🔧 Optimizing Verification Workflow with Portable Test and Stimulus Standard (PSS): Best Practices
Nachrichtenbereich: 🔧 Programmierung
🔗 Quelle: dev.to
The semiconductor industry now faces challenges like delivering reliable, high-performance designs with the reduced time-to-market. Verification is an important step that ensures a design meets up to its required functional and performance specifications. Traditional methods of verification are unable to cope with the complexities of semiconductor designs and, hence, are creating inevitable bottlenecks in the development process.
The PSS has become the game-changing methodology since it offers an efficient approach to generating reusable test scenarios across different platforms. PSS therefore accelerates verification by providing higher levels of automation, reuse, and portability. Still, like any other tool or methodology, its power is unleashed only when applied correctly.
Within this blog we will cover how you can optimize your verification flow using PSS. We will dedicate some best practices so PSS can be adopted efficiently and scalably, thus helping to streamline your verification efforts, improve functional coverage, and hence get your design to market faster.
I. Understanding the PSS Workflow
To fully optimize your verification workflow using PSS, one needs to understand what the key stages involve. PSS is an upgrade to a traditional verification flow that allows it to be portable and reusable during test case generation, model creation, and execution across platforms. Let's walk through each stage of a typical verification workflow in PSS.
A. Test Case Generation
Any verification activity starts by generating different and robust test cases. Generating test cases the traditional way is a time-consuming process with a high likelihood of errors, primarily if a user begins to create scenarios for various platforms or use cases manually.
In PSS, test cases are automatically generated from high-level models. These models define a wide set of functional and performance behaviors. It is thus easy to generate tests for various scenarios, corner cases, and conditions. The key benefit here again is the portability of the approach - once a model is defined, the same test cases can be reused with various platforms, such as simulation, emulation, and post-silicon environments.
B. Model Creation
PSS models describe the system under test and encapsulate the components, actions, and constraints in a test. They are written at a level of abstraction that makes it easy to reuse them across projects and adapt them to different platforms.
In model development, engineers typically identify:
- Components: These comprise the hardware or software entities to be tested.
- Actions: These are operations performed by, or on, components.
- Constraints: The conditions under which some actions can be performed.
These are models reusable across scenarios and configurations, making sure not to duplicate work and that testing remains consistent. Engineers could scale their verification efforts from this.
C. Stimulus and Scenario Development
After the model is created, it is followed by stimulus and scenario configurations that describe how tests are to be actually executed. PSS makes available a well-structured approach to define what stimuli must be used so that all the possible use cases and their respective edge conditions are also considered.
PSS offers the ability to randomize and, for constraint-based stimulus generation, to exercise a broad range of scenarios without having to write each and every test by hand. It thus ensures the coverage of even unlikely or infrequent conditions and thereby improves test coverage decisively.
D. Execution and Results Analysis
As soon as the test scenarios are produced, execute them and then analyze the output. PSS lets tests be executed very smoothly on various verification platforms like simulators, emulators, and real hardware without writing down test cases for every environment.
Actually, this is where the portability of PSS really shines - engineers can create test cases in simulation and reuse the same tests in post-silicon environments. Maintaining consistency across platforms reduces duplication of effort and minimizes the risk of discrepancies between different stages of verification.
II. Best Practices for Maximizing PSS Workflow
Optimization of the workflow using PSS unlocks huge efficiencies in semiconductor verification that then translate into faster time to market as well as stronger designs. Below are best practices that ensure you get the most out of PSS.
A. Early Integration of PSS in the Design Flow
Indeed, early use of PSS in the design and verification cycle improves the overall flow of it. This is because test models and test scenarios can be defined from the start, problems are tackled proactively in the design, and hardware and software verification gets initiated at the same time, day one.
- Advantages: Early integration will begin to catch problems at the right time before it becomes expensive to fix. In addition, by setting up reusable test scenarios early, teams can be assured that the design will pick both functional and non-functional aspects that had been appropriately tested at all stages through the development cycle.
B. Modular and Reusable PSS Models
One of the major strengths of PSS is in modular, reusable components. The modular aspect of PSS models allows teams to encapsulate complex systems into smaller, reusable pieces that might then be combined or extended to generate a wide variety of test scenarios across multiple projects and platforms.
- Utility: Modular PSS models save time and efforts by not requiring people to rewrite the test code based on various configurations that would be required if they didn't need to. Moreover, it makes the process absolutely scalable because teams can simply recycle verified modules in new designs without much change. In addition, this approach simplifies collaboration since different teams can contribute reusable components to a common repository.
C. Automation of Test Scenarios
PSS excels in the field of automatically generating test scenarios. PSS can automatically produce many test cases that utilize constraint-driven randomization which goes beyond even the most elongated conditions and corner cases which are practically possible by developing tests by hand.
- Benefits: Automation reduces the use of manual interventions to near zero, which means that test cycle time goes down and test coverage increases simultaneously. It is quicker to find an edge case, hence having a stronger verification. This way, through rapid iteration over generations of test scenarios, teams get more time for analysis of results rather than writing new tests.
D. Cross-platform Consistency
In fact, one of the very important advantages of PSS is its portability across verification environments whether it is simulation, emulation or post-silicon testing. In fact, cross-platform consistency is of paramount importance for a smooth and efficient verification process.
- Consistency: PSS tests are created once and can then be applied to multiple environments without needing any adjustments. This means that the same test cases will run at maximum consistency hence having no discrepancies of different iterations since the test is being rewritten for a different environment. This helps with fast transition from one developmental stage to another, and verification is now efficient.
E. Correct Debugging and Maintenance
If the designs become big and the system intricate, maintenance and debugging PSS models will be too complex. This is one reason model readability has to be made easier and debugging more straightforward as part of workflow simplification.
a. Maintenance Tips:
- Read-able Models: PSS models must be in plain and modular forms by appropriate uses of meaningful names of the components and actions. Thus, a team can quickly understand and maintain the model over time.
- Version Control: A version control system is coupled with documentation such that any changes into PSS models are well-documented and traceable back in the event of any problems.
- Debugging: Make use of PSS tools that offer high power debug functionality and include visualization of generation flows for tests and coverage of scenarios. This makes the problem identification of failures and correction of faults more manageable.
Using these best practices, teams can then leverage the benefits of PSS, including higher productivity, higher test coverage, and faster execution times. But much more than this, it is an approach that not only optimizes verification but positions your team better to face the growing semantic complexity of semiconductor design.
III. Overcoming Common Challenges in PSS Workflow Optimization
Although PSS has much promise for verification, it is indeed very difficult to bring it into real-world usage. Let's learn how a semiconductor team had to grapple with their woes in optimizing the verification process with the usage of PSS in this real-life experience.
A. Challenge 1: Complexity in Initial Model Creation
One of the first major challenges was how to deal with complexity in building correct and reusable models after the team adopted PSS. It takes quite a good amount of time to build models from scratch for such large and very complex SoCs that would require deep expertise.
a. How to Overcome It:
The team can ease this challenge by breaking up the task of modeling into a phased approach. Instead of starting with the attempt to model the whole system in one shot, the team would start with smaller, critical parts, such as processor and memory controllers. These were the high-priority areas that had the greatest impact on functionality. Breaking the SoC down into manageable modules in this way will help to work up modular models over time that can then be mixed and matched accordingly.
This phased development approach would allow the workload to be divided in such a way that verification engineers were building confidence in their understanding of PSS before embarking on the more challenging sections. Additionally, the team could assure themselves that every model was heavily documented and modular, making easy updation or repurposing whenever the design evolved.
B. Challenge 2: PSS and Integrating with Legacy Systems So Far
Semiconductor companies had already invested heavily in legacy verification systems and environments, and one of their major concerns was going to be integrating PSS into an existing workflow. They needed to ensure that PSS-based tests worked properly side by side with their established methods without disruption and a delay.
a. How To Overcome It:
To address this, the team can follow a hybrid approach wherein PSS can be applied parallel to the existing testbenches. Here, instead of replacing everything at once, the team can use PSS to generate some portion of the test cases while continuing to run legacy tests in other parts of the system. This would let the team gradually move to PSS without risking either verification coverage or productivity.
With time, as the confidence in PSS models increases, the team will start phasing out their legacy tests and begin to fully adopt to PSS for their verification efforts. This hybrid approach not only minimizes disruption but also gives the team a chance to compare the effectiveness of tests generated by PSS with traditional methods, ultimately proving that PSS is superior in terms of coverage and efficiency.
C. Challenge 3: Debugging PSS Models Across Platforms
Yet another key challenge is debugging of PSS models in case of failures observed against different verification platforms like simulation and post-silicon validation. Indeed, PSS provided excellent test portability, but close cooperation is necessary for diagnosing an issue that manifested only in a given environment-for instance, in hardware but not simulation.
a. How To Overcome It:
To address this issue, the PSS models must use platform-specific logging and monitoring. These tools can easily identify the conditions under which failures occur with a good degree of granularity and can be very useful when trying to correlate issues on different platforms. For example, if a test passes in simulation but fails in hardware, logs help identify particular constraints or scenarios causing the failure.
Also, modular debugging must be used. Break the tests into pieces of smaller, isolated parts so that only the exact parts of a test run on each platform. This really helps with the localizing process as it not only helps narrow down where the problem is but also what location it is at. The other aspect is continuous collaboration between the hardware and verification teams. The data of both parties will yield combined insights into speeding up the root cause analysis and a more efficient resolution of cross-platform failures.
D. Challenge: Skill Gap and Team Adaptation
Although PSS can bring along so many benefits, adopting PSS would definitely mean a rather steep learning curve for engineers who are relatively accustomed to verification methodologies and toolsets. Rapid updating skills of the team would be necessary to draw all the benefits of PSS.
a.How to Overcome It:
Have structured PSS training programs-including workshops and hands-on, across all junior engineers right up to the senior verification lead-and have everybody skilled in this new methodology. Have a culture of knowledge sharing: The best engineers who embrace PSS early on are then coaches, sharing best practices for creating models, generating scenarios, and debugging.
Develop standardized and internal libraries of PSS components that the engineers can leverage as template as well as reference for any new model. Pre-loads of such built assets save huge onboarding time and provide engineers with real references that are more amenable to use and come up with PSS quick on productivity.
E. Challenge: Achieving Cross-Platform Consistency
Since PSS is targeted to be portable, however, it is really challenging to get consistent verification results on a simulation, emulation, or hardware platform. In many cases, these variations in test behavior are the outcome of some kind of platform-specific constraints or limitation.
a. How to Overcome It:
To address this, validation logic needs to be included in the PSS models which will ensure that any test scenario of PSS obeys explicit conditions for each platform. For example, a test requiring more control over timing and synchronizations would need to be taken into account as additional constraints in PSS models.
By adapting the tests for what is possible with each platform, you keep uniformity in executing tests different environments and also ensure the consistency and dependability of the results.
IV. Future-Proofing Verification Processes with PSS
To achieve long-term success, as the complexity of semiconductor designs continues to increase and technology advances rapidly, verification processes must adapt in similar ways. It is in this context that one's verification workflow can be future-proofed with the Portable Stimulus Standard (PSS)-with flexible, scalable models created that take into account the evolution of the industry and emerging methodologies.
A. Adapting to New Technology Developments
The continuous advancement of semiconductor technology through newer architectures, protocols, and fabrication techniques demands verification teams to ensure that the PSS models are designed to embrace new technologies without necessarily demanding a total overhaul. Modular design approaches have made this possible because they allow component swapping and replacement as need be, ensuring verification processes can keep up with changes in technologies.
For instance, in case of new communication protocols or new memory architectures, modular PSS models allow teams to introduce such innovations into their test scenario without forcing them to redo the entire verification flow. Flexibility thus reduces downtime and brings verification processes abreast with the current industrial standards.
B. Preparation for changing industry standards
Verification standards are continually increasing with the time and need to accommodate ever-rising complexity of semiconductor systems. Companies that will be working with flexible PSS models allows it to react better to updated standards. The newly defined verification standards, such as those defined by organizations like Accellera, force teams to review their process constantly in order to adhere to the new standards. With PSS, one develops models not only compliant with current standards but also flexible and able to react to the changing standards in time.
For example, if new safety or security features are introduced for particular devices during the evolution of verification standards, flexible PSS models allow teams to easily add such requirements without reverting to clean sheet design. It is this flexibility that provides the cornerstones of maintaining compliance in an increasingly dynamic regulatory environment.
C. Leveraging Automation to Handle Increased Complexity
Trends of Future Semiconductor Projects - Semiconductor projects can only continue and continually be more complex designs, more subsystems, multiple cores, integrated hardware-software components, and so on. Automation becomes key in the management of complexity through the power of PSS. Generation and execution of test scenarios help teams deal with larger and more intricate designs without overstretching resources.
As the integration of these ML and AI technologies into the verification workflows rises, PSS models have to be adaptable enough to absorb these advancements. Organizations with a base for verifying processes built around automated and adaptive PSS models can quickly integrate these technologies to make the testing even more optimal, increase coverage, and improve analysis.
D. Building Scalable and Reusable PSS Models
Scalability is also one of the critical aspects in future-proofing verification flow. Verification environments need to scale from small designs to much larger, more complex SoCs with minimal rework. Thus, scalable verification environments for various projects can be developed by teams by concentrating on reusable PSS models so that adequate switching to verification flows can be done when the scale or complexity of the design increases.
For instance, reusable models that can be initially created for small components, be thereafter adapted and further elaborated in bigger SoC designs, saving time and effort. In addition, the teams would use these models for other projects, resulting in an efficient workflow, growing with time naturally with the needs of the organizations.
To be competitive in this fast-changing industry of semiconductors, organizations need verification workflows that are prepared for change. PSS provides a framework through which teams can design flexible, scalable models that not only align with current industry standards but also can incorporate some of the new trends and technologies emerging in the future. First, it allows teams to future-proof themselves in this environment with verification processes via investing in automation, modular design, and reuse of models, thus not having to continuously experience large-scale overhauls due to innovation from the industry for long-term success.
V. Conclusion
Indeed, the PSS has revolutionized the world of verification. It makes workflows more efficient, increases test coverage, and maintains cross-platform consistency. When applied early in the design cycle, using modular reusable models, manual effort and verification cycles can be greatly reduced.
With PSS, it addresses all the issues currently but also guards the verification flow from all the accelerations of technology changes and flux in industry standards. Since complexity levels are constantly being pushed upwards by semiconductor companies, embracing PSS will actually give the way to agile delivery, quick time to market, and high-quality products.
In simple words, optimising verification with PSS is the need of the hour to be competitive and look ahead to the dynamic semiconductor industry tomorrow.
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