As system complexity and performance demands continue to rise, single-FPGA solutions are often no longer sufficient. Applications such as high-performance computing, avionics, radar, AI acceleration, and data center networking increasingly rely on multi-FPGA systems to achieve higher throughput, scalability, and flexibility. Designing such systems, however, introduces new challenges in partitioning logic, managing interconnects, and maintaining precise synchronization across devices. This blog explores practical strategies to address these challenges effectively.
Understanding Multi-FPGA Systems
A multi-FPGA system consists of two or more FPGAs working together to implement a single logical design or application. These FPGAs may be located on the same board, across multiple boards, or even distributed across a chassis. The primary motivation behind this approach is to overcome limitations related to logic capacity, I/O bandwidth, power, or performance that a single FPGA cannot meet alone.
While multi-FPGA architectures enable scaling, they also introduce complexities related to data movement, latency, clocking, and design verification. A well-planned system architecture is therefore critical for success.
Design Considerations Before Partitioning
Before dividing a design across multiple FPGAs, it is important to analyse the application requirements thoroughly. Key factors include data bandwidth between modules, latency sensitivity, clock domain requirements, and expected future scalability. Early architectural decisions can significantly reduce design iterations and integration risks later in the project.
Another important aspect is selecting the right FPGA devices. Factors such as available transceivers, supported interconnect standards, logic density, memory resources, and power budget directly influence how the design can be partitioned and interconnected.
Strategies for Design Partitioning
Partitioning is the process of dividing a large design into smaller functional blocks that can be mapped onto multiple FPGAs. A common and effective approach is functional partitioning, where each FPGA is responsible for a distinct subsystem such as signal processing, control, data aggregation, or protocol handling. This method improves modularity and simplifies debugging.
Another approach is data-flow-based partitioning, where the design is divided according to data paths. Blocks with heavy internal communication are kept within the same FPGA, while well-defined data streams are passed between devices. This helps minimise inter-FPGA communication and reduces latency.
In some high-performance applications, resource-based partitioning is used. Here, logic is distributed based on available LUTs, DSP slices, BRAM, or high-speed transceivers. This approach is useful when specific parts of the design have intensive resource requirements.
Regardless of the strategy, it is essential to minimise cross-FPGA signals, clearly define interfaces, and maintain balanced resource utilisation across devices.
Interconnect Technologies in Multi-FPGA Systems
Interconnect design plays a critical role in overall system performance. The choice of interconnect depends on required bandwidth, latency, distance, and power constraints.
Parallel interconnects are often used for short-distance, high-throughput communication on the same board. These are relatively simple to implement but can become challenging at higher speeds due to signal integrity and routing complexity.
High-speed serial interconnects using FPGA transceivers are widely adopted in modern designs. Standards such as PCIe, Ethernet, Aurora, JESD204, and custom serial links offer scalable bandwidth with fewer physical connections. These interfaces are well-suited for both board-level and backplane communication.
Chip-to-chip protocols and FPGA-to-FPGA links using low-latency serial interfaces are also gaining popularity, especially in data center and accelerator platforms. They enable efficient data sharing while maintaining protocol flexibility.
When designing interconnects, careful attention must be paid to signal integrity, clock recovery, lane bonding, and error detection to ensure reliable communication.
Synchronization and Clocking Challenges
Synchronization is one of the most critical aspects of multi-FPGA system design. Each FPGA may have its own clock source, leading to clock domain crossings and potential timing issues. Poor synchronization can result in data corruption, metastability, or unpredictable system behaviour.
One common approach is to use a global reference clock distributed to all FPGAs. This ensures frequency alignment and simplifies timing analysis. However, skew management becomes important, especially in large or distributed systems.
In cases where a single clock is not feasible, clock domain crossing techniques such as asynchronous FIFOs, handshake protocols, and elastic buffers are used. These methods allow safe data transfer between different clock domains while maintaining data integrity.
For applications requiring precise timing alignment, such as radar or avionics, techniques like deterministic latency links, timestamping, and phase alignment using PLLs or MMCMs are employed. Protocols that support deterministic behaviour are often preferred in such scenarios.
Reset and Configuration Synchronization
In multi-FPGA systems, reset and configuration sequencing must be carefully managed. All devices should enter a known state during power-up and reset events. Improper reset sequencing can lead to partial system initialisation and difficult-to-debug failures.
A common strategy is to use a central controller or supervisor FPGA to manage reset, configuration, and monitoring of other devices. This ensures coordinated start-up and simplifies system management.
Verification and Debug Considerations
Verification complexity increases significantly in multi-FPGA designs. Simulation must account for inter-FPGA interfaces, timing variations, and synchronisation mechanisms. Co-simulation and hardware-in-the-loop testing are often used to validate system-level behaviour.
Debugging also requires careful planning. Integrated logic analysers, cross-triggering, and well-defined debug interfaces help capture and correlate events across multiple FPGAs. Designing with observability in mind can save substantial time during system bring-up.
Power, Thermal, and Scalability Considerations
Multiple FPGAs increase overall power consumption and thermal density. Efficient power management, proper heat dissipation, and airflow design are essential to maintain reliability. Partitioning decisions should also consider power distribution and thermal balance across the board or system.
From a scalability perspective, modular architectures make it easier to add or upgrade FPGAs as requirements evolve. Using standardised interconnects and reusable design blocks supports long-term system growth.
Conclusion
Multi-FPGA systems enable designers to build high-performance, scalable solutions that go beyond the limitations of a single device. Successful implementation depends on thoughtful partitioning, robust interconnect design, and reliable synchronisation strategies. By addressing these aspects early in the design process and adopting proven architectural practices, engineers can unlock the full potential of multi-FPGA architectures while reducing integration risk and development time.
As applications in high-speed data processing, aerospace, and advanced computing continue to grow, multi-FPGA systems will remain a key enabler for next-generation electronic designs.
