Blog Posts

My Journey Building a 3MF Native Rust Library from Scratch

For the past few years, I’ve been getting more and more into 3D printing as a hobbyist. Like everyone, I started with one, a Bambu Lab X1 Carbon, which has now grown to three printers. I find the hobby fascinating as it entangles software, firmware, hardware, physics, and materials science.

As a software engineer, I’m naturally drawn to the software side of things (Slicer and Firmware). But what interests me most, is how the software interacts with the hardware and the materials. How the slicer translates the 3D model into instructions for the printer (G-Code). How the printer executes those instructions. How the materials behave under the printer’s control.

I Added a Feature to OrcaSlicer to Show Travel Distance and Moves

OrcaSlicer is a powerful and popular slicer for 3D printers, known for its rich feature set and active development community. In this blog post, we’ll take a closer look at a new feature I proposed and implemented that provides more insight into your prints: the display of total travel distance and the number of travel moves. See the feat: Display travel distance and move count in G-code summary for more details.

How to Build OrcaSlicer from Source on macOS 15 Sequoia - A Step-by-Step Guide

Building OrcaSlicer from source on macOS 15 (15.6.1 Sequoia) can be straightforward, but recent changes in macOS, Xcode, and CMake require some extra care. This guide updates the official instructions with important tips and fixes from this GitHub issue to avoid common build issues.

For this article, we will be using this build system:

Apple MacBook Pro M1 (Apple Silicon)
macOS 15.6.1 (Sequoia)
Orca Slicer 2.3.1 from https://github.com/SoftFever/OrcaSlicer

Prerequisites

Before you start, ensure you have the following installed:

How to Build acpidump from Source and use it to Debug Complex CXL and PCI Issues

This article is a detailed guide on how to build the latest version of the acpidump tool from its source code. While many Linux distributions, like Ubuntu, offer a packaged version of this utility, it’s often outdated. For developers and enthusiasts working with modern hardware features, particularly those related to Compute Express Link (CXL), having the most current version is essential.

Before you begin, it’s important to remove any old, conflicting versions of the tools. If you have previously installed the acpica-tools package from your distribution’s repository, you should remove it to prevent conflicts.

Is Your Application Really Using Persistent Memory? Here’s How to Tell.

Persistent memory (PMEM), especially when accessed via technologies like CXL, promises the best of both worlds: DRAM-like speed with the durability of an SSD. When you set up a filesystem like XFS or EXT4 in FSDAX (File System Direct Access) mode on a PMEM device, you’re paving a superhighway for your applications, allowing them to map files directly into their address space and bypass the kernel’s page cache entirely.

But here’s the crucial question: after all the setup and configuration, how do you prove that your application’s data is physically residing on the PMEM device and not just in regular RAM? I’ve run into this question myself, so I wrote a small Python script to get a definitive answer using SQLite3 as an example application. However, before we proceed with the script, let’s examine how you can verify this manually.

How to Confirm Virtual to Physical Memory Mappings for PMem and FSDAX Files

Are you curious whether your application’s memory-mapped files are really using Intel Optane Persistent Memory (PMem), Compute Express Link (CXL) Non-Volatile Memory Modules (NV-CMM), or another DAX-enabled persistent memory device? Want to understand how virtual memory maps onto physical, non-volatile regions? Let’s use easily adaptable scripts in both Python and C to confirm this on your Linux system, definitively.

Why Does This Matter?

With the advent of persistent memory and DAX (Direct Access) filesystems, applications can memory-map files directly onto PMem, bypassing the traditional DRAM page cache. This promises significant performance and durability improvements for data-intensive workloads and databases, such as SQLite, Redis, and others.

CXL Memory NUMA Node Mapping with Sub-NUMA Clustering (SNC) on Linux

CXL (Compute Express Link) memory devices are revolutionizing server architectures, but they also introduce new NUMA complexity, especially when advanced memory configurations, such as Sub-NUMA Clustering (SNC), are enabled. One of the most confusing issues is the mismatch between NUMA node numbers reported by CXL sysfs attributes and those used by Linux memory management tools.

This blog post walks through a real-world scenario, complete with command outputs and diagrams, to help you understand and resolve the CXL NUMA node mapping issue with SNC enabled.

CXL Device & Fabric Buyer's Guide: A List of GA Components (2025)

Last Updated: June 27, 2025

This guide provides a curated list of generally available (GA) Compute Express Link (CXL) devices, fabric components, and memory appliances. It is a technical resource for engineers, architects, and hardware specialists looking to identify and compare CXL memory expansion modules, switches, and full system-level appliances from leading vendors. The tables below detail market-ready components, focusing on the specifications required to design and build CXL-enabled infrastructure.