The Diagnostic Pivot: Isolating the PCE Hypothesis in a Zero-Proof Environment

Message Overview

In message [msg 335] of this opencode session, the assistant executes a targeted diagnostic experiment on a remote proving host:

[assistant] Let me add CUZK_DISABLE_PCE=1 and restart to test if PCE is the culprit: [bash] ssh 10.1.16.218 "sudo sed -i '/^Environment=LD_LIBRARY_PATH/a Environment=CUZK_DISABLE_PCE=1' /etc/systemd/system/cuzk.service && sudo systemctl daemon-reload && sudo systemctl restart cuzk.service && sudo systemctl status cuzk.service" 2>&1 | head -20 ● cuzk.service - CuZK Proving Engine Daemon Loaded: loaded (/etc/systemd/system/cuzk.service; enabled; preset: enabled) Active: active (running) since Mon 2026-03-02 11:09:45 UTC; 13ms ago Main PID: 714808 (cuzk) Tasks: 1 (limit: 531347) Memory: 4.6M (peak: 4.6M) CPU: 4ms CGroup: /system.slice/cuzk.service └─714808 /usr/local/bin/cuzk -l unix:///tmp/cuzk.sock -c /etc/cuzk.toml Mar 02 11:09:45 systemd[1]: Started cuzk.service - CuZ...

At first glance, this appears to be a routine operational command — edit a systemd unit file, reload, restart, check status. But beneath the surface, this message represents a critical decision point in a debugging odyssey that spans multiple segments of the conversation. It is the moment where the assistant commits to a specific hypothesis about the root cause of a 100% proof failure rate, and designs a controlled experiment to test it.

The Context: A Cascade of Failures

To understand why this message was written, we must trace the chain of events that led to it. The team had been implementing Pre-Compiled Constraint Evaluator (PCE) extraction for all proof types — WinningPoSt, WindowPoSt, and SnapDeals — in the CuZK proving engine. This was a significant optimization: instead of running full circuit synthesis (which builds and evaluates ~130 million LinearCombination objects for each proof), the PCE path pre-computes the constraint structure once per circuit topology and reuses it across all proofs, performing only a fast sparse matrix-vector multiply to evaluate the R1CS constraints.

The PCE work had been largely successful. The assistant had implemented the extraction pipeline, added a partitioned pipeline for SnapDeals to overlap synthesis with GPU proving, and fixed a WindowPoSt crash caused by a mismatch in the is_extensible() flag between RecordingCS and WitnessCS. These fixes were deployed to a remote test host (10.1.16.218), a dual-GPU machine running RTX 4000 Ada cards.

But the deployment revealed a devastating problem: every single proof was failing. Logs showed a 100% failure rate — zero valid partitions out of ten for every proof attempt. This was not a sporadic glitch; it was a complete, systematic breakdown of the proving pipeline.

The Investigation Preceding This Message

The assistant spent the preceding messages (314–334) conducting an increasingly focused investigation. The first hypothesis was that the GPU selection mechanism was broken. The C++ code in sppark reads CUDA_VISIBLE_DEVICES at static initialization time, so Rust's std::env::set_var() calls have no effect on the CUDA runtime. This meant that all partition proofs (which use num_circuits=1) were targeting GPU 0 regardless of which Rust worker picked up the job. On a multi-GPU system, this could cause data races on device memory if multiple workers ran concurrently on the same physical GPU.

However, deeper analysis revealed that the per-GPU mutex in the Rust engine should serialize access to GPU 0. The mutex ensures that only one thread at a time enters the CUDA kernel region. So the GPU race hypothesis, while plausible, was not fully consistent with the evidence — especially since the failure rate was 100%, not the intermittent pattern one would expect from a race condition.

The assistant then pivoted to a second hypothesis: the PCE path itself might be producing incorrect witness data. The logs confirmed that every proof was using the PCE fast path. If there were a bug in the PCE evaluation — an off-by-one in constraint indexing, incorrect handling of the ONE input variable, wrong density bitmaps, or a mismatch in the a/b/c vector computation — it would produce consistently invalid proofs.

The assistant examined the PCE code path in detail: the evaluate_pce function that computes a = A*w, b = B*w, c = C*w via CSR sparse MatVec; the RecordingCS::enforce method that captures constraint structure; the into_precompiled function that builds the CSR matrices; and the density bitmap computation. Each component was scrutinized for correctness. The analysis suggested the code was logically sound, but the assistant recognized that theoretical correctness does not guarantee practical correctness — especially in a system as complex as a GPU-accelerated zk-SNARK prover.

The Decision to Run the Experiment

Message [msg 335] represents the moment the assistant decided to stop analyzing code and start running controlled experiments. The reasoning is clear: instead of continuing to trace through source files and build mental models of where the bug might be, the assistant chose to use the CUZK_DISABLE_PCE environment variable — a feature flag designed precisely for this kind of diagnostic — to test the PCE hypothesis directly.

The decision process visible in the preceding messages shows the assistant weighing evidence:

  1. The 100% failure rate ruled out intermittent issues like race conditions or memory corruption (though these could still be present).
  2. The PCE path was active for all proofs, making it the common factor in every failure.
  3. The standard (non-PCE) path was known to work correctly from earlier testing on the local development machine.
  4. The code analysis was inconclusive — the PCE implementation appeared correct in principle, but the proof failures were undeniable. The experiment was elegantly simple: disable PCE, restart the service, and observe whether proofs start passing. If they do, the bug is in the PCE path. If they don't, the bug is elsewhere — likely in the partitioned proof pipeline itself or in some environmental factor unique to the remote host.

Assumptions Embedded in the Action

This message makes several assumptions, some explicit and some implicit:

The CUZK_DISABLE_PCE flag works correctly. The assistant assumes that setting this environment variable to 1 will cause the service to bypass the PCE path entirely and fall back to standard bellperson synthesis. This is a reasonable assumption — the flag was presumably added for this exact purpose — but it is untested in this deployment.

The service restart will be clean. The systemctl restart command terminates the existing process and starts a new one. The assistant assumes the new process will read the updated environment and operate correctly. The status output confirms the service is "active (running)" with a new PID (714808), which is a good sign.

The systemd unit file edit is idempotent. The sed command appends the new Environment= line after the LD_LIBRARY_PATH line. This works correctly on the first run, but if the experiment is repeated, it would add a duplicate line. The assistant is treating this as a one-shot diagnostic, not a permanent configuration change.

The remote host is representative. The assistant assumes that if the PCE path is the culprit, disabling it will produce the same behavior on the remote host as on the local development machine (where proofs worked). This is a reasonable assumption, but differences in GPU architecture (RTX 4000 Ada vs. RTX 5070 Ti), CUDA driver versions, or memory configurations could introduce confounding factors.

Potential Mistakes and Incorrect Assumptions

The most significant risk in this message is that the experiment might produce a false negative — proofs still fail even with PCE disabled, leading the assistant to incorrectly rule out the PCE path. This could happen if:

  1. The CUZK_DISABLE_PCE flag is not properly wired through the codebase, so setting it has no effect.
  2. The service caches PCE data (e.g., serialized PreCompiledCircuit files on disk) and reuses them even when PCE is "disabled."
  3. The service restart does not fully clear GPU state (e.g., CUDA contexts, pinned memory allocations), and residual corruption from previous PCE runs affects the non-PCE path.
  4. The bug is actually in code that is shared between the PCE and non-PCE paths, such as the partitioned proof pipeline or the GPU prover interface. Conversely, a false positive is also possible: proofs start passing, but the improvement is coincidental (e.g., the restart cleared a transient GPU state issue unrelated to PCE). The assistant's phrasing — "to test if PCE is the culprit" — reveals appropriate scientific caution. The word "if" acknowledges uncertainty. The experiment is framed as a test, not a confirmation.

Input Knowledge Required

To fully understand this message, one needs:

  1. The architecture of the CuZK proving engine: That it supports two synthesis paths — the standard bellperson path (full circuit synthesis with LinearCombination evaluation) and the PCE fast path (pre-computed constraint structure with sparse MatVec). That the CUZK_DISABLE_PCE environment variable controls which path is used.
  2. The systemd service management model: That services are defined in unit files under /etc/systemd/system/, that environment variables can be set via Environment= directives, that systemctl daemon-reload is required after editing unit files, and that systemctl restart stops and starts the service cleanly.
  3. The remote debugging setup: That the assistant has SSH access to 10.1.16.218 with passwordless sudo, that the service runs as the curio user, and that the service binary is at /usr/local/bin/cuzk.
  4. The history of the PCE implementation: That the team recently extended PCE to support all proof types, that a WindowPoSt crash was fixed by harmonizing RecordingCS with WitnessCS, and that these changes were deployed to the remote host.
  5. The proof failure symptom: That partitioned PoRep proofs are failing with 0/10 valid partitions, that this is a 100% failure rate, and that the local development machine (single GPU) produces correct proofs.

Output Knowledge Created

This message creates several pieces of knowledge:

  1. A documented experimental result: The service restarted successfully with PCE disabled. The status output confirms the new PID and active state. This becomes the baseline for the next round of observations.
  2. A controlled perturbation of the system: By toggling the PCE flag, the assistant creates a before/after comparison point. The next message will show whether proof success rates change.
  3. Confirmation of operational procedures: The SSH command chain works correctly — the sed edit, daemon-reload, restart, and status check all succeed without errors. This validates the deployment workflow for future experiments.
  4. A narrowed hypothesis space: Regardless of the outcome, this experiment reduces the set of possible root causes. If proofs pass, the bug is in the PCE path. If they still fail, the bug is in the shared pipeline infrastructure or the environment.

The Thinking Process Visible in the Message

While the message itself is terse — a single command with its output — the thinking process is visible in the structure of the action:

The choice of diagnostic tool: The assistant uses CUZK_DISABLE_PCE=1 rather than, say, rebuilding the binary with debug assertions, adding verbose logging, or running a unit test. This reveals a preference for runtime configuration changes over code modifications — faster to deploy, easier to revert, and less likely to introduce new bugs.

The placement of the environment variable: The sed command inserts the new Environment= line immediately after the LD_LIBRARY_PATH line, preserving the existing structure. This is a deliberate choice to minimize disruption to the unit file.

The command chaining: The assistant chains sed, daemon-reload, restart, and status in a single SSH command, using && to ensure each step succeeds before proceeding. This reveals an understanding that the steps are dependent — restarting without reloading would use the old configuration, and checking status without restarting would show the old process.

The output selection: The assistant pipes through head -20 to capture the status output without flooding the conversation. This reveals an awareness of information density — the key data (service is active, new PID, no errors) is in the first few lines.

Conclusion

Message [msg 335] is a textbook example of diagnostic reasoning in a complex system. Faced with a 100% proof failure rate on a remote multi-GPU host, the assistant resists the temptation to continue tracing through source code and instead designs a clean controlled experiment. The CUZK_DISABLE_PCE=1 flag is the perfect tool for this moment: it isolates the PCE variable while keeping every other aspect of the system constant.

The message is brief — a single SSH command and its output — but it carries the weight of dozens of preceding messages of analysis. It is the pivot point where investigation becomes experimentation, where hypothesis becomes test. The next message in the conversation will reveal the outcome, but the significance of this moment lies in the decision itself: the commitment to let the system speak, rather than continuing to interrogate the code.