Programming Persistent Memory: A Comprehensive Guide for Developers Book

Programming Persistent Memory: A Comprehensive Guide for Developers Book

After many months of hard work by everyone involved, I’m very pleased to announce that the book “Programming Persistent Memory: A Comprehensive Guide for Developers” is now available for download in digital PDF & ePUB formats from https://pmem.io/book , and Kindle & paperback through Amazon .

Beginner and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times―a huge leap forward in byte-addressable capacity compared with current DRAM offerings.
This revolutionary new technology gives applications significant performance and capacity improvements over existing technologies. It requires a new way of thinking and developing, which makes this highly disruptive to the IT/computing industry. The full spectrum of industry sectors that will benefit from this technology include, but are not limited to, in-memory and traditional databases, AI, analytics, HPC, virtualization, and big data.   
Programming Persistent Memory describes the technology and why it is exciting the industry. It covers the operating system and hardware requirements as well as how to create development environments using emulated or real persistent memory hardware. The book explains fundamental concepts; provides an introduction to persistent memory programming APIs for C, C++, JavaScript, and other languages; discusses RMDA with persistent memory; reviews security features; and presents many examples. Source code and examples that you can run on your own systems are included.
What You’ll Learn
- Understand what persistent memory is, what it does, and the value it brings to the industry
- Become familiar with the operating system and hardware requirements to use persistent memory
- Know the fundamentals of persistent memory programming: why it is different from current programming methods, and what developers need to keep in mind when programming for persistence
- Look at persistent memory application development by example using the Persistent Memory Development Kit (PMDK)
- Design and optimize data structures for persistent memory
- Study how real-world applications are modified to leverage persistent memory
- Utilize the tools available for persistent memory programming, application performance profiling, and debugging
Who This Book Is For
C, C++, Java, and Python developers, but will also be useful to software, cloud, and hardware architects across a broad spectrum of sectors, including cloud service providers, independent software vendors, high performance compute, artificial intelligence, data analytics, big data, etc. 

Source Code

The book uses code examples extensively through many of the chapters to explain how the Persistent Memory Developer Kit (PMDK) library works and how to use it. The code that accompanies the book can be found at https://github.com/pmem/book .

Getting Help

To ask questions pertaining to the book, its code, PMDK, or persistent memory in general, go to https://groups.google.com/g/pmem . You can also join the #pmem Slack channel .

How to Boot Linux from Intel® Optane™  Persistent Memory

How to Boot Linux from Intel® Optane™ Persistent Memory

Introduction

In this article, I will demonstrate how to configure a system with Intel Optane Persistent Memory (PMem) and use part of the PMem as a boot device. This little known feature can reduce boot times for those that need it.

The basic steps include:

  • Configure the Persistent Memory in AppDirect Interleaved

  • Create two small SECTOR namespaces, one per Region

  • Install the OS and select one or both of the namespaces (single disk install, or mirrored LVM)

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

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.

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Using ltrace to see what ipmctl and ndctl are doing

Occasionally, it is necessary to debug commands that are slow. Or you may simply be interested in learning how the tools work. While there are many strategies, here are some simple methods that show code flow and timing information.

To show a high-level view of where the time is being spent within libipmctl, use:

# ltrace -c -o ltrace_library_count.out -l '*ipmctl*' ipmctl show -memoryresources

To show a high-level view of where the time is being spent within libndctl, use:

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