Linux in a Scientific Laboratory
Our laboratory, the NIST Center for Neutron Research (NCNR) at the National Institute of Standards and Technology, uses neutron beams to probe the structure and properties of materials. This technique is in many respects similar to its better-known relative, X-ray scattering, but offers some unique advantages for studies of materials as diverse as semiconductors, superconductors, polymers and concrete.
Our work could not be done without computer technology. Computers help us collect experimental data: they interface with the real world, controlling and recording various physical parameters such as temperature, flux and mechanical position. The collected measurements need to be displayed, analyzed and communicated to others. All these stages require sophisticated and flexible computer tools. In this article we will describe how Linux helps us solve many needs that arise in our everyday work. We believe that our experience might be typical of any scientific or engineering research and development laboratory.
The main advantage we get from using Linux is its amazing flexibility. Because of the open development model and open source code, there are no “black box” subsystems; when something doesn't work correctly, we can usually investigate the problem and fix it to our satisfaction. The significant spirit of cooperation and mutual support found in Linux is important to us—a consequence of the general philosophy of open software as well as the practical result of source code being available for anyone to fix. Also, Linux is rather robust, in the sense that once something is set up, it stays set up; Linux shows none of the brittleness that, unfortunately, we have learned to expect from mainstream computer operating systems.
Unfortunately, sometimes we run into a lack of support for some useful hardware or software. Since few manufacturers actively support Linux, the driver availability on Linux lags behind Windows 95, although it is probably better than any other environment thanks to the excellent work of many people who contribute their hardware drivers. We avoid unsupported hardware by checking the availability of drivers before purchasing, and by staying away from the manufacturers who do not publish engineering specifications for their products.
In the end, we use whichever environment does the job better. Since some tools are available on Windows and not on Linux, we sometimes use the former. For instance, the LabView software, available on Windows, is an integrated graphical tool for rapid prototyping of data acquisition, with an impressive collection of instrumentation hardware drivers. It is sometimes the platform of choice, especially for exploratory work, although it doesn't scale well for more complex tasks.
Overall, we have about 25 computers running Linux. We have been very happy with their operation and have saved taxpayers a bundle of money in the process. We have seen Linux grow from a virtual unknown, perceived as risky and devoid of support, to its current status as a serious contender with brand-name UNIX and NT boxes, and we definitely see Linux in our future.
Real-world data acquisition usually requires endlessly repeated high-precision measurements, and so it is ideally suited for a computer, as long as the data is available in computer-readable form. Unfortunately, data acquisition is not a mass-market application, so the acquisition hardware tends to be expensive and hard to obtain, even for the ubiquitous PC/x86 platform. Consider a sound card: it has high quality analog-to-digital and digital-to-analog converters, timers, wave-table memory, etc., all for around $100 US. Similar hardware with relatively small modifications to make it suitable for data acquisition will probably cost around $1000 US.
The scientific instruments we use at the NCNR are quite diverse and interesting on their own; a lot of mechanical and electronic engineering is involved even before computers get into the picture. Some of our instruments are quite impressive in size and weight—we actually use decommissioned battleship gun turret components to support them. You can get a feel for the scale of our instrumentation by looking at Figures 1 and 2; the experiment hall measures approximately 30 by 60 meters.
For the purpose of this article, let us assume all the hard work of designing and constructing an instrument has been done, including providing the appropriate sensors that measure the interesting physical quantities such as temperature, radiation intensity or position. Our task is to read data from these sensors into the computer. (Because of concerns for cost and availability of hardware, PC/x86 platform is the practical choice for data acquisition tasks.)
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.
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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:
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- Next winner announced on 5-27-13!
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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?
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