Linux Journal Contents #175, November 2008
Linux Journal Issue #175/November 2008
There aren't many numbers that put the US national debt to shame, but here's one: 1,100,000,000,000,000. What's that? That's how many floating-point operations per second the Roadrunner supercomputer at Las Alamos can perform. That's about 100 FLOPS per dollar of US debt (unfortunately, the debt is winning the second derivative race). Read the article about Roadrunner in this month's High Performance Computing issue of LJ. Along with that, find out how to program the Cell processor and how to use CUDA with your NVIDIA GPU. Also in this issue: Mr HandS (aka Kyle Rankin) gives us a few tips on using Compiz, Chef Marcel shows you how to get blogging off your plate quicker, Mick Bauer talks about Samba security, Dan Sawyer interviews Cory Doctrow and Doc talks about how information technology can affect democracy and fix the national debt (just kidding about that last part). That and more for your reading pleasure in this month's Linux Journal.
Features
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The Roadrunner Supercomputer: a Petaflop's No Problem
by James Gray
IBM and Los Alamos National Lab teamed up to build the world's fastest supercomputer.
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Massively Parallel Linux Laptops, Workstations and Clusters with CUDA
by Robert Farber
Unleash the GPU within!
-
Increase Performance, Reliability and Capacity with Software RAID
by Will Reese
Put those extra hard drives to work.
-
Overcoming the Challenges of Developing Applications for the Cell Processor
by Chris Gottbrath
Introducing techniques for troubleshooting programs written for the Cell processor.
Indepth
-
Cory Doctorow—Linux Guru?
by Dan Sawyer
Cory Doctorow on DRM, his new novel and more.
-
How We Should Program GPGPUs
by Michael Wolfe
Porting to GPUs without heroic programming effort.
-
Use Python for Scientific Computing
by Joey Bernard
Leverage the benefits of Python for scientific computing.
Columns
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Shawn Powers' Current_Issue.tar.gz
Sometimes, Fast Just Isn't Enough
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Reuven M. Lerner's At the Forge
Book Roundup
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Marcel Gagné's Cooking with Linux
Warp-Speed Blogging
-
Dave Taylor's Work the Shell
Pushing Your Message Out to Twitter
-
Mick Bauer's Paranoid Penguin
Samba Security, Part I
by Mick Bauer
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Kyle Rankin's Hack and /
Memories of the Way Windows Were
-
Doc Searls' EOF
Lincoln and Whitman's Unfinished Business
Reviews
-
Tracking Your Business Finances with NolaPro
by Mike Diehl
-
The Popcorn Hour A-100
by Daniel Bartholomew
In Every Issue
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| Designing Electronics with Linux | May 22, 2013 |
| Dynamic DNS—an Object Lesson in Problem Solving | May 21, 2013 |
| Using Salt Stack and Vagrant for Drupal Development | May 20, 2013 |
| Making Linux and Android Get Along (It's Not as Hard as It Sounds) | May 16, 2013 |
| Drupal Is a Framework: Why Everyone Needs to Understand This | May 15, 2013 |
| Home, My Backup Data Center | May 13, 2013 |
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- Making Linux and Android Get Along (It's Not as Hard as It Sounds)
Enter to Win an Adafruit Pi Cobbler Breakout Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Pi Cobbler Breakout Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- 5-21-13, Prototyping Pi Plate Kit: Philip Kirby
- Next winner announced on 5-27-13!
Featured Jobs
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Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?




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