The Silent Benchmark: When Parameter Fetch Completes but Proving Doesn't Begin

A Status Report That Reveals a Hidden Hardware Constraint

In the middle of a complex deployment session spanning Docker builds, Go service fixes, and Vast.ai instance management, a single user message arrived that captured a critical moment of uncertainty. The message, sent at index 976 of the conversation, reads as follows:

[user] [setup]Status Legend:
[setup](OK):download completed.
[setup]2026-03-12T00:50:48.500Z	INFO	paramfetch	fastparamfetch/paramfetch.go:227	Parameter file /var/tmp/filecoin-proof-parameters/v28-stacked-proof-of-replication-merkletree-poseidon_hasher-8-8-0-sha256_hasher-82a357d2f2ca81dc61bb45f4a762807aedee1b0a53fd6c4e77b46a01bfef7820.params is ok
[setup]2026-03-12T00:50:57.874Z	INFO	paramfetch	fastparamfetch/paramfetch.go:227	Parameter file /var/tmp/filecoin-proof-parameters/v28-proof-of-spacetime-fallback-merkletree-poseidon_hasher-8-8-0-0377ded656c6f524f1618760bffe4e0a1c51d5a70c4509eedae8a27555733edc.params is ok
[setup]2026-03-12T00:50:57.874Z	INFO	paramfetch	fastparamfetch/paramfetch.go:251	parameter and key-fetching complete
[setup][entrypoint] 00:50:58 Parameter fetch complete.
[setup][entrypoint] 00:50:58 Signaled param-done
[setup][entrypoint] 00:50:58 Starting benchmark: 12 proofs, concurrency 5, partition-workers 10 -- setup says benchmark start, but there are no benchmark logs seemingly, also no bench in nvidia smi

This message appears unremarkable at first glance—a simple status update from a remote instance. But it is anything but simple. It represents the culmination of hours of debugging, the first end-to-end test of a newly fixed deployment pipeline, and the moment when a subtle hardware constraint first announced itself. To understand why this message matters, one must understand the intricate chain of events that led to it and the assumptions embedded in its seemingly straightforward observations.

The Context: A Deployment at the Edge of Failure

The message arrives at a pivotal moment in the session. The assistant had just completed a major fix to the vast-manager service—a Go-based management daemon that orchestrates worker instances on the Vast.ai marketplace. The critical bug was in the monitor's instance matching logic: it was matching database instances to Vast API instances solely by the API's label field, which remains null unless explicitly set via vastai label. Meanwhile, the actual instances were reporting their identity through a VAST_CONTAINERLABEL environment variable set to patterns like C.32710471. This mismatch caused the monitor to incorrectly kill perfectly healthy instances (<msg id=957-958>).

The fix introduced an ID-based fallback map (idMap) that extracts the Vast instance ID from the C.<id> label pattern, ensuring correct matching across all lifecycle operations: disappearance checks, timeout killing, failed benchmark detection, bad host handling, and dashboard data merging. The fix was deployed, the Docker image was rebuilt and pushed, and a new instance—32710471 (2x RTX 3090, BC Canada, 125GB RAM, $0.38/hr)—was created using the --ssh --onstart-cmd workaround to run the lifecycle entrypoint alongside SSH access (<msg id=960-974>).

By the time this message was written, the instance had been running for some time. The parameter download—a multi-gigabyte fetch of Filecoin proof parameters—had completed successfully. The entrypoint had signaled param-done to the vast-manager API, and had begun the benchmark phase. And then... nothing. Or at least, nothing visible.

Input Knowledge: What You Need to Understand This Message

To parse the significance of this message, a reader needs substantial context about the system being deployed. First, one must understand the CuZK proving pipeline: it is a GPU-accelerated zero-knowledge proof system for Filecoin, involving pre-compiled constraint evaluators (PCE), partition workers that split proof work across GPU cores, and a warmup phase where the first proof is synthesized without cached parameters. Second, one must know the lifecycle managed by entrypoint.sh: the script progresses through paramfetch (download cryptographic parameters), benchmark (run a set of trial proofs to measure performance and register with the network), and finally curio run (the main proving daemon). Third, one must understand the Vast.ai environment: instances are rented GPU machines where the Docker ENTRYPOINT is replaced by Vast's own init script when using --ssh mode, requiring the --onstart-cmd workaround to run the lifecycle script in the background.

The message itself contains several technical artifacts. The timestamps show the parameter fetch completing at 00:50:57 UTC, with the entrypoint reacting at 00:50:58. The parameter files listed are specific to Filecoin's proof system: v28-stacked-proof-of-replication (PoRep) and v28-proof-of-spacetime-fallback (WindowPoSt). The benchmark configuration—"12 proofs, concurrency 5, partition-workers 10"—reveals the proving strategy: 12 trial proofs run with 5 concurrent workers, each using 10 partition workers to split the GPU work.

The User's Reasoning and Motivation

The user wrote this message because they observed a discrepancy between expectation and reality. The expectation, encoded in the entrypoint script, was that the benchmark would produce visible output—log lines showing proof progress, GPU utilization visible in nvidia-smi. The reality was silence. The user's phrasing—"setup says benchmark start, but there are no benchmark logs seemingly, also no bench in nvidia smi"—is a concise problem report, but it carries layers of implicit reasoning.

The user is performing a sanity check. They have been through multiple rounds of debugging: the VAST_CONTAINERLABEL mystery, the monitor matching bug, the Docker build blockers, the entrypoint hardening. Each previous issue was resolved, and this new instance was supposed to be the first clean run of the fixed pipeline. When the benchmark appeared to start but produced no visible activity, the user's instinct was to flag it immediately rather than wait for a timeout. This reflects the operational mindset developed over the course of the session: trust nothing, verify everything, and report anomalies the moment they appear.

The user also assumes that "no benchmark logs" and "no bench in nvidia smi" are reliable indicators of a problem. This assumption is reasonable but not necessarily correct. The benchmark script might produce output to a different log file, or the GPU work might be scheduled but not yet visible, or the process might have crashed silently before producing any output. The user's message is essentially a request for investigation: "Something is wrong here, can you figure out what?"

Assumptions and Their Hidden Flaws

The message rests on several assumptions, some of which turn out to be incorrect or incomplete. The most significant assumption is that the absence of visible benchmark activity means the benchmark is not running. In reality, as revealed later in the session ([chunk 7.1]), the benchmark did start, but the process was killed by the Linux Out-Of-Memory (OOM) killer before it could produce any meaningful output or GPU activity. The 125GB RAM on the BC Canada host proved insufficient for the initial proof synthesis when using 10 partition workers with an uncached PCE, causing organic memory allocation to exceed available resources.

This is a subtle failure mode. The benchmark process doesn't crash with a clear error message—it is silently terminated by the kernel. No benchmark logs are written because the process never reaches the logging stage. No GPU activity appears because the process is killed before it can submit work to the GPU. To an external observer, it looks exactly like the benchmark never started, when in fact it started and was immediately murdered by the system.

Another assumption embedded in the message is that the benchmark configuration (12 proofs, concurrency 5, partition-workers 10) is appropriate for this hardware. The user does not explicitly state this assumption—it is implicit in the decision to deploy with these parameters. But the OOM kill reveals that this configuration, while appropriate for high-memory instances (like the Norway instance with 500GB RAM that succeeded later), is disastrous for the 125GB BC Canada instance. The assumption of hardware homogeneity across Vast.ai instances is quietly invalidated.

The user also assumes that the entrypoint's log message "Starting benchmark" means the benchmark process was successfully launched. This is technically true—the shell script did execute the benchmark command—but it does not guarantee that the benchmark process will survive to produce results. The entrypoint script, having been hardened against failures in previous rounds (<msg id=964-974>), no longer uses set -e, so a crashed benchmark does not abort the entire pipeline. But it also means the entrypoint has no mechanism to detect that the benchmark was killed.

Output Knowledge Created

This message, despite its brevity, creates several important pieces of knowledge. First, it establishes that the parameter fetch pipeline works correctly on the new instance—the paramfetch completed successfully, validating the Docker image and the network connectivity. Second, it reveals that the param-done signaling to the vast-manager API works, confirming that the ID-based matching fix is functional (the manager did not kill the instance during parameter download). Third, and most importantly, it surfaces the OOM problem that becomes the central focus of the next phase of work.

The message also implicitly validates the overall architecture. The instance booted, the entrypoint ran, the parameters downloaded, the API communication worked. The only failure point is the benchmark itself, and that failure is not a software bug but a resource constraint. This distinction is crucial: it means the software stack is sound, but the deployment strategy needs to account for heterogeneous hardware.

The Thinking Process: What Happens Next

The assistant's response to this message (which appears in subsequent rounds) reveals the diagnostic thinking. The immediate question is: is the benchmark actually running but producing output elsewhere, or has it crashed? The assistant would check the instance's logs, look at the OOM killer messages in dmesg or journalctl, and examine the benchmark script's output handling. The discovery of OOM kills would then trigger a redesign of the benchmark strategy: reducing partition workers for the warmup proof (when the PCE is uncached and memory usage peaks), then scaling up for subsequent cached proofs.

This message thus serves as the canary in the coal mine. It is the first signal that the deployment, while architecturally correct, must adapt to the realities of the Vast.ai marketplace where memory configurations vary wildly. The 125GB instance is not defective—it simply cannot run the same configuration as a 500GB instance. The knowledge created by this message directly drives the hardware-aware pipeline configuration that becomes the next major theme of the session.

Conclusion

The user message at index 976 is a masterclass in concise problem reporting. In a few lines of log output and a brief observation, it captures the successful completion of parameter fetch, the initiation of the benchmark, and the troubling silence that followed. It is a message that seems to report a failure but actually reveals a success—the deployment pipeline works end-to-end—and a constraint—the hardware is not uniformly capable. The assumptions embedded in the message—that visible output equals running process, that benchmark configuration is portable across instances—are reasonable but ultimately incorrect, and their correction drives the next phase of development.

This message is the pivot point between two eras of the session: the era of platform-specific debugging (VAST_CONTAINERLABEL, monitor matching, Docker build blockers) and the era of workload-specific resource tuning (partition worker counts, memory-aware configuration, hardware profiling). It is a small message with outsized consequences, a status update that changed the trajectory of an entire deployment.