Algorithm engineering is a term coined for applied algorithm design. It refers to the process of transforming a pencil-and-paper algorithm into a robust, well-tested, and easy-to-use implementation. Implementing an algorithm to provide desired functionality in a prototype can be the most challenging part of the whole product development life cycle, but it also has the potential to be the most rewarding. By applying real-world I/O, you can see the functionality of your algorithm come to life before your eyes.
Implementing algorithms in a functional prototype can be difficult for a variety of reasons:
Programming limitations—Often control systems or processors that are chosen for their I/O capabilities, such as FPGAs, involve programming limitations for a developer. Programming for different platforms usually requires programming knowledge that few system-level designers have.
Basic algorithm implementation—Implementing low-level algorithms for basic functionality takes time. Speed is paramount in prototyping, and designers often cannot afford to get bogged down in implementing a well-known algorithm from scratch due to the lack of existing code.
Reworking algorithms for multiple platforms—As the functional prototype evolves, algorithms often have to be revisited to port them to a different type of system. Code is rarely functional between different run-time environments, and that makes scaling an application from prototyping to deployment difficult.
Test and verification—You usually don’t know for sure whether a system can meet functional requirements until late in the game, and starting over costs too much. For example, the processor may not be able to perform the required number of parallel tasks fast enough. It may not be able to achieve an adequate cycle time. It also may not be able to handle the processor-intensive analysis in real time.
LabVIEW graphical system design addresses and mitigates many of the potential pitfalls involved in engineering algorithms for a functional prototype. Graphical system design is an approach to solving design challenges that blends intuitive graphical programming and flexible commercial off-the-shelf (COTS) hardware. With this approach, you can use a single environment across all stages of design. Now take a more in-depth look at how this approach specifically addresses the challenges raised above.
Multiple Models of Computation
One of the virtues of graphical system design is that it gives programmers the ability to create their algorithms regardless of the model of computation (MoC) they are implemented with. As code complexity for algorithms continues to grow, programmers have to use different MoCs to expand their coding capabilities. The following are just a few MoCs you can use with graphical system design:
Data flow—Data flow is the MoC most often associated with LabVIEW software. With data flow, operations require the developer to insert data in all the inputs before it executes. Data flow is an intuitive coding structure that makes implementing applications such as parallel processes easy.
Textual math—Textual math is another tool for creating complex functions easily. Text-based math is a human-readable implementation of often complex algorithms that are easier to write in a script description form. Examples of textual math are the formula node and LabVIEW MathScript RT Module. With LabVIEW MathScript, you can choose the most effective syntax for algorithm development, whether you are developing algorithms, exploring signal processing concepts, or analyzing results.
Figure 8. Reusing Text-Based Code With the LabVIEW MathScript RT Module
C code—Sometimes the algorithm you use was originally created in C or C++. In this case, you no longer have to discard the previous work. You can instead use the Inline C Node or the Call Library Function Node to directly call your previous code within LabVIEW. Use the Inline C Node for preexisting C code or implementing a small numeric or array algorithms and use the Call Library Function Node to access C code in DLLs or shared libraries.
Open Software Architecture
Over the years, the LabVIEW platform has seen wide-scale adoption in numerous design disciplines, which has led to a need to incorporate data with different design and simulation tools. LabVIEW accomplishes this intercompatibility with numerous integration tools, libraries, and file formats. LabVIEW also offers standard integration with a large array of other software tools and measurement resources including the following:
- DLLs, shared libraries
- ActiveX, COM, .NET (Microsoft)
- DDE, TCP/IP, UDP, Ethernet, Bluetooth
- CAN, DeviceNet, Modbus, OPC
- USB, IEEE 1394, RS232/485, GPIB
- Databases (ADO, SQL, and so on)
Using these tools, integration with data from almost every kind of measurement and control device is possible. By combining LabVIEW with general-purpose standards for hardware communication, developers can ensure compatibility and scalability for many years in the future.
The LabVIEW Approach
The hundreds of functions in LabVIEW that cover a wide variety of traditional algorithms in math, signal processing, probability, and control are essential building blocks for any custom algorithm. These functions alleviate the burden of writing low-level code and give engineers the time to focus on a solution instead of implementation.
Because using LabVIEW makes acquiring real-world data so easy, engineers find it valuable to test their algorithms with actual data as an iterative approach to tuning them. With this interactive test approach, you can experiment with different functions to see if they provide the required expected result. For example, when processing a signal with a filter, you can select from a wide variety of solutions, acquire the actual signal that you need, and look at the results in either a graph or file. If the results are not suitable for the application, then you can select another filter. Often it is easier to acquire the actual signal to apply to an algorithm and then take the time to simulate it on software.
Figure 9. NI ships LabVIEW with hundreds of built-in algorithms that you can use in your prototype.