but must be approved via the Fix-Request process. As per the release schedule, JDK 26 will be formally released on March 17, 2026.

The reason for this is Snap - a Linux application packaging format - creates a local Trash folder for each VS Code version, one that's separate from the system-managed Trash, according to a VS Code bug report dating back to November 11, 2024. Not only that, but Snap keeps older versions of VS Code after updates, potentially multiplying the number of local Trash folders and the trashed-but-not-deleted files therein. Emptying the system Trash folder doesn't affect the local instances.

In total I probably spent around 45 minutes actively with it. It worked for around 3 hours while I was watching, then another 7 hours alone. This post is a recollection of what happened and what I learned from it. All prompting was done by voice using pi, starting with Opus 4.5 and switching to GPT-5.2 Codex for the long tail of test fixing.

XAI just open sourced the X recommendation algorithm, and honestly, it felt like they massacred my boy. I scrolled down expecting to see language stats like the 2023 repo. You know the usual breakdown: Java, Scala, maybe some Python sprinkled in. Instead, there were only two languages listed. Rust and Python. That's it. Which immediately tells you this wasn't a refactor. This was a full rewrite.

One thing I always do when I prompt a coding agent is to tell it to ask me any questions that it might have about what I've asked it to do. (I need to add this to my default system prompt...) And, holy mackerel, if it doesn't ask good questions. It almost always asks me things that I should have thought of myself.