The All-Partitions-Invalid Message: When Benchmark Success Masks a Deeper Pipeline Bug

Introduction

In distributed proving systems, few failures are as disheartening as the one reported in message [msg 1957] of this coding session. After successfully fixing a deadlock in the ProofShare request pipeline—a victory that required careful surgery on retry logic, queue cleanup, and binary deployment—the user returns with devastating news: the CuZK GPU proving engine is still producing invalid proofs. Not just one or two, but all ten partitions of a PoRep (Proof of Replication) proof are failing verification. The benchmark script passes inside the Docker container, but the production pipeline—run.sh combined with Curio—generates nothing but garbage. This message is the catalyst for the next phase of debugging, one that will ultimately uncover a subtle job ID collision bug at the heart of the concurrent proving system.

The Message in Full

The user's message is a raw dump of CuZK engine logs spanning approximately eight seconds of real time, bookended by a stark error:

[user] Proof requesting fixed now; CuZK - benchmark.sh in container passed, but run.sh + curio still generates bad proofs - 2026-03-13T08:56:22.598610Z  INFO synthesize_partition{job_id="ps-porep-1000-1" partition=8}: cuzk_core::pipeline: partition synthesis complete partition=8 synth_ms=83051
...
2026-03-13T08:56:31.549122Z  WARN cuzk_core::engine: assembler not found, discarding partition result job_id="ps-porep-1000-1" partition=8
CUZK_TIMING: async_dealloc_ms=684
CUZK_TIMING: b_g2_msm_ms=4397 num_circuits=1
curio:error: failed to compute proof: cuzk porep prove failed: cuzk proof failed: PoRep proof self-check failed: assembled proof did not verify (sector=1, miner=1000)

Every partition—0 through 9—is flagged as INVALID by the per-partition verifier. The final self-check confirms the worst: the assembled proof does not verify. The message is terse, but it carries immense diagnostic weight.

Why This Message Was Written: The Context of Desperation

To understand why this message exists, we must understand what preceded it. The conversation had just resolved a critical deadlock in TaskRequestProofs, where CreateWorkAsk would retry HTTP 429 responses indefinitely, blocking the poll loop from discovering matched work and inserting it into the proofshare_queue. The assistant had:

  1. Added an ErrTooManyRequests sentinel to break the infinite retry loop
  2. Implemented progress-based exponential backoff so the system wouldn't hammer the service
  3. Fixed orphan cleanup to preserve fetched work instead of deleting it
  4. Added a routine to purge completed rows older than two days
  5. Built a new Curio binary inside the Docker CUDA environment and deployed it to the remote vast host The user's opening line—"Proof requesting fixed now"—confirms that the deadlock fix worked. The proof request pipeline is functional. But the celebration is immediately cut short: the proofs themselves are bad. This is a fundamentally different class of problem. The pipeline can request proofs, but it cannot produce valid proofs. The user's decision to include the full log output rather than a summary is itself a diagnostic choice. They are providing the raw evidence, trusting that the assistant can parse the timing, the partition IDs, the GPU worker assignments, and the error messages to trace the root cause. The message is a cry for help wrapped in data.

What the Logs Reveal: A Systematic Failure

The log output tells a detailed story. Let us trace the timeline:

  1. 08:56:22 — Partition synthesis completes for partition 8 with synth_ms=83051 (83 seconds of synthesis). The job ID is ps-porep-1000-1, meaning this is a ProofShare PoRep for miner 1000, sector 1.
  2. 08:56:22 — The per-partition verification begins. All ten partitions are checked. Every single one returns INVALID. The summary line is damning: "PER-PARTITION VERIFICATION: 0/10 valid — likely a num_circuits=1 GPU proving bug". The engine itself is speculating about the cause—it suspects a num_circuits=1 GPU proving bug.
  3. 08:56:24 — GPU worker 0 picks up partition 3, completes GPU proving in 14,807ms, but then we see: "assembler not found, discarding partition result job_id=ps-porep-1000-1 partition=0". The partition assembler—the component responsible for collecting and combining partition results—cannot be found for this job ID.
  4. 08:56:31 — GPU worker 1 picks up partition 0, completes in 11,696ms, and again: "assembler not found, discarding partition result job_id=ps-porep-1000-1 partition=8".
  5. Final error — "PoRep proof self-check failed: assembled proof did not verify (sector=1, miner=1000)". The "assembler not found" warnings are the most telling clue. The CuZK engine uses a partition assembler that keys on job_id. When a synthesized partition is ready for GPU proving, the engine looks up the assembler by job ID to route the result. If the assembler is missing, the partition result is discarded. This suggests that multiple concurrent proof requests are using the same job ID, and the assembler for that job ID has already been consumed or cleaned up by the time some partitions arrive.

Input Knowledge Required to Understand This Message

To fully grasp the significance of this message, a reader needs several layers of context:

1. The CuZK proving architecture. CuZK is a GPU-accelerated proving engine for Filecoin proofs. It uses a partitioned pipeline where a proof is split into multiple partitions (here, 10), each synthesized independently and then proven on the GPU. A partition assembler collects the results and combines them into a final proof. The assembler is keyed by job_id.

2. The ProofShare system. ProofShare is a protocol for outsourcing proof generation. Multiple concurrent challenges can target the same sector (miner=1000, sector=1 is a benchmark/test sector). Each challenge generates a proof request with a job_id. If two requests use the same job_id, their partition results can collide.

3. The benchmark.sh vs run.sh distinction. The user notes that benchmark.sh passes inside the Docker container, but run.sh + curio fails. This is a critical clue: benchmark.sh likely runs a single proof request in isolation, while run.sh + curio runs the full production pipeline with concurrent requests. The bug is triggered by concurrency.

4. The num_circuits=1 hint. The engine's own error message speculates about a num_circuits=1 GPU proving bug. This refers to the number of circuits processed in a single GPU batch. With num_circuits=1, each partition is proven individually, which should work—but the engine suspects this configuration might be the cause. This is a red herring, but it shows the engine's own diagnostic limitations.

5. The deployment context. The Curio binary was just rebuilt inside Docker and deployed. The user is running the production pipeline on a remote vast.ai host with CUDA GPUs. The binary was built with the _psfix suffix to identify the build.

Assumptions and Potential Misconceptions

The message contains several implicit assumptions:

Assumption 1: The benchmark.sh passing means the core proving logic is sound. This is the most dangerous assumption. The user (and likely the assistant) initially believed that if the benchmark passes, the GPU proving pipeline is fundamentally correct. The message challenges this by showing that the benchmark environment differs from production in a critical way: concurrency.

Assumption 2: The "num_circuits=1 GPU proving bug" is the real cause. The engine's own log message speculates about this, but it turns out to be a misdirection. The real cause is a job ID collision, not a GPU batch configuration issue.

Assumption 3: The proof request fix is complete. The user opens with "Proof requesting fixed now," implying that the previous work should have resolved the issue. But the problem has merely shifted from the request pipeline to the proving pipeline.

Assumption 4: The Docker build environment is identical to production. The fact that benchmark.sh passes inside Docker but run.sh + curio fails on the same binary suggests environmental differences. The user assumes the binary is correct because it compiled and the benchmark passed.

Mistakes and Incorrect Assumptions Visible in the Message

The most significant mistake is the engine's own diagnostic: "likely a num_circuits=1 GPU proving bug". This is a plausible hypothesis—if the GPU is configured to prove one circuit at a time, perhaps some state is corrupted between partitions. But it is wrong. The real issue is that all ten partitions belong to different proof requests that happen to share the same job_id. The engine sees partition results for ps-porep-1000-1 coming from multiple GPU workers and cannot assemble them correctly because the assembler for that job ID has already been consumed.

The "assembler not found" warnings are the true signal. The engine is discarding partition results because it cannot find the assembler for the job ID. This means the assembler was already removed—likely because another proof request with the same job ID completed and cleaned up the assembler before all partitions from the current request arrived.

Another subtle mistake is the assumption that job_id="ps-porep-1000-1" is unique. The format ps-porep-%d-%d uses miner ID and sector number. Since all ProofShare challenges target the same benchmark sector (miner=1000, sector=1), every concurrent request gets the same job ID. This is the root cause.

Output Knowledge Created by This Message

This message creates several critical pieces of knowledge:

1. The deadlock fix is confirmed working. The user explicitly states "Proof requesting fixed now," validating the previous round of changes.

2. A new bug exists in the proving pipeline. The problem has shifted from proof requesting to proof generation. The system can now request proofs, but it cannot produce valid ones.

3. The bug is concurrency-dependent. The benchmark (single request) passes; the production pipeline (concurrent requests) fails. This isolates the bug to a concurrency issue.

4. The "assembler not found" pattern is the key diagnostic clue. The logs show partition results being discarded because the assembler is missing. This points directly to a job ID collision.

5. All ten partitions fail identically. The failure is not random or intermittent—every partition is invalid. This suggests a systematic issue rather than GPU flakiness or memory corruption.

6. The GPU proving itself completes successfully. The GPU workers report "GPU prove complete (split)" with reasonable timing (11-15 seconds per partition). The GPU hardware and drivers are functioning. The problem is in the assembly/logic layer, not the GPU computation.

The Thinking Process Visible in the Message Structure

The user's decision to include the full log rather than a summary reveals their thinking: they want the assistant to see the raw data, not a filtered interpretation. The log is organized chronologically, showing the exact sequence of events. The user is effectively saying, "Here is everything that happened. Find the pattern."

The inclusion of the engine's own speculation ("likely a num_circuits=1 GPU proving bug") is interesting. The user might be offering this as a hypothesis, or they might be showing it as a red herring. Either way, they are providing the engine's self-diagnosis as part of the evidence.

The timing information is also significant. The user includes timestamps down to the microsecond, allowing the assistant to trace the exact sequence of GPU worker assignments and partition completions. This level of detail suggests the user understands that timing is critical—the "assembler not found" error likely occurs because one proof request finishes and cleans up before another request's partitions arrive.

The Broader Significance

This message represents a classic debugging scenario in distributed systems: a fix that works in isolation but fails under concurrency. The deadlock fix addressed a serialization problem (one task blocking forever), but it revealed a parallelism problem (multiple tasks using the same identifier). The two bugs are related only in that they both affect the ProofShare pipeline, but they operate at different levels of the system.

The message also illustrates the importance of production logging. Without the detailed CuZK logs showing partition-by-partition verification results, GPU worker assignments, and the "assembler not found" warnings, the root cause would be nearly impossible to find. The logs tell a story: synthesis works, GPU proving works, but assembly fails because the assembler is missing.

Conclusion

Message [msg 1957] is a pivot point in this coding session. It marks the transition from fixing the proof request pipeline to fixing the proof generation pipeline. The user provides a wealth of diagnostic data—timestamps, partition IDs, GPU worker assignments, verification results, and error messages—that collectively tell the story of a job ID collision bug. The engine's own speculation about a num_circuits=1 bug is a red herring; the real culprit is the shared job_id across concurrent proof requests targeting the same benchmark sector.

This message is a testament to the complexity of debugging distributed GPU proving systems. A fix that works in the benchmark environment (single request) fails in production (concurrent requests). The logs reveal the pattern, but only to someone who understands the architecture: the partition assembler keys on job ID, and when multiple requests share the same job ID, their partition results collide and are discarded. The next phase of debugging will trace this exact issue, leading to the fix that adds the harmony task ID to the RequestId, making it unique per invocation.