During a project troubleshooting session, a hardware module occasionally exhibited functional anomalies upon power-up. Further investigation revealed that the digital signals generated by the FPGA were abnormal, which was traced back to the output of the digital filter being erroneous. The root cause was identified as an issue with the reset of the digital filter.
This is a very practical and common problem in FPGA designs. Failing to reset filters (especially digital filters like FIR and IIR) can lead to a series of serious issues, primarily because the initial state of the filter is unknown.
1. Unknown Initial State
In an FPGA, the storage elements that make up the filter (such as DSP48 units, registers, and Block RAM) have unpredictable internal values after power-up configuration is complete. They could be all zeros, all ones, or any random combination of zeros and ones. This random initial value is referred to as the filter’s “initial state.”
2. Specific Problems That May Occur
1. Long Output Transients and Setup Times
Phenomenon:
After the filter begins operation, it may take a long time (potentially hundreds or even thousands of clock cycles) for the output to stabilize to the correct value. During this stabilization period, the output is invalid and filled with “glitches.”
Cause:
The filter’s delay line (such as the tap register chain in an FIR) or state variables (like feedback registers in an IIR) are filled with random data. When the first valid data input arrives, it convolves or operates with this random data, resulting in a random output. As valid data continues to flow in, it gradually “flushes” out these random states, and the output slowly approaches normal.
2. System-Level Cascading Failures
Phenomenon:
If the output of this filter directly drives another module (for example, a decoder, a controller, or another filter), then the downstream module receives these invalid, chaotic data during the startup phase.
Consequence:
This may lead to erroneous actions in the downstream module, entering incorrect states, or even triggering cascading failures throughout the entire system. For instance, a motor drive system may experience severe jitter due to an erroneous filter value.
3. Discrepancies Between Simulation and Actual Measurements
Phenomenon:
In simulation, you might provide a clear reset signal to the filter, and everything works correctly. However, once programmed into the FPGA, the behavior may not match the simulation.
Cause:
Simulation tools typically initialize values to X (unknown) or 0. If you rely on this “default” behavior of the simulation environment without explicitly resetting in the code, the initial values in the real FPGA are random, leading to different behavior. This is a classic case of “simulation passes, real-world fails.”
4. Poor Repeatability
Phenomenon:
Each time the FPGA is powered up or reconfigured, the system’s startup behavior may differ.
Cause:
This is because each initial state is random. This is critical for industrial systems that require stable, repeatable behavior.
3. A Simple Example of an FIR Filter
Consider a simple moving average filter: y[n] = (x[n] + x[n-1] + x[n-2]) / 3.
It has two internal registers to store x[n-1] and x[n-2].
1. Without Reset:
After power-up, the values of x[n-1] and x[n-2] are unknown (let’s assume they are A and B).
When the first input x[0] arrives, the output y[0] = (x[0] + A + B) / 3. This result is meaningless because it contains garbage data A and B.
In the second cycle, y[1] = (x[1] + x[0] + A) / 3, still containing garbage data A.
Only in the third cycle does y[2] = (x[2] + x[1] + x[0]) / 3 produce an output that is entirely based on valid input data. Prior to this, the output was incorrect.
2. With Reset:
Before starting operation, a reset pulse clears x[n-1] and x[n-2] to zero.
y[0] = (x[0] + 0 + 0) / 3 (although not completely “correct,” this is a defined, controllable initial state)
y[1] = (x[1] + x[0] + 0) / 3
y[2] = (x[2] + x[1] + x[0]) / 3
The system starts from a known, clean state, making the output behavior predictable.
4. Special Cases and Considerations
1. Global Reset vs. Local Reset:
It is not always necessary to provide a dedicated reset pin for each module. A common practice is to use a global reset signal to uniformly initialize all modules that require resetting at system startup.
2. Synchronous Reset vs. Asynchronous Reset:
Asynchronous Reset:
Effective immediately, not clock-dependent. Poor design can easily lead to stability issues and timing violations.
Synchronous Reset:
Effective on clock edges, safer, and recommended in modern FPGA designs. However, ensure that the reset pulse is long enough to be captured by the clock.
3. Partial Reset:
In some high-performance or high-speed pipelined applications, designers may choose not to reset certain registers to simplify timing, relying instead on subsequent valid data (e.g., packet frame headers) to naturally “flush” out the correct state. This is an advanced optimization technique but carries high risk and must be thoroughly validated, typically only used in data paths, while control paths almost always require resetting.
4. Higher Risks with IIR Filters:
Due to feedback loops in IIR filters, a random initial state may persist longer in feedback, potentially leading to output saturation or overflow, making the issues more severe than those with FIR filters.
5. Conclusion and Best Practices
Conclusion:
In the vast majority of cases, failing to reset filters is a design flaw.
Best Practice Recommendations:
1. Explicit Reset:
In HDL code (VHDL/Verilog), write explicit reset logic for all state registers of the filter (delay lines, accumulators, state machines, etc.).
2. Use Synchronous Reset:
Prioritize synchronous reset designs to enhance system stability and timing performance.
3. Develop a Reset Strategy:
Plan the overall reset scheme for the system. Will it be an automatic reset on power-up, or triggered by an external button? How will the reset signal be distributed to various modules?
4. Thorough Simulation:
Test reset behavior in simulations, including power-up resets and runtime resets, ensuring correct operation under various scenarios.
5. Caution with “No Reset” Designs:
Unless you have compelling reasons (such as pursuing extreme performance or frequency) and fully understand the consequences, do not omit resets.
In short, adding a reset to a filter is akin to performing a “zeroing” operation on a complex machine before startup, which is a critical step to ensure the system begins operation from a known, safe, and consistent state.
Tips
Public Account: FPGA Communication Beginner’s Growth Path
Zhihu: FPGA Communication Beginner’s Growth
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