The software simulation configuration discussed in this article was a Bombardier/Canadair Regional Jet RJ-200 aircraft (Figure 9), a successful 50-seat twin jet regional aircraft manufactured and built by Bombardier Aerospace in Montréal and popular with airlines such as Comair, Skywest and Air Canada, just to name a few. The first task at hand for CAE engineers was to port the entire CAELIB and SIMEX software environment to Linux. This proved to be a relatively uncomplicated task for our operating system support group (OSU), since most of our code is in ANSI C. All modules were compiled with relatively minor modifications. Once this was done, the task of transferring and porting the entire software simulation code from SIMEX to Linux proved to be more challenging. Now, I am referring to years of software development on AIX with at least 500 software modules, each ranging from 1,000 to over 100,000 lines of code—the porting of which would be no trivial matter. The third task was to port the required CAE-specific compilers from our own OpenGL-based graphics compiler and editor to our basic support utilities. CAE has developed its own graphical environment called TIGERS (an OpenGL-based system).
At the time TIGERS was developed at CAE, sophisticated graphic systems for simulation use were not yet commonplace. Figures 10, 11, 12, 13 and 14 show the level of graphical detail required for CATS simulation. The main difference between a CATS and a full-flight simulator is simple: CATS requires that all aircraft panels be a graphical representation, as opposed to the hardware-driven interface on a full-flight simulator. Simply put, a graphical representation of a switch is used instead of a real switch in a cockpit environment. In all respects, the amount of simulation software required is much more complex on a CATS as opposed to a real full-flight simulator. All aircraft systems are simulated in the CATS environment, instead of only the simulated black boxes of the full-flight simulator. In flight simulators, we simulate the same black boxes as used on the aircraft. In trying to address the needs of a Bombardier's training department as they sought a portable version of their existing AIX CATS on the PC platform, CAE engineering decided Linux would be the ideal and practical choice for this project.
We made the decision to use the standard GNU ANSI C compiler and F77 translator for the task. Our FORTRAN77 legacy software modules proved to be the greatest challenge. AIX FORTRAN77 compilers are very forgiving in equating logical to integer data types. For example, if you equate an integer label to a logical label, the AIX FORTRAN compiler would assume you require the value in the logical label to be stored into the integer label. This style of programming is not allowed under F77 Linux. You must declare and equate labels of the same data type, or the compilation will fail. Now, this would be a simple task if the labels were defined in the local module. The problem arises when the software module in question uses a logical label declared in what we call our CDB (common data block) as an integer label. This common data block is used to declare all global labels used by every simulation module to pass variables among each other. If the declaration is wrong in the CDB, a correction must be made in all modules. Then each module must be reprocessed with the new CDB and recompiled.
The next problem lies with the memory storage format of logical labels between AIX and Linux. For example, a data type of Logical*4 (four bytes) in F77 Linux is stored from left to right (MSB, most significant bit, to LSB, least significant bit) while AIX stores the logical in reverse order (LSB to MSB). This can create a major problem when using the logical in a bit manipulation operation. If you use each bit for a different function in your code and apply a bit manipulation operation (e.g., FECDE .XOR. Logical Label), then the problems are compounded. You must reverse all masks used in the bit manipulation operation—a considerable amount of work.
Another area of concern is the data files used to store navigation and engine data interpolation information. The byte order in these data files must also be reversed to read data correctly into their assigned CDB labels. Our ANSI C code does not have this problem. Most of the C code compiled with relatively little change.
Aural warning system conversation required a minor amount of work. Under AIX, all audio warnings were designed to work with a DSP card with one large digital audio file. We were required to convert the large digital aural warnings data files into separate PCM wave files. A newly coded audio software module was then needed to cross-index the requested aural warnings to their corresponding wave file and pipe them to a standard SoundBlaster audio card. Throw in all the graphics files and IOS pages (Instructor Operator System Pages, Figure 15), and we have an enormous porting task.
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