When the Benchmark Breaks: A Real-World Failure Teaches Hard Lessons About Assumptions in Distributed Systems

Introduction

In software engineering, there is a vast gulf between "it works on my machine" and "it works in production." The gap is filled with assumptions—implicit beliefs about the environment, configuration, and behavior that the developer holds but the deployment environment does not honor. Message 675 of this opencode session captures that gap in vivid detail. It is a user message containing the raw terminal output of running a freshly built benchmark script on a remote vast.ai GPU instance. The script fails in multiple, illuminating ways. This single message is a case study in how assumptions compound into failures, how real-world deployment exposes design blind spots, and how the most valuable debugging information often comes not from logs but from the user's own investigative commands typed at the shell prompt.

Context: What Led to This Message

To understand message 675, we must understand what came before it. The opencode session spans five segments of intense engineering work. The assistant has been building a Docker container (curio-cuzk) for Filecoin proving workloads using the CuZK GPU proving engine. The container bundles curio, sptool, cuzk-daemon, and cuzk-bench binaries with CUDA 13 supraseal support. Over the course of the session, the assistant resolved multiple build blockers: a pip conflict in the SPDK build system, a missing LIBRARY_PATH entry for libcudart_static.a, missing runtime libraries (libconfig++, libaio, libfuse3, libarchive), and a spurious StorageMetaGC error in curio.

In the immediate lead-up to message 675, the user requested a benchmark.sh script ([msg 634]) that would benchmark PoRep proofs using cuzk. The assistant researched the cuzk codebase, studied the cuzk-bench binary's CLI interface, examined the e2e test script, and identified a downloadable C1 test data file (~51MB) from a public R2 bucket. The resulting script was designed to: download C1 test data if absent, start cuzk-daemon, run a warmup proof to trigger PCE extraction, run N benchmark proofs, and report timing metrics. The user then pushed the Docker image to Docker Hub and deployed it on a vast.ai instance. Message 675 is the first real execution of that script on a remote host.

The Message Itself: A Play-by-Play of Failure

The message begins with the user pasting the terminal output of running benchmark.sh on a vast.ai instance identified as C.32627837. The output is a cascade of partial successes and hard failures.

Phase 1: Setup succeeds. The C1 output file is not found at /data/32gbench/c1.json, so the script downloads it—all 50MB—successfully. The daemon starts on 127.0.0.1:9820 with PID 1048. So far, everything works.

Phase 2: Warmup fails. The script prints "PCE file not found — warmup will trigger extraction. This takes 2-5 minutes on first run..." Then it submits a single PoRep proof. The result:

status:    FAILED
job_id:    10b7f303-092a-420e-baf5-fc1d9940b8a6
error:     C1 parse failed: SRS param file not found for Porep32G: /data/zk/params/v28-stacked-proof-of-replication-...

The warmup "completed" in 1 second—far too fast for actual PCE extraction, which takes 2-5 minutes. The script then warns that the PCE file was not found after warmup, adding a hopeful parenthetical: "(this may be OK if the daemon uses a different param_cache)."

Phase 3: Benchmark run fails differently. The script attempts to run 5 PoRep proofs with concurrency 1, but cuzk-bench batch immediately errors:

error: unexpected argument '-n' found

Usage: cuzk-bench batch [OPTIONS] --type <PROOF_TYPE>

The script is passing a -n argument that the cuzk-bench batch subcommand does not accept.

Phase 4: The user investigates. After the script stops the daemon and exits, the user types two commands at the shell prompt. ls /data/ shows only 32gbench. ls /var/tmp/filecoin-proof-parameters/ | head shows a list of verification keys and SRS files—but notably, the output ends with a telling comment: -- fetch needs to set FIL_PROOFS_PARAMETER_CACHE=/data/zk/params. This comment is the user's own diagnosis, typed directly into the terminal as a note to self (and to the assistant).

The Assumptions That Failed

This message is a graveyard of assumptions. Let me enumerate them.

Assumption 1: The param cache path is consistent. The benchmark script uses /var/tmp/filecoin-proof-parameters as the default param cache directory. This is the standard default in the Filecoin proving ecosystem. However, the vast.ai instance has its proving parameters stored at /data/zk/params. The curio fetch-params command (run by the on-start script, which runs in the background) downloaded parameters to the default location, but the SRS parameters needed for PoRep proving—specifically the 32GiB stacked-proof-of-replication parameter file—are not present there. The error message reveals that cuzk-daemon is looking for the SRS param file at /data/zk/params/..., not at /var/tmp/filecoin-proof-parameters/.... This means either the daemon was configured with a different FIL_PROOFS_PARAMETER_CACHE, or the param fetch command was run with a different environment variable than the daemon uses.

Assumption 2: The -n argument exists. The benchmark script was written to pass a -n flag to cuzk-bench batch, presumably to specify the number of proofs. But the actual CLI parser rejects this argument. The assistant had researched the cuzk-bench binary earlier ([msg 635]), reading its full source code and CLI definition. Yet the script still contains a flag that doesn't exist. This suggests either the research missed the exact argument name, or the script was written before the research was complete and never corrected.

Assumption 3: The warmup would trigger PCE extraction. The script's logic hinges on the idea that submitting one proof with no PCE file present will cause the daemon to extract the pre-compiled circuit. But the warmup proof failed during C1 parsing—it never reached the point where PCE extraction would be triggered. The SRS parameter file was missing, so the proof pipeline failed before it could begin the GPU proving phase that requires PCE. The script's warning message ("PCE file not found after warmup") is correct but misleading: it implies the extraction might have happened elsewhere, when in fact it never happened at all.

Assumption 4: The environment is self-consistent. The script assumes that if it starts the daemon with a certain param cache path, the daemon will use that path consistently. But the error message shows the daemon looking for SRS params at /data/zk/params, suggesting that either the daemon was compiled with a hardcoded path, or the environment variable FIL_PROOFS_PARAMETER_CACHE was set differently in the daemon's process environment than in the script's environment.

The User's Contribution: Debugging Beyond the Script

One of the most instructive aspects of this message is what happens after the script fails. The user doesn't just paste the error and wait for help. They investigate. They run ls to check what's actually on disk. They look at the param cache directory. And crucially, they add a comment at the end of the output: -- fetch needs to set FIL_PROOFS_PARAMETER_CACHE=/data/zk/params.

This comment is the user's hypothesis about the root cause. It reveals that the user understands the Filecoin proving ecosystem well enough to know that FIL_PROOFS_PARAMETER_CACHE controls where the daemon looks for parameter files. They've identified that the param fetch (run by the entrypoint script) downloaded to the default location, but the daemon expects params at /data/zk/params. The fix is to ensure the environment variable is set consistently.

This is a beautiful example of the collaborative debugging dynamic that makes opencode sessions effective. The user is not a passive consumer of the assistant's work—they are an active participant who runs experiments, interprets results, and forms hypotheses. The assistant, in turn, receives rich diagnostic data that includes not just the error messages but the user's own investigative output and their articulated theory of the problem.

Input Knowledge Required to Understand This Message

To fully grasp what this message communicates, a reader needs:

  1. Knowledge of the Filecoin proving pipeline. The distinction between C1 (circuit construction) and C2 (GPU proving) is essential. The error "C1 parse failed" means the circuit could not be constructed because the SRS (Structured Reference String) parameters were missing. Understanding that PoRep (Proof of Replication) requires a 32GiB parameter file explains why the warmup failed instantly rather than taking 2-5 minutes for PCE extraction.
  2. Knowledge of the CuZK/cuzk architecture. The PCE (Pre-Compiled Constraint Evaluator) is an optimization that pre-compiles the circuit constraints for faster GPU proving. The benchmark script's warmup phase is designed to trigger PCE extraction, which only happens after a successful first proof. If the first proof fails before reaching the GPU stage, no PCE is generated.
  3. Knowledge of the vast.ai environment. Vast.ai is a GPU rental marketplace where instances come with pre-configured storage paths. The user's instance has /data/ as a large storage volume, and the proving parameters were presumably fetched there by a previous setup script. The on-start entrypoint runs in the background, so curio fetch-params may still be running when the user SSHes in and runs benchmark.sh.
  4. Knowledge of the Docker build process. The Docker image was built with specific paths for binaries and configuration. Understanding that FIL_PROOFS_PARAMETER_CACHE defaults to /var/tmp/filecoin-proof-parameters in the Docker image, but the vast.ai instance has params at /data/zk/params, explains the mismatch.
  5. Knowledge of CLI argument parsing. The -n error indicates that cuzk-bench batch uses a different argument syntax than what the script provides. This requires understanding that CLI tools can have subcommand-specific argument sets, and that cuzk-bench batch may use --num-proofs or -N instead of -n.

Output Knowledge Created by This Message

This message generates several important pieces of knowledge:

  1. Empirical evidence of a param cache path mismatch. The error message explicitly shows the daemon looking for SRS params at /data/zk/params/..., confirming that the daemon's FIL_PROOFS_PARAMETER_CACHE is set to /data/zk/params, not the default /var/tmp/filecoin-proof-parameters.
  2. Empirical evidence of a CLI bug. The -n argument error is a concrete bug in the benchmark script that must be fixed before the script can run.
  3. Empirical evidence that the warmup logic is insufficient. The warmup completed in 1 second and did not produce a PCE file. This shows that the script's assumption—that submitting a proof with no PCE triggers extraction—is only valid if the proof pipeline succeeds. The script needs to check whether the warmup proof actually succeeded, not just whether it completed.
  4. A user-generated hypothesis. The comment at the end of the output—"fetch needs to set FIL_PROOFS_PARAMETER_CACHE=/data/zk/params"—is a piece of diagnostic knowledge that the assistant can act on. It points directly to the root cause of the SRS param file error.
  5. A richer understanding of the deployment environment. The output reveals that the vast.ai instance has a pre-existing /data/zk/params directory with Filecoin proving parameters. This means the instance was previously used for Filecoin proving, and the parameters were fetched to a non-standard location. The Docker container's default param cache path conflicts with this existing setup.

The Thinking Process Revealed

While this is a user message (not an assistant message with explicit reasoning), the thinking process is visible in the structure of the output itself. The user's decision to paste the full terminal output—including the investigative commands they ran afterward—reveals a methodical debugging approach:

  1. Run the script and observe. First, run benchmark.sh and capture everything.
  2. Check the filesystem. When the script fails, check what's actually on disk with ls.
  3. Check the param cache. Look at what parameters are present and what's missing.
  4. Form a hypothesis. The user notices the daemon looked for params at /data/zk/params but the cache is at /var/tmp/filecoin-proof-parameters. They articulate this as "fetch needs to set FIL_PROOFS_PARAMETER_CACHE=/data/zk/params."
  5. Share the full context. Paste everything—successes, failures, investigations, and hypothesis—so the assistant has complete information. This is expert-level debugging behavior. The user doesn't just report "it failed." They provide the raw data, their intermediate findings, and their best guess at the root cause. This makes the assistant's job dramatically easier: instead of asking clarifying questions ("What's in your param cache? What error did you get?"), the assistant can immediately start working on fixes.

The Broader Lessons

Message 675 teaches several lessons that extend far beyond this specific session.

First, scripts that work in one environment will fail in another unless environment assumptions are explicitly validated. The benchmark script assumed a standard param cache path, a standard CLI interface, and a standard proof pipeline. The vast.ai instance violated all three assumptions. The fix is not just to change paths but to add validation: check that the param cache contains the required files before starting; test that the CLI arguments are accepted before running; verify that the warmup proof actually succeeded before proceeding.

Second, the user's investigative commands are often more valuable than the script's output. The ls commands the user ran after the script failed revealed the root cause more clearly than the error messages themselves. The script's error said "SRS param file not found." The user's investigation showed why: the params are in a different directory. This is a general principle: automated scripts produce error messages, but human investigators produce diagnoses.

Third, partial failure is harder to debug than total failure. The benchmark script partially succeeded (downloaded C1, started daemon) before failing in two independent ways (warmup proof failed, CLI argument rejected). Multiple simultaneous failures can obscure each other. The user might have fixed the param path only to still hit the -n error, or fixed the -n error only to still have the warmup fail. The assistant needs to address both issues.

Conclusion

Message 675 is a snapshot of the moment when a carefully built system meets an uncooperative reality. The Docker image built cleanly. The binaries compiled. The script was written with care. But the deployment environment had different paths, different configurations, and different expectations. The benchmark script failed not because it was fundamentally wrong, but because it was built on assumptions that did not hold.

The message is also a testament to the power of collaborative debugging. The user didn't just report failure—they investigated, formed hypotheses, and provided rich context. The assistant, in turn, received everything needed to diagnose and fix the issues. The failures in this message are not setbacks; they are data. And in the opencode session that follows, that data will drive the next iteration of fixes, bringing the system closer to something that truly works in the real world.