How To Make Virtual Prototyping Better Than Designing With Hardware

Synopsys’ hybrid prototyping solution integrates Virtualizer with a Synopsys HAPS FPGA-based ASIC prototyping system. The combination provides several benefits to the virtual prototype user including reduced modeling effort by integrating existing RTL blocks and more accurate prototypes that include high-fidelity real-world I/Os. With respect to the “it’s not real hardware” argument, the first virtual prototype was easier to accept when management could touch and feel a real product that had been developed in the environment. Virtual prototypes eliminate these errors, but are subject to accuracy issues where the model does not match the silicon behavior. This is often the result of creating the model from the specification, rather than a detailed gate or register transfer level. The simulation essentially contains a FAE in the box which constantly checks the software execution for correct interaction with the hardware design.

The simulation of manufacturing processes has many economic repercussions for manufacturing companies, from the increase in quality to the reduction of time to market (time-to-market). The key demonstration, however, was an interactive GUI that could induce a car rollover event in a similar way as a scaled car model containing the same firmware in an actual product. The pilot project success overcame the inhibition that “virtual hardware” was “pretend hardware”. Unfortunately, model development is often not planned or requested until a silicon error impedes firmware development.

Thus, having accurate model of microcontroller and ASICs particularly a rich set of assert/constraint checks on access, usage, etc. is an extremely valuable tool for achieving ZERO defects in software. Frequently, the issue of accuracy is really one of ambiguity where the silicon designer and the model designer simply interpreted the written specification differently. In most situations, investigation of the problem leads to a model correction to ensure compliance with the silicon. The VP accurately models interrupts and interrupt priorities, and because of the deterministic nature of simulation, a symptom is often repeatable in the VP but may be elusive on actual hardware. In this particular case, the thermal design of the package only allowed for short duration current measurements on a single output driver at a one time. The model for this particular ASIC is built in a way that if the duration is exceeded or the number of measured channels is exceeded, a warning message is displayed to the software developer.

Without the aid of the warnings, the author may unknowingly violate requirements, potentially resulting in a quality or field return issue. This message alerts the software engineer of the specification violation. This system problem due to the specification violation could easily remain latent in normal product development.

Just as model-based design has been used in other disciplines to test systems that are unsafe, or cost prohibitive, VPs allow this type of testing to be applied to embedded control systems. See how these tools can help you improve the efficiency and performance of your machine design and lower the cost and risk of your development. I was able to create different test cases which were difficult to do in bench and test cases were repeatable.

Reduces the time-to-market and used from the planning gets eliminate bottlenecks in production. While there is no known silicon issue with the current micro, there’s no guarantee that there wouldn’t be an issue with future MCU silicon had the same access method been used. Losing sight of the speed goal, even on part of a project, can cost the entire use of the VP. Even the best modeling practices cannot overcome a slow computer, thus the use of modern, off the shelf PCs, ($1000) is strongly encouraged.

Simulation And Prototyping Of A Two

But every simulation tool user knows that simulation models are not perfect and thus the simulation has some limitations. “It works in simulation” doesn’t mean “it will work in the real world” ! At the end, only real world testing, at different temperature, load, batches of critical components, etc is able to validate the design against its spec. Firmware was then integrated into the physical controller in the last week of the schedule. Executing the firmware on the actual hardware uncovered one additional error due to a hardware model error.

The views, opinions and technical analyses presented here are those of the author or advertiser, and are not necessarily those of ULProspector.com or UL. The appearance of this content in the UL Prospector Knowledge Center does not constitute an endorsement by UL or its affiliates. Welcome to the blog for UL Prospector, the most comprehensive raw material search engine for product developers. Synopsys helps you protect your bottom line by building trust in your software—at the speed your business demands.

Virtual Prototyping Use Cases

But I wouldn’t trust sims as much if I was doing more RF, at least not Spice sims.

Regardless of whether you have a physical prototype or simulation-based proof of concept, there is data analysis to then be covered. The difference is only from where the data come — physical testing or virtual, simulation-based testing. Draw this information from the prototype-stage verification table, updated to reflect what actually happened.

To achieve 10% to 50% of real product execution speed, the choice of model abstraction level is of higher importance than the choice of modeling language. The abstraction level choice is unfortunately beyond the scope of this paper, but the modeling team should always consider simulation speed as a top goal while building the models. In nearly all of these cases the illegal access had escaped other forms of checking such as code review, static analysis , and bench testing. Lint tools do not have built in knowledge of the hardware memory map and bench testing often did not reveal the issue because of the benign or hidden symptoms.

Creating models with an appropriate amount of detail, yet retaining significant simulation speed, is a difficult problem that the modeling team must address. Generally, software developers require at least 10% of the real product speed in the simulations. For some projects, though very rare (e.g., very large-scale systems), the prototype is a high-fidelity virtual-world prototype in the absence of a physical-world prototype.

Verification Email Sent

“Timer capture mode should only be modified when the timer is disabled.” Assumptions about how the IC is utilized in the system are eliminated under this scenario, resulting in adherence to the specification throughout the development process. Internal to physical EEPROM/Flash devices, high voltages supply the internal memory cells during write sequences. During the several millisecond write state, data reads are not electrically possible.

• But it’s pretty much always accompanied by bench testing and looking at real measurements.
• For one particular airbag controller project, the engineering team implemented a daily execution of 14 scripts on two different ECU configurations.
• A simulation of an OPAMP negative feedback might tell you that you have a phase margin of 60°.
• Of that quarter requiring another iteration, 90% of the modifications required could have retrospectively been found with more extensive simulation.
• Regardless of whether you have a physical prototype or simulation-based proof of concept, there is data analysis to then be covered.
• In one example, the addition of a new interrupt to the system resulted in a second undefined interrupt problem.
• It also increases the quality of the tools and allows the optimization of the manufacturing process.

Just like static analysis tools, too many or too frequent messages cause the software developer to de-sensitize and miss underlying problems. The errors found are often complex, subtle driver-related initialization order or MCU specification violations. Several studies on software dependability report fault densities of 2 to 75 bugs per 1000 lines of executable code.

The software developer thus benefits as if an omnipotent field application engineer for the device were watching the code development. See more advanced motion control programming techniques, including blended moves, electronic gearing, camming, and 3D motion control functions. Calculate motor sizing requirements and analyze machine performance parameters such as cycle time and throughput. Then easily deploy your application to NI CompactRIO to control the physical machine.

Should I Invest In Simulation Process Data Management Spdm?

Drivers, which typically comprise 70% of the operating system code, have a reported error rate that is 3 to 7 times higher. Allowing engineers and verification personnel to run experiments in the virtual environment before committing to the physical product saves money and increases safety. Developers can then be assured the design will work prior committing to a real physical product. In this subsection, in words and with complementary annotated graphics, describe all refinements made and the reason for making them. You should consider a refinement anything changed after it had been realized in full system-level prototype form (beyond function-level concept MIP or physical feasibility trials). This means, generally, anything made and then re-made/modified after about week 5 of Term-II.

A simulation of an OPAMP negative feedback might tell you that you have a phase margin of 60°. Nice, but that simulation doesn’t tell you what the real phase margin will be. The only thing you can conclude is that your system is very likely to be stable because you have a big simulation margin and if the model is not very poor, it should agree with the real thing somehow.

Multibody Dynamics Integrated With Simulation Process And Data Management

Synopsys is a leading provider of electronic design automation solutions and services. Making statements based on opinion; back them up with references or personal experience. As you won’t use the general relativity to solve for the motion of an apple falling down a tree. Even if you https://globalcloudteam.com/ know that Newton’s laws of motions are a just a special case that works well only in specific conditions and if theses specific conditions are met, go for Newton ! Another aspect is the speed at which you can adjust and try new things, without creating a new prototype at every step.

Nonetheless, they are still subject to measurement and emulation errors induced by intrusive debug, in-circuit emulators and instrumentation cable impedances. In the context of this article, acceptability is the notion that the virtual prototype must be generally accepted for non-technical as well as technical reasons. Software developer productivity-increases due to visibility, controllability and improved quality are often intangible to decision makers. In one example, the parameters for the write/program operation time were set to the specification limits for the EEPROM device model in order to verify the corner cases. The firmware caused unanticipated retry loops which cascaded to COP timeout and reset of the system.

To Comment Or Not To Comment Code?

Of course, if you did not manufacture a prototype, then your refinements to your design as described here are simulation-driven. Explore the basic programming techniques needed to control your SolidWorks assembly using industrial grade motion control software. Learn to execute precise 2D motion trajectories by exploring the NI SoftMotion functions for straight line, arc, and contour moves and more. Deploy and run your simulation using LabVIEW and visualize the motion path in SolidWorks. I do find them useful, especially when some degree of component tweaking in a filter circuit is needed. But it’s pretty much always accompanied by bench testing and looking at real measurements.

Rapid Prototyping

Testing and development of a product requires putting the product through possible failure modes. To refine model design, validate component functionality, evaluate system performance, and test hardware, use rapid prototyping. Run real-time, external mode simulations that enable you to monitor signals and tune model parameters in your target application.

Even though physical prototypes were available there was no easy to way automate running test cases on them. Test examples include accelerometer and input sensor data filtering, deployment loop configuration and activation, event recording, serial EEPROM read/write, and manufacturing diagnostics. The productivity of the team was accelerated because each team member could run tests prior to and after a firmware change and did not need to be an expert in all areas of the ECU. Describe in words any differences between the intended manufacturing for which you designed and the actual methods used in your prototyping that took place .

Account Activated

This should account for any learning that took place through the prototyping process. My sentiment is also that sims have replaced 90% of bench tests for me. But, simulation is not something meant to replace real world testing.

I fully agree on the essence that more simulation brings me to working circuits faster. I simulate, then select components, simulate again because components force compromises, layout, simulate again with approximate parasitics, maybe tune values. I prototype of a website feel that bench work has been easily one of the most enriching aspects of my development as an engineer. Even the simplest seeming circuits can have unexpected “features” and one can learn valuable lessons from figuring out what is going on and why.

Unlike that table, to avoid repetition, do not present this section on a requirement-by-requirement basis (since often times there are multiple requirements verified by a single test/method). Though, each method noted should indicate by naming all the requirements it serves to verify. The only cost effective path forward for this level of development is virtual prototypes and the engineering value of the VP continues to be high even after the hardware becomes available.