Blog Posts

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 While many Linux distributions, like Ubuntu, offer a packaged version of this utility, it’s often outdated.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.

CXL Server Buyer's Guide: A Complete List of GA Platforms (Updated 2025)

Last Updated: June 27, 2025

This quick reference guide provides a definitive, up-to-date list of generally available (GA) Compute Express Link (CXL) servers from major OEMs like Dell, HPE, Lenovo, and Supermicro. It is designed for data center architects, engineers, and IT decision-makers who need to identify and compare server platforms that support CXL 1.1 and CXL 2.0 for memory expansion and pooling. The tables below offer a direct comparison of server models, supported CPUs, CXL versions, and compatible CXL device form factors. The goal is to cut through the noise of announcements and roadmaps to provide a clear view of what you can deploy today.

Your Personal Codespace: Self-Host VS Code on Any Server

GitHub Codespaces and other cloud IDEs have revolutionized development, offering a complete VS Code environment that runs on a remote server and is accessible from any browser. It’s a game-changer for productivity and flexibility.

But what if you could have that same powerful, seamless experience on your own terms?

This guide will show you how to build your very own private Codespace, replicating the convenience of the GitHub experience on any server you control—be it a machine in your home lab, a dedicated server, or a budget-friendly cloud VM. We’ll explore two distinct paths to get you up and running with a persistent, browser-based VS Code instance on Ubuntu 24.04, complete with AI assistants like Gemini and GitHub Copilot to boost your workflow.

Unlock Your CXL Memory: How to Switch from NUMA (System-RAM) to Direct Access (DAX) Mode

As a Linux System Administrator working with Compute Express Link (CXL) memory devices, you should be aware that as of Linux Kernel 6.3, Type 3 CXL.mem devices are now automatically brought online as memory-only NUMA nodes. While this can be beneficial for most situations, it might not be ideal if your application is designed to directly manage the CXL memory as a DAX (Direct Access) device using mmap().

This blog post will explain this behavior and provide a step-by-step guide on how to convert a CXL memory device from a memory-only NUMA node back to DAX mode, allowing applications to mmap the underlying /dev/daxX.Y device. We’ll also cover troubleshooting steps if the memory is actively in use by the kernel or other processes.