Reading the Benchmark Script: A Diagnostic Deep Dive into a Failed GPU Proving Benchmark

Introduction

In the course of operating a distributed Filecoin proving network on Vast.ai GPU instances, a newly deployed machine equipped with an RTX PRO 4000 GPU failed its benchmark almost immediately after deployment. The instance ran for approximately ten minutes, downloaded cryptographic parameters, then exited with an error, producing zero proofs per hour. The vast-manager system, which orchestrates these instances, automatically killed the machine and marked it for destruction. But the question remained: why did the benchmark fail? Message [msg 1482] captures a single moment in the diagnostic process—a read operation that examines a specific section of the benchmark shell script responsible for restarting the proving daemon between the warmup and benchmark phases. Though seemingly mundane, this message reveals the layered reasoning, shifting assumptions, and methodical investigation that characterize operational debugging in complex distributed systems.

The Message Itself

The subject message is a straightforward read tool call issued by the assistant:

[assistant] [read] /tmp/czk/docker/cuzk/benchmark.sh

298: # If we started with reduced partition workers for warmup, restart with 299: # full workers for the benchmark. Skip restart if daemon was already at 300: # full partition_workers (PCE existed at startup). 301: if [[ "$NO_START" == false && -n "$WARMUP_PW" ]]; then 302: echo "" 303: echo "Restarting daemon with full partition_workers=$PARTITION_WORKERS for benchmark..." 304: star...

The assistant is reading lines 298–304 of the benchmark.sh script, which handles the transition from the warmup phase to the actual benchmark phase. The script logic checks whether the daemon was started with reduced partition workers during warmup (which happens when no PCE cache exists, to avoid OOM), and if so, restarts it with the full partition worker count for the actual benchmark run.

Why This Message Was Written: The Diagnostic Context

To understand why the assistant read this specific section of code, we must trace the investigation that led here. The story begins in [msg 1475], where the user posted logs from a newly deployed instance (label C.32733029, a 1x RTX PRO 4000 with 504 GB RAM). The logs showed a clean parameter fetch completing in about four minutes, followed by the entrypoint starting the benchmark with 12 proofs, concurrency 3, and 16 partition workers. Then, at the 10-minute mark: "benchmark.sh exited with error." The benchmark result was zero proofs per hour, well below the minimum rate of 29.0, and the instance was killed.

The assistant's first hypothesis, stated in [msg 1476], was that the failure was "likely the same curio-can't-connect-to-lotus issue (port 1234 not tunneled)." This was a reasonable assumption: in the previous chunk of work ([chunk 9.0]), the assistant had discovered that the portavailc tunnel on worker instances was not forwarding port 1234 (hosting the Lotus API), causing curio to fail at startup. The fix had been applied to the entrypoint script and the Docker image rebuilt and pushed. However, the assistant recognized that this particular instance might have been deployed before the fix or pulled a cached image.

But as the investigation deepened, this hypothesis began to unravel. In [msg 1477], the assistant examined the instance logs more carefully, looking at the tail of the log stream. The logs showed the parameter download completing successfully, but the actual benchmark output was not visible in the snippet—only the setup phase logs appeared. This prompted the assistant to examine the benchmark script itself.

In [msg 1478], the assistant read the beginning of benchmark.sh to understand its structure. The script's header comments revealed it was a "PoRep C2 benchmark for cuzk" that starts a cuzk-daemon, runs a warmup proof, then benchmarks N sequential PoRep proofs. This was important context: the benchmark was not using curio at all—it was a standalone test using cuzk-daemon and cuzk-bench.

Then in [msg 1479], the assistant grepped for relevant patterns (start_daemon, curio.*run, chain, 1234) and found six matches, none of which involved curio or port 1234. The matches were all about start_daemon and partition workers. This was the critical turning point.

In [msg 1480], the assistant read the start_daemon helper function, which handles killing any existing daemon process and starting a new one with a specified partition worker count. And in [msg 1481], the assistant made an explicit realization: "The benchmark doesn't use curio at all — it's a standalone cuzk-daemon + cuzk-bench test. The curio connection issue is separate. The benchmark failed for a different reason."

This realization reframed the entire investigation. The port 1234 tunnel theory was wrong. The assistant now needed to understand how the benchmark script actually worked, and specifically how it handled the daemon lifecycle during the warmup-to-benchmark transition. That is precisely what led to [msg 1482]—the subject message.

What the Assistant Was Looking For

The assistant read lines 298–304 of benchmark.sh to understand the daemon restart logic. This section handles the case where the daemon was started with reduced partition workers during warmup (to avoid OOM when no PCE cache exists) and needs to be restarted with full workers for the actual benchmark. The key variables are:

$WARMUP_PW: The reduced partition worker count used during warmup when no PCE cache is present.
$PARTITION_WORKERS: The full partition worker count for normal operation.
$NO_START: A flag controlling whether the daemon is managed by the script at all. The assistant was looking for potential failure points in this restart logic. If the daemon failed to restart properly—if the kill signal didn't work, if the new daemon process crashed during startup, if the partition worker count was misconfigured—that could explain the "exited with error" message and the zero-proof result.

Assumptions and Their Revision

This message is a beautiful example of how operational debugging requires constant revision of assumptions. Let's trace the evolution:

Initial assumption ([msg 1476]): The failure was the same port 1234 tunnel issue that had plagued earlier instances. This was the most parsimonious explanation—a known bug with a known fix, and the instance might simply have been deployed with a stale image.

Revised assumption ([msg 1478]): After reading the benchmark script header, the assistant realized the benchmark was a standalone cuzk-daemon process, not a curio process. The port 1234 tunnel issue was specific to curio's need to connect to a Lotus API endpoint. The benchmark used cuzk-daemon which communicates via its own protocol on a different port.

Refined assumption ([msg 1481]): Explicitly stated: "The benchmark doesn't use curio at all." This was a significant correction. The assistant had been operating under a mistaken hypothesis and had to abandon it.

New investigative direction ([msg 1482]): With the curio theory discarded, the assistant focused on the daemon lifecycle within the benchmark script itself. The warmup phase, the daemon restart, the partition worker configuration—any of these could be the source of the failure.

Input Knowledge Required

To fully understand this message, several pieces of prior knowledge are essential:

The architecture of the proving system: The assistant knows that cuzk-daemon is a standalone GPU proving daemon that performs PoRep (Proof of Replication) C2 computations. It operates independently of curio, which is a separate service that coordinates proving tasks across the Filecoin network.
The PCE cache and warmup strategy: Previous work in segment 8 had established that when no PCE (Pre-Compiled Constraint Evaluator) cache exists, the daemon must perform PCE extraction during the first proof, which is memory-intensive. To avoid OOM on low-RAM instances, the benchmark script uses reduced partition workers during warmup, then restarts with full workers for the actual benchmark. This is the logic the assistant is reading.
The partition worker concept: Partition workers control how many GPU compute partitions are used concurrently. Higher values increase throughput but also increase memory pressure. The dynamic configuration based on available RAM was a key innovation from earlier segments.
The vast-manager system: The assistant knows that the manager monitors instances, collects logs, and automatically kills instances that fail to meet their minimum benchmark rate. The instance in question was already killed by the time the assistant investigated.
The benchmark script's error handling: The assistant needs to understand how benchmark.sh reports errors. The entrypoint log said "benchmark.sh exited with error," but the actual error message from the script was not captured in the log snippet. The assistant was looking for where errors might be generated.

Output Knowledge Created

This message, combined with the surrounding investigation, produced several important pieces of knowledge:

The benchmark failure was NOT the port 1234 tunnel issue. This was a critical negative finding. The assistant had to rule out the most obvious explanation before looking deeper.
The benchmark uses a standalone cuzk-daemon, not curio. This means the failure is in the GPU proving pipeline itself, not in the coordination layer.
The daemon restart logic is a potential failure point. The transition from warmup (reduced partition workers) to benchmark (full partition workers) involves killing and restarting the daemon process. If this restart fails silently, the benchmark would produce zero proofs.
The investigation was still in progress. The read operation in [msg 1482] was not the end of the diagnostic process—it was a step toward understanding the restart logic. The assistant would need to read more of the script to see how errors are propagated and whether the restart failure would be caught.

The Thinking Process Visible in the Message

While the message itself is just a read operation, the surrounding messages reveal a clear thinking process:

The assistant is methodically working through the benchmark script from top to bottom, reading relevant sections as they become pertinent. The pattern is: form a hypothesis, test it by reading code, refine the hypothesis based on new information, read more code. This is classic debugging methodology applied to a distributed system where direct access to the failed instance is impossible (it was already killed).

The assistant is also managing multiple potential explanations simultaneously. Even as it reads the daemon restart logic, it hasn't fully committed to this being the cause—it's gathering information to evaluate whether this path could produce the observed symptoms.

Conclusion

Message [msg 1482] captures a single, quiet moment in a larger diagnostic investigation. On its surface, it is merely a developer reading a few lines of a shell script. But in context, it represents a pivot point: the abandonment of a plausible but incorrect hypothesis (the port 1234 tunnel issue) and the beginning of a deeper inquiry into the actual behavior of the GPU proving daemon during benchmark execution. The message demonstrates that even the simplest tool operations—a file read, a grep, a log inspection—are embedded in a rich tapestry of reasoning, assumption-testing, and knowledge accumulation. In operational debugging, the most important work often happens in the transitions between tool calls, where hypotheses are formed, tested, and revised.