Design-flow discontinuities are becoming increasingly disruptive and expensive. How is MathWorks combating this?
It is true that as system designs get more complex, across a variety of industry segments from automotive to medical devices, the engineering teams are paying a heavy price every time they run into design flow discontinuities. Design flow discontinuities typically manifest as rework, recoding, or restarts, and increase the time and money that companies spend on product development.
For example, a system design that is originally modeled in C/C++ needs to be recoded in VHDL or Verilog for implementation in an FPGA or an ASIC.
In a typical system design flow, there are potential discontinuities between Requirements and Specifications, Specifications and System Models, and Floating Point and Fixed Point Models. System simulation models may themselves be disconnected from C/VHDL/Verilog code, prototypes, MCU/DSP/FPGA/ASIC hardware, test and measurement equipment, etc.
At a fundamental level, MathWorks has been committed to addressing all these major discontinuities through the development of a Model-Based Design methodology. Model-Based Design with MATLAB and Simulink platforms provides integration and streamlined design flow from Requirements to Executable Specifications, and connecting the various stages of the design flow, modeling, simulation, fixed point conversion, C and HDL code generation, rapid prototyping, and integration with downstream tools such as integrated design environments (IDEs), simulators, and MCU/DSP/FPGA/ASIC hardware.
By integrating the system design environment with external test and measurement equipment as well as automating the verification, validation, and test processes, Model-Based Design addresses not only design flow discontinuities but also significantly accelerates design verification as well.
Q. How have advances in solid-state power electronics enabled engineers to develop equipment that modulates and converts higher power ranges? What is MathWorks doing in the area?
A. Power electronic switching is modulated by a control system, involving both supervisory and feedback algorithms. Testing and verifying the control system on actual equipment poses risks and expense.
Finding problems in the control system during hardware testing can cause damage to prototypes and test systems and significantly delay time to market.
MathWorks offers Model-Based Design for Power Electronics Control, a solution that lets the control engineer develop the power electronics control system using desktop and real-time simulation to design and verify the control strategy. Our software can model the switching electronics and control strategy. Using desktop simulation allows developers to explore different supervisory and feedback controller configurations and introduce faults and scenarios difficult to test on hardware.
From the desktop simulation, engineers can generate code for both the control algorithms and the balance of the system (power electronics, load). Code for the controller can be ported to a real-time computer or the actual controller processor to help test the timing aspects of the controller against actual hardware or a real-time simulation of the power electronics and load. These latter aspects of simulating the power electronics and load in real-time can significantly reduce the risks and costs of testing on actual hardware, particularly in higher power equipment.
What are your future plans? Please elaborate.
One of the trends that we are going through right now is what is referred to as the ‘data deluge’, the ever increasing amount of data being generated by the billions of electronic devices around the world and that is projected to grow by orders of magnitude in the upcoming years.
The data comes from a multitude of devices generating data, from mobile device usage to sensor networks to satellite imagery and remote sensing to web traffic statistics to telemetry data in products such as aircraft, automobiles, and more and more consumer devices. However, projections show that number of engineers and scientists will grow by two orders of magnitude less than the rate of data growth.
Clearly, technology, and technical computing, will be critical to being able to analyze all of this data. At MathWorks we are committed to providing the sophisticated technical computing tools that allow engineers and scientists to mine and analyze all of this data to make inferences and drive business, scientific, and research decisions.
A related aspect is that with the advent of multi-core, GPU, cluster, and cloud computing, you have more computing power at your disposal now and MathWorks has been investing in technical computing software for 28 year and counting that allows you to take maximum advantage of all this computing hardware.
As mentioned before, the number of devices with embedded processors is increasing significantly and the market demands that these devices be more intelligent and more sophisticated, which means these devices need to have more math and algorithms on them, and that math and those algorithms need to be programmed. This translates into an explosive increase in lines of code embedded in these devices.
Further, these devices and systems are being integrated into larger ‘systems of systems’ that are even more complex systems themselves and this poses a significant challenge in terms of designing all these complex systems and writing the required software. At MathWorks, we have enabled Model-Based Design with our technology to deal with this issue over the past 20 years.
Going forward, our focus is on making it easier to simulate these large scale, complex, multi-domain systems before building hardware to enable a systematic approach to design exploration, optimization, and refinement, and further enhance the reuse of models across the development process and across organizations with capabilities for systematic verification and validation from requirements to implementation. This is consistent with, and in support of, the MathWorks mission to accelerate the pace of engineering and science.