Designing for Debug: Top 10 Strategies for Managing Debug Complexity in Modern Semiconductor Designs

Semiconductor design is becoming increasingly complex and challenging as technology scales and new applications emerge. To ensure the quality and reliability of the final product, designers need to have effective and efficient methods for debugging their designs at different stages of the development cycle, from pre-silicon simulation and verification to post-silicon validation and testing. The current technology era has brought rapid breakthroughs in semiconductor manufacturing processes to support extreme design complexities, leading to the integration of billions of transistors into a single die resulting in sophisticated electronic systems with unparalleled performance and functionality. This period is also seeing the emergence of new design methodologies and technologies, such as 3D packaging, and advanced lithography techniques, which have allowed designers to continue pushing the boundaries of semiconductor shrinkage despite the physical limitations of scaling. 

This miniaturization has increased chip complexity and resulted in more powerful and energy-efficient electronic systems, with applications in fields such as artificial intelligence, machine learning, self-driving cars, and the Internet of Things. This era of VLSI technology and sub-5nm nodes is a significant milestone in semiconductor manufacturing history, and it sets the stage for future innovations.

With the advancements in process technology and complex designs, a major challenge in semiconductor design is Design for Debug (DFD). DFD refers to the practice of designing electronic systems with built-in features and methodologies to facilitate the identification and resolution of issues that may arise during the deployment and debugging process. The aim of DFD is to shorten the debugging time and improve the quality and reliability of the final product. DFD includes features such as built-in self-test circuits, observability, and controllability, and is a critical part of the design process for complex electronic systems. With the increasing complexity of modern electronic systems, DFD has become an essential tool for designers to ensure that products are delivered on time and meet the high standards of quality and reliability required by modern applications.

Two key aspects of design for debug (DFD) are the architecture of the system, which determines how the various components interact and communicate with each other, as well as with external tools and interfaces and the Design of the system that simplifies the implementation to ensure simplified verification and ease of physical design without coming into the critical path. A well-designed architecture can facilitate the debugging process by providing good visibility, controllability, and observability of the system's behavior and state, as well as enabling the injection and detection of faults and errors.

Lets dive into the details.

Are DFT and DFD similar?

Design for Test (DFT) and Design for Debug (DfD) are two related but distinct concepts in semiconductor design. DFT features are intended to help test and verify the functionality of a design during manufacturing, while DfD features are intended to help debug and diagnose issues that arise during the post-silicon bring-up phase. DFT features are primarily intended to support manufacturing testing and verification, while DfD features are intended to support post-silicon debugging and diagnosis. Both are important concepts in semiconductor design and can help reduce time-to-market, cost, and improve the quality of designs.

DFT features typically include on-chip test logic and other built-in self-test (BIST) circuits that allow designers to test and diagnose the functionality of the design during manufacturing. DFT features may also include scan chains and other observability features that enable designers to observe internal signals and functionality during testing.

DfD features, on the other hand, are intended to help diagnose and debug issues that arise during the post-silicon bring-up phase. DfD features may include on-chip debug logic, error detection and correction circuits, and other built-in diagnostic capabilities that enable designers to monitor and diagnose issues in real-time.

Some specific examples of DFT features include boundary scan, memory built-in self-test (MBIST), and power-on self-test (POST) features. In contrast, specific examples of DFD features include on-chip trace buffers, performance monitors, and other diagnostic features that enable real-time monitoring and analysis of on-chip signals and functionality.

Here are the Top 8 strategies for managing complexity in modern semiconductor designs to streamline Design for Debug:

1. Adopt a modular Architectire/Design approach: 

A modular architecture and design approach can simplify the controllable parts of the design for debugging by allowing designers to isolate and debug individual modules rather than the entire design at once.

Here are 3 key considerations when adopting a modular approach for DFD:

1. A modular approach involves breaking a complex system or design into smaller, more manageable functional blocks. When adopting this approach for DFD, it is important to identify the key functional blocks that are most likely to cause issues during bring-up and validation.
2. To enable easy integration and testing of functional blocks, it is important to use standard interfaces that are well-defined and understood. This can help simplify the process of debugging and validation by ensuring that each block can be tested and validated in isolation and with least setup effort before being integrated into the larger system
3. To facilitate post-silicon debug, each functional block should include its own on-chip debug logic. This can help isolate issues to specific blocks, reducing the time required to diagnose and fix issues with better control.

2. Implement standard interfaces: 

Standard interfaces can facilitate debugging by providing a common interface between modules that simplifies integration and reduces the likelihood of interface-related issues. It is an important aspect of Design for Debug (DFD) in complex semiconductor designs. 

Here are 5 examples of how standard interfaces can be used for DFD:

1. Many modern semiconductor designs incorporate an industry-standard JTAG interface, which can be used for boundary scan testing, on-chip debugging, and programming of non-volatile memory devices. By incorporating this standard interface, designers can simplify the process of debugging and testing their designs, since they can leverage pre-existing tools and methodologies that are well-established within the industry.
2. The ARM AHB (Advanced Microcontroller Bus Architecture) is a widely-used standard for on-chip interconnects in complex SoC (system-on-chip) designs. By incorporating AMBA-based bus interfaces into functional blocks within the SoC, designers can enable standardization across the entire design and ensure that each functional block can be easily integrated and tested with other blocks.
3. Many semiconductor designs incorporate standard memory interfaces, such as DDR (Double Data Rate) SDRAM (Synchronous Dynamic Random Access Memory) or LPDDR (Low Power DDR) interfaces, to enable high-speed data transfer to and from memory devices. By using these standard interfaces, designers can leverage pre-existing tools and methodologies for memory testing and validation, and can more easily diagnose and fix issues related to memory access and performance.
4. The AMBA trace bus (ATB) is designed to be highly scalable and can support a wide range of trace data sources, including processor cores, buses, memory controllers, and peripheral devices. By capturing this trace data and analyzing it using specialized tools, designers can gain valuable insights into the behavior of their designs and identify issues that may be difficult or impossible to diagnose using other debugging methodologies.
5. The MIPI PTI interface is designed to be flexible and scalable, allowing it to support a wide range of trace data sources, including processors, buses, memory controllers, and peripherals. This makes it an ideal choice for debugging complex SoC designs, where there are numerous sources of trace data that need to be captured and analyzed. The MIPI PTI interface is also well-supported within the industry, with a wide range of tools and methodologies available for capturing and analyzing trace data. By incorporating the MIPI PTI into a design, designers can leverage pre-existing tools and methodologies for post-silicon debug, rather than having to develop custom solutions. 

3. Efficient Trace Signal selection: 

Trace design is a technique that captures and stores a subset of internal signals during the normal operation of the device. The stored signals can be later retrieved and analyzed for debugging purposes. Trace design can be implemented using various methods, such as on-chip buffers, off-chip analyzers, or embedded logic analyzers. Trace design can provide more visibility and observability than scan based design, but it also has some limitations, such as storage capacity, bandwidth, trigger conditions, and signal selection criteria.

Here are three considerations:

1. The first consideration is to select trace signals that are relevant to the debug objectives and scenarios. For example, if the debug objective is to verify the functionality of a specific module or component in the DUT, then trace signals that are related to the inputs, outputs, and internal states of that module or component should be prioritized. Similarly, if the debug scenario involves a specific stimulus or event that triggers an error or defect in the DUT, then trace signals that can capture or correlate with that stimulus or event should be selected.
2. The second consideration is to select trace signals that can provide sufficient coverage of the DUT's behavior and functionality. Coverage refers to the extent to which trace signals can represent or reflect the different aspects or dimensions of the DUT's operation, such as temporal, spatial, logical, or functional aspects. For example, temporal coverage refers to how well trace signals can capture the timing and sequence of events in the DUT; spatial coverage refers to how well trace signals can capture the distribution and interaction of signals across different regions or layers of the DUT; logical coverage refers to how well trace signals can capture the values and transitions of signals in different modes or states of the DUT; and functional coverage refers to how well trace signals can capture the outputs and outcomes of different functions or operations performed by the DUT.
3. The third consideration is to select trace signals that can provide diverse and complementary information about the DUT's behavior and functionality. Diversity refers to the degree of variation or difference among trace signals in terms of their characteristics, properties, or features. For example, trace signals can vary in terms of their frequency, amplitude, phase, polarity, direction, type, format, or content. Selecting diverse trace signals can help increase the amount and quality of information that can be obtained from the DUT, as well as reduce redundancy and correlation among trace signals.

4. Utilize abstraction techniques during Pre Si Verification: 

Abstraction can make design for debugg easier by allowing designers to focus on identifying issues early in the design cycle rather than waiting for a mature low-level implementation. The metrics from these simulations can help pinpoint potential issues.

Here are three abstraction techniques that can support DFD:

• System level abstraction is often necessary to abstract the system-level behavior to a higher level of representation. This abstraction technique allows designers to focus on the overall system-level behavior rather than on individual components or modules. By identifying and isolating the root cause of a problem at a higher level of abstraction, designers can quickly diagnose and fix issues related to system-level behavior. Suppose a designer is working on a complex system-on-chip (SoC) design that contains multiple processors, memory controllers, and peripheral interfaces. If an issue arises during post-silicon debug related to the overall system-level behavior, the designer may use system-level abstraction techniques to focus on the high-level system behavior. This could involve abstracting the system into several sub-systems or modules, each with well-defined interfaces and functionality. 
• Transaction-level abstraction involves abstracting the design behavior at the transaction level. This technique allows designers to focus on the transaction flow through various components or modules, without worrying about the implementation details of the individual components or modules. By abstracting the design at the transaction level, designers can isolate and fix issues related to transaction flow and data transfer between different components or modules. Suppose a designer is working on an interface design between two modules that transfer data using a protocol such as USB or PCIe. If an issue arises during post-silicon debug related to the transaction flow, the designer may use transaction-level abstraction techniques to abstract the design at the transaction level. This could involve focusing on the transaction flow, such as packetizing data, error checking, or flow control, rather than the specific details of each module's implementation. 
• Signal-level abstraction involves abstracting the design behavior at the signal level. This technique allows designers to focus on the signals flowing between different components or modules, without worrying about the implementation details of the individual components or modules. By abstracting the design at the signal level, designers can isolate and fix issues related to signal integrity, timing, and noise. Suppose a designer is working on a high-speed interface design between two modules that transfer data at high speeds. If an issue arises during post-silicon debug related to signal integrity or noise, the designer may use signal-level abstraction techniques to abstract the design at the signal level. This could involve focusing on the signal quality, such as the rise and fall times, the jitter, or the noise margin, rather than the specific details of each module's implementation. 

5. Employ maximum design reuse: 

Design reuse can simplify debugging by eliminating the need to debug functionality that has already been tested and validated in previous designs.

Here are four ways in which design reuse can simplify the DFD process:

• By reusing previously designed and tested IP blocks, the overall complexity of the design is reduced. This simplifies the post-silicon debug process by reducing the number of new components that need to be debugged, allowing designers to focus on the integration of the reused IP blocks. 
• Since the reused IP blocks have already been tested and verified, their behavior is well understood. This means that designers can confidently reuse these blocks without worrying about the need for additional testing or debugging, reducing the overall time and effort required for DFD.
• Reusing IP blocks that conform to industry-standard interfaces, such as AMBA, can further simplify the post-silicon debug process. Standardized interfaces provide a consistent and familiar set of signals and controls, making it easier for designers to integrate the reused IP blocks and debug any issues that may arise.
• If the reused IP blocks have already been debugged in previous designs, designers can leverage this knowledge to more quickly diagnose and resolve issues in the current design. By understanding how the IP blocks were debugged in previous designs, designers can avoid making the same mistakes or overlooking similar issues in the current design.

6. Use design verification metrics to judge DFD logoc additions: 

Design verification metrics like functional and code coverage can help identify and catch issues early in the design process, reducing the amount of debugging required later on. Additionally they can predict areas of focus based on heuristics and data flow that can lead to efficiently defining debug focussed design methods/logoc additions to simplify post-silicon debug.

Here are three ways in which design verification can simplify DFD:

• Verification tools and methods, such as simulation and formal verification, can detect design issues early in the design cycle. By identifying issues before fabrication, designers can make changes to the design and avoid costly post-silicon debug efforts.
• Verification can help also improve the coverage of the design verification process. By exercising the design under a wide range of scenarios and test cases, designers can be more confident that the design will function correctly in all possible operating conditions.
• Verification can provide detailed reports on the causes of bugs, which can simplify post-silicon debug. For example, a simulation may identify a specific clock cycle or input stimulus that triggered a bug, allowing designers to quickly isolate and correct the issue.

7. Create detailed design documentation: 

Detailed design documentation can help ensure that all team members understand the design and can debug it effectively.

Here are five ways in which detailed design documentation can improve DFD:

• Detailed design documentation can help debuggers to understand the design's intended functionality, design choices, and constraints. This understanding can help debuggers to more easily identify and isolate bugs.
• Detailed interface documentation can help debuggers to understand how different modules of the design communicate with each other. This understanding can help debuggers to identify where a bug may have originated and track its propagation through the design.
• Detailed test documentation can help debuggers to understand how the design was tested during the design process. This understanding can help debuggers to identify test cases that may have been missed and test cases that can be used to isolate and reproduce bugs.
• Detailed design information about the design's timing constraints, power constraints, and other critical design parameters adds significant value. This information can help debuggers to identify design rule violations and potential sources of bugs.
• Detailed change history that records all changes made to the design during the design process in very crucial. This information can help debuggers to understand how the design has evolved over time and identify potential sources of bugs.

8. Conduct regular design reviews: 

Regular design reviews can help identify potential issues early in the design process, reducing the need for complex debugging later on.

Here are five ways in which regular design reviews can help in DFD:

• Regular design reviews can provide an opportunity for the design team to review their design choices and ensure that they align with the intended functionality of the design. This can help to prevent design bugs that may have arisen due to poor design choices.
• Regular design interface reviews can also provide an opportunity for the design team to review the interfaces between different modules of the design. This can help to ensure that the interfaces are well-defined and that they allow for easy debugging in case of a bug.
• Regular design constraints reviews can also provide an opportunity for the design team to review the design constraints such as timing, power, and area. This can help to ensure that the design is meeting the required constraints, which can help to reduce the likelihood of design bugs.
• Regular test strategy reviews can also provide an opportunity for the design team to review their test strategy and ensure that they are testing all aspects of the design thoroughly. This can help to identify bugs early on in the design process, which can help to reduce the likelihood of post-silicon debug.
• Regular DFD feature reviews can also provide an opportunity for the design team to review the DFD features that are included in the design. This can help to ensure that the DFD features are well-designed and implemented, which can help to facilitate post-silicon debug.

9. Use design for test (DFT) techniques: 

DFT can simplify debugging by providing on-chip test features that allow designers to isolate and diagnose issues quickly and accurately.

Here are seven examples of DFT techniques that can be used for DFD:

• Scan chains are commonly used in DFT to capture the state of a design and apply test vectors. However, they can also be used for DFD purposes by allowing the state of a failing design to be captured and analyzed during post-silicon debug.
• BIST is a technique used in DFT to add test circuits to a design that can test and diagnose the design itself. BIST can also be used for DFD purposes by including a diagnostic mode that can be used during post-silicon debug.
• MBIST is a technique used in DFT to test and diagnose memory blocks within a design. MBIST can also be used for DFD purposes by including diagnostic modes that allow the memory blocks to be analyzed during post-silicon debug.
• JTAG is a standard used in DFT to provide access to the internal circuitry of a design for testing and debugging purposes. JTAG can also be used for DFD purposes by providing access to the internal circuitry of a design during post-silicon debug.
• Boundary scan is a technique used in DFT to provide access to the I/O pins of a design for testing and debugging purposes. Boundary scan can also be used for DFD purposes by providing access to the I/O pins of a design during post-silicon debug. 
• A Scan dump is a diagnostic method used during post-silicon debug that captures the state of the scan chain and associated flip-flops at the time of a failure. This allows designers to analyze the captured data and determine the root cause of the failure.
• An Array freeze and dump is another diagnostic method used during post-silicon debug that captures the state of a memory array at the time of a failure. This allows designers to analyze the captured data and determine the root cause of the failure. 

10. Built in Debug Security:

One of the key challenges of designing for debug in semiconductors is that the debug features are often embedded in the chip's hardware, making them hard to disable or modify after fabrication. This means that the debug features can be exploited by malicious actors who have physical access to the chip, such as reverse engineers, hackers, or competitors. For example, a malicious actor could use the debug features to extract intellectual property, modify the chip's behavior, or bypass security mechanisms.

To mitigate this risk, designers need to implement various security measures in the debug features, such as encryption, authentication, access control, and obfuscation. These measures can prevent unauthorized access to the debug features or limit the amount of information that can be extracted or modified. For instance, encryption can protect the communication between the chip and the debug tool, authentication can verify the identity of the debug tool, access control can restrict the debug functions based on the level of authorization, and obfuscation can hide or randomize the debug data.

Designing for debug in semiconductors is not only a technical challenge, but also a business and legal challenge. Debug features can affect the chip's performance, cost, and time-to-market, as well as its compliance with regulations and standards. Therefore, designers need to consider the trade-offs between debugging and security, and align their design decisions with the business objectives and legal requirements of their customers and stakeholders.

Designing for debug in semiconductors is a complex and dynamic process that requires constant evaluation and adaptation. As new technologies emerge and new threats arise, designers need to update their debug strategies and security measures accordingly. By doing so, they can ensure that their chips are both debuggable and secure, and deliver high-quality products to the market.