• Linux VM 2.4 architecture in depth-with diagrams and call graphs
• Physical memory description, page tables, address spaces, and memory allocation
• High memory, swapping, shared memory, and much more
• Expert guidance for analyzing the code of any open source project
• New Linux 2.6 kernel features in every chapter

CD-ROM INCLUDED

Complete VM Learning Lab! Contains the author's new toolkit for exploring VM, including a browsable version of kernel source, CodeViz call graph generator; and VMRegress for analyzing and benchmarking VM. Also includes all code commentary in HTML, PDF, and plain text formats.

About The Author


MEL GORMAN specializes in documenting open source software. He holds a MSc in Computer Science from the University of Limerick, Ireland, and has served as an instructor there. He has worked as a system administrator, applications developer, and consultant, and has been researching Linux memory management for more than two years. Currently he is an applications developer with J2EE technologies at IBM, Dublin.

Customer Reviews & Comments
A slightly unusual book from Prentice-Hall. If you peruse a list of their recent offerings, this book stands out as rather more specialised. Certainly, in general there is no shortage of linux books, from a variety of publishers. But typically such books are aimed at using linux or they describe applications built atop it. Whereas the technical ability and interest in actually understanding and changing any operating system (not just linux) acts as a tremendous barrier. Hence, the potential audience for Gorman's book is quite exclusive. An upside is that it reduces the potential competition from other authors and publishers. Gorman is attempting an outreach to potential linux developers. The book has two parts. The first explains key concepts for the VMM. He quickly gets into the issues, with little preamble. In other words, you need at a minimum to be fluent in C, and have some acquaintance with the ideas of memory management, though not necessarily with linux. Each algorithm in this book is not that intricate. As a rough guide to difficulty level, if you can understand a typical algorithm from the texts by Knuth or Aho or Sedgewick, then you should not have any trouble here. The second part of the book has code listings with accompanying detailed commentary. This is different from, and substantially improves upon the inline comments, which are sparse to non-existent in the exampled code. To some of you who want to try changing code, the second part's annotations may be the crucial portions of the book. It is rare to see such extensive commentary of source code in book form. Comment | Permalink | (Report this)