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hardware by checking the availability of drivers before purchasing, and by staying away from the manufacturers who do not publish engineering specifications for their products.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.)
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.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide