How FPGA-to-FPGA Retargeting Improves Performance and Versatility

Introduction

FPGAs have revolutionized modern hardware system design, providing unparalleled flexibility and performance. Because FPGAs are reprogrammable after deployment, designers can then adapt and optimize their systems to do a particular job. One of the more advanced applications is FPGA-to-FPGA retargeting, whereby the functionality of one FPGA design is seamlessly transferred to another FPGA. This approach has gained much ground as it enhances performance and adaptability across many usage scenarios.

In this blog, we will explore the concept of FPGA-to-FPGA retargeting, see its benefits, and understand its impact on the modern engineering challenge.

What is FPGA-to-FPGA Retargeting?

FPGA-to-FPGA retargeting refers to the translation of a hardware design targeting one FPGA device into a design that may operate on another FPGA device. This involves aspects such as:

• Design adaptation for different FPGA architectures.
• Constraints such as clocking, pin mapping, and logic element utilization are resolved.
• Ensure the same functional and performance metrics on the target FPGA are achieved or bettered.

Key Benefits of FPGA-to-FPGA Retargeting

1. Performance Optimization

FPGAs belong to various families and architectures. Optimized for specific workloads, they are targeted retargeted designs to leverage the specific strength of the targeted FPGA such as:

Higher clock speeds Advanced DSP blocks for signal processing Larger memory resources for complex applications

2. Cost Efficiency

Retargeting lets engineers use the same design for cost-optimized FPGAs for various levels of performance. For instance:

High-end FPGAs for high-level real-time systems Lower-cost devices for less demanding applications.

3. Scalability

Retargeting offers scalability because a design can be migrated into more highly advanced FPGAs without redesigning it from scratch as the requirement evolves.

4. Reusability

Retargeting helps in reusability, where designs can run on different FPGAs, saving development time and effort.

5. System Integration

Modern systems involve multiple FPGAs communicating with each other. Retargeting ensures the compatibility of them.

Click here to learn about “The Role of FPGA Prototyping in Modern IC Development”.

How FPGA-to-FPGA Retargeting Works

The FPGA-to-FPGA retargeting process encompasses several critical steps:

1. Analysing the Original Design

It is essential to have a complete understanding of the original design implemented on the original FPGA. These include:

• Resource usage, such as logic elements, DSPs, and memory blocks used in the design.
• Knowing the timing constraints including clock speeds, to ensure that they may be duplicated or modified for the target FPGA.
• The unique features or architectural advantages of the original FPGA are critical for design performance.

This analysis provides the basis for retargeting as it highlights those aspects that must be preserved or optimized in the new FPGA.

2. Mapping Resources

Next to these is the mapping of resources of the original design to corresponding components in the target FPGA. For instance:

• Logic elements and flip-flops in the original FPGA must be mapped to corresponding structures in the target FPGA.
• Specialized components like DSP blocks, memory blocks, and I/O pins need to be matched with their correspondents.

This step ensures that the functionality is in pace with the capabilities of the new FPGA.

3. Timing Constraint Handling

Timing constraints are paramount to ensuring that the design will work correctly. Because of the differences in various FPGAs as well as their clocking capabilities and timing characteristics, the constraints need to be adjusted so they match the target FPGA’s clock domains and timing specifications.

Tested to confirm that critical paths and setup/hold times are met without introducing errors or performance degradation.

At this step, performance metrics are ensured to be met for the retargeted design.

4. Simulation and Verification

After mapping the resources and resolving timing constraints, the retargeted design needs to be simulated and verified. This includes:

• Running functional simulations to ensure that the design works as required under a variety of conditions.
• Performs the timing analysis to confirm that the incorporated constraints are satisfied and the design functions properly.

Simulation and verification are very important because of potential design flaws before the implementation on the target FPGA.

5. Synthesis and Place-and-Route

The final step is synthesis of the design for the target FPGA, place-and-route using its specific toolchain. This includes:

• Translating the design into a netlist optimized for the target FPGA’s architecture.
• These mapped resources are then allocated on the FPGA’s physical layout to meet timing and routing requirements.
• Generating the bitstream, which is the binary file used to program the target FPGA.
• Once this is done, the design is ready for testing on the hardware.

Challenges in FPGA-to-FPGA Retargeting

While retargeting offers numerous benefits, it comes with challenges:

Toolchain Compatibility: Different FPGA vendors use different design tools, requiring adaptation.

Hardware Differences: differences in architecture, resources available, and clocking mechanisms must be handled with care.

Timing Closure: Timing closure on the target FPGA is challenging due to the variations in routing and clock management.

Applications of FPGA-to-FPGA Retargeting

FPGA-to-FPGA retargeting is an adaptive technique and finds application in various domains to help meet changing technological needs and optimize system performance. The following explains how retargeting benefits several key sectors:

1. Telecommunications

Network standards in telecommunications, however, including 4G and 5G, are highly improving and pushing the envelope in terms of performance and capabilities. FPGA-to-FPGA retargeting is all about enabling the following:

• System Upgrades: The ability to retarget existing FPGA designs to include the newer, higher-level protocols and features that advanced communication systems demand.
• Future-proofing: As network requirements evolve, retargeting allows hardware designs to remain relevant and handle modern workloads without the need for a complete redesign.

For example, a design that could be created for 4G networks could be retargeted to support the advanced processing needs of 5G networks.

2. Aerospace and Defence

Long lifecycles are common for aerospace and defence systems, but the hardware components – FPGAs in particular – eventually reach end-of-life status. Retargeting addresses this challenge by:

• Ensuring Longevity: Designs implemented on older FPGA families can be migrated to newer FPGA models, thus ensuring their continued use in mission-critical applications.
• Performance Improvements: Most of the latest FPGA families come with better performance and reliability which is requisites for applications in aerospace and defence.

For example, radar systems or avionics platforms that were developed on legacy FPGAs could be retargeted to exploit modern FPGA families’ advanced capabilities.

3. Automotive

The automotive industry nowadays increasingly relies on FPGAs for applications like advanced driver assistance systems (ADAS), powertrain control, and in-vehicle infotainment. Retargeting supports this domain by:

• Adapting to Varying Performance Needs: Different automotive control units require different levels of computation. Retargeting allows the same design to be adapted for high-performance systems or cost-optimized variants.
• Enabling Scalability: As new models and features are brought into the pipeline, FPGA retargeting ensures that designs can scale across multiple vehicle platforms without extensive redevelopment.

For example, an FPGA design used in a high-end luxury car can be retargeted to work in a mid-range model with minimal modifications.

4. Artificial Intelligence and Machine Learning (ML)

AI and ML applications need special hardware accelerators for purposes such as deep learning inference and neural network training. FPGA-to-FPGA retargeting can be beneficial in this domain by:

• Optimized Performance: Different architectures of FPGAs may support workloads associated with AI differently. Retargeting helps ML accelerators to be optimized for the architecture of the target FPGA for enhanced throughput and energy efficiency.
• Scaling of Usability: With increased sophistication in AI models, retargeting ensures designs can be transferred to more advanced, powerful FPGAs that will solve the increasing computational demands.

For example, a neural network inference engine developed for one FPGA can be retargeted to another one that possesses advanced DSP and memory capabilities, thus improving performance overall.

FPGA-to-FPGA Retargeting Process Flow

Below is a flowchart illustrating the steps involved in the FPGA-to-FPGA retargeting process:

Practical Application: Retargeting a DSP Design

Consider a digital signal processing (DSP) design originally implemented on an FPGA with simple basic DSP blocks. Retargeted onto a high-end FPGA with advanced DSP slices, the design might:

• Offer higher throughput based on fully exploiting the advanced capabilities of the DSP slices.
• Reduced usage of resources, thereby freeing up logic for other functions.

Conclusion

FPGA-to-FPGA retargeting is a very powerful technique that addresses both modern challenges: scalability, cost efficiency, and performance optimization. When the FPGA ecosystem continues to evolve, the ability to seamlessly retarget designs across devices will become significantly more important for engineers.

Mastering the ability to move designs between FPGAs represents new opportunities for innovation; your designs will always be adaptable and high-performing for various applications.

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