ChessBrain: a Linux-Based Distributed Computing Experiment
Because many members of the ChessBrain community run PeerNode clients on several machines, they wanted a convenient way to monitor the status of a group of machines. The PeerNode client was modified to post SOAP requests to port 3434 so PeerNode monitor applications could listen on that port and display real-time status information. I wrote the first PeerNode monitor application, and other members submitted their own. Greg Davis and Oliver Otte both submitted Perl-based PeerNode monitors. The most popular PeerNode monitor, CBMoc, was written in Java by Kris Drent.
ChessBrain collects a great deal of data, and we're currently exploring data visualization as a way of tracking and investigating system behavior. We're adding 3-D-based game navigation tools to allow us to track network play visually. Sven Herrmann, our resident 3-D expert, has created an OpenGL-based renderer that we use in our SuperNode monitor application. We'll also use the new renderer in our next-generation screensaver program and game viewers.
Today, ChessBrain is a working prototype that plays chess using hundreds of machines running Linux, FreeBSD, Mac OS X and Microsoft Windows. It plays at international master strength, and we see many ways to continue making improvements.
ChessBrain exemplifies the use of open-source tools to solve complex problems. We're preparing ChessBrain itself for release as an open-source project, with the hope that others will join and expand the effort. The wonderful thing about ChessBrain is that there are so many ways to contribute. Anyone with a PC and Internet connection can participate. Download a PeerNode client from the ChessBrain Web site, run the software on one or more computers and help increase the size of ChessBrain.
We're currently working toward an official world record for the largest number of machines used to play a single game. We have an established contact at the World Record office in London and contacts within a number of official chess federations. The ChessBrain Project is supported by a strong core team, including Peter Wilson, the former chairman of the World Chess Federation's (FIDE) Computer Chess and Internet Committee. The ChessBrain team currently is exploring potential venues for a public and Internet-based demonstration involving a new Guinness World Record in distributed computation and chess. Check the ChessBrain site for an official announcement.
Many thanks to Janus Daniels, Cedric Griss and other ChessBrain team members for their support in the preparation of this article. For contact information and a list of who's who on ChessBrain visit, www.chessbrain.net/friends.html.
Carlos Justiniano is a 20-year veteran of the software industry. ChessBrain allows him to live several mantras: “Embrace complexity”, “Engage in nontrivial pursuits” and “Do it using open-source software”! Comments on this article can be sent to firstname.lastname@example.org.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
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