The Build Cache Breakthrough: Deploying a Unique Job ID Fix to a Production GPU Proving System

Introduction

In the midst of debugging a critical production bug in a distributed GPU proving system, one short message marks a pivotal turning point. The assistant writes:

Now it shows ps-porep-%d-%d-%d — three format specifiers. Upload and deploy: ``bash scp -P 40362 /tmp/curio-psfix3 root@141.195.21.72:/tmp/curio-psfix3 2>&1 ``

This message, at first glance, appears to be a routine deployment command. But it represents the culmination of a frustrating debugging session where a seemingly simple code change—adding a third %d format specifier to a job identifier string—was repeatedly thwarted by Docker's Go build cache. The message is the moment of triumph after correctly diagnosing why previous builds silently produced stale binaries, and it initiates the deployment of a fix that resolves a catastrophic production bug: job ID collisions in a concurrent GPU proving pipeline.

The Production Bug: When Identical Job IDs Corrupt Proofs

To understand the weight of this message, one must understand the bug it fixes. The ProofShare system in the Curio Filecoin proving stack allows multiple concurrent proving tasks to target the same sector. All these tasks were constructing their cuzk RequestId using the format fmt.Sprintf("ps-porep-%d-%d", miner, sector). Because every proofshare challenge targets a hardcoded bench sector (miner=1000, sector=1), every concurrent task produced the identical job ID string ps-porep-1000-1.

The cuzk GPU proving engine used this job_id as a key in its partition assembler's HashMap. When multiple tasks submitted different partitions with the same job_id, the engine would attempt to insert partition results from different proofs into the same slot, triggering a panic: "partition 0 already inserted". This meant that all ten PoRep partitions were producing invalid proofs—a complete failure of the proving pipeline.

The fix was conceptually trivial: add the harmony task ID to the format string, producing fmt.Sprintf("ps-porep-%d-%d-%d", miner, sector, taskID). This would make every concurrent task's RequestId unique, preventing the partition collision.

The Build Cache Nightmare

The assistant had already built and deployed a fix twice before this message. The first attempt (curio-psfix) used Docker's --volumes-from mechanism to copy modified source files into a builder container. The second attempt (curio-psfix2) added touch commands to the build script to bust the Go build cache. Both attempts failed silently.

The user reported that cuzk logs still showed ps-porep-1000-1 without the task ID. The assistant confirmed the failure by grepping the deployed binary for the format string:

grep -ao "ps-porep-%d-%d[^\"]*" /usr/local/bin/curio

This returned ps-porep-%d-%d—only two %d specifiers. The binary was identical to the original, proving that the Go compiler had not recompiled the modified source file.

The Root Cause: Understanding Docker Volume Mounts

The breakthrough came from understanding why --volumes-from failed. The docker cp command copies files into a container's writable layer. However, docker run --volumes-from only mounts volumes explicitly declared in the Dockerfile via VOLUME directives—it does not share the container's entire filesystem overlay. The curio-builder Docker image had no VOLUME directive for /build, so the copied source files were invisible to the build container. The Go build cache, stored in a separate Docker layer, still had the old compiled artifacts and reused them without recompilation.

The assistant switched to direct bind mounts using -v:

docker run --rm \
  -v /tmp:/output \
  -v /tmp/czk/tasks/proofshare/task_prove.go:/build/tasks/proofshare/task_prove.go \
  -v /tmp/czk/tasks/proofshare/task_request.go:/build/tasks/proofshare/task_request.go \
  -v /tmp/czk/lib/proofsvc/provictl.go:/build/lib/proofsvc/provictl.go \
  ...

Bind mounts override files in the container's filesystem at the kernel level, ensuring the build process sees the modified source files. This forced Go to detect the changes, invalidate the build cache for the affected packages, and recompile them. The resulting binary contained the correct format string.

The Verification: Grepping the Binary

The build script included an inline verification step that grepped the output binary for the format string pattern:

grep -ao "ps-porep-%d-%d[^\"]*" /output/curio-psfix3 | head -3

This grep command searches the raw binary for any occurrence of ps-porep-%d-%d followed by any non-quote characters. The -a flag treats the binary as text, -o prints only the matching portion. By checking for the two-%d pattern, the assistant could confirm whether the old format string still existed in the binary. When this grep returned ps-porep-%d-%d-%d instead, it confirmed the fix was genuinely compiled in.

The Deployment Strategy

With the verified binary in hand, the assistant initiates deployment via scp to the remote production host. The deployment required careful orchestration: the running curio process had to be killed, the old binary moved aside, the new binary copied into place, and the process restarted. Earlier attempts to chain these steps with kill and mv in a single SSH command had failed because the running process held a file lock on the binary, preventing the move. The assistant learned to separate the steps, verifying the process had stopped before replacing the binary.

Assumptions and Lessons

Several assumptions were made during this debugging process. The assistant initially assumed that docker cp combined with --volumes-from would make modified files available to the build container—an assumption that proved incorrect due to Docker's volume semantics. The assistant also assumed that touch would bust the Go build cache, but this failed because the files being touched were in an invisible layer. The key lesson is that Docker's build cache and filesystem layering can silently defeat source modifications, and the only reliable way to inject changes is through bind mounts that operate at the filesystem level.

Knowledge Inputs and Outputs

Input knowledge required to understand this message includes: Docker container filesystem layering and volume semantics, Go build cache invalidation mechanics, the cuzk GPU proving engine's job ID architecture, the ProofShare system's concurrent task model, and the production deployment workflow for the Curio proving stack.

Output knowledge created by this message includes: a verified fix for the job ID collision bug, a hardened deployment procedure that validates binary contents before deployment, and a documented technique for injecting source changes into Docker-based Go builds without full image rebuilds.

The Thinking Process

The assistant's reasoning chain is visible in the progression of failed attempts. Each failure was met with a diagnostic step—grepping the binary, checking version strings, examining Docker volume behavior—that narrowed down the root cause. The shift from --volumes-from to bind mounts represents a deep understanding of Docker's filesystem semantics. The inline binary grep in the build script demonstrates a defensive verification mindset: don't trust the build succeeded, prove it by examining the output. This message, though brief, is the culmination of that systematic debugging process—the moment where all the pieces finally aligned and a correct binary was produced.

Conclusion

Message 2006 is a study in the hidden complexity of deploying code changes in containerized build environments. A one-line code change—adding %d to a format string—required three build attempts, a deep understanding of Docker volume semantics, and a verification step that grepped raw binary output. The message captures the moment of breakthrough after a frustrating debugging session, and it initiates the deployment of a fix that restores correct operation to a production GPU proving system handling concurrent proof challenges. It is a reminder that in distributed systems engineering, the build and deployment pipeline is as critical as the application code itself, and that the simplest fixes can be the hardest to deploy correctly.