A Moment of Validation: The US Instance Benchmark Begins

Message 1107 — The assistant confirms that a US-based GPU instance (2x RTX 3090, 75GB RAM) has successfully completed parameter fetching, auto-configured to partition_workers=10, and begun its PoRep proving benchmark — the first instance to run with the newly deployed OOM fixes and hardware-aware pipeline.

The Message

[assistant] Excellent! The US instance has:
1. Finished param fetch
2. Started benchmark with `partition-workers 10` (correctly using 10, not 16, since this machine has < 400GB RAM — 75GB)
3. The cuzk daemon is running (PID 865 at 100% CPU, 4.8% of 75GB = ~3.6GB RSS so far)

The benchmark just started. Let me check the benchmark-full.log to see the warmup progress:
[bash] ssh -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -p 33080 root@ssh1.vast.ai 'cat /tmp/benchmark-full.log 2>/dev/null' 2>/dev/null
C1 output not found at /data/32gbench/c1.json
Downloading from https://pub-08ae819c828244bdbe5f615fd8c5e144.r2.dev/c1.json ...

Context: The OOM Crisis

To understand why this message matters, one must appreciate the cascade of failures that preceded it. The CuZK proving engine — a high-performance GPU-based prover for Filecoin proofs — was being deployed across rented GPU instances on Vast.ai. The system involved a manager service that provisioned instances, ran benchmarks to measure proofs-per-hour throughput, and kept or destroyed instances based on performance.

The problem was brutal: instances with limited RAM (125GB, 75GB) were being killed by the Linux OOM killer during the benchmark warmup phase. The root cause was twofold. First, the benchmark.sh script started the cuzk daemon with the full complement of partition workers immediately, causing all partition synthesis to happen simultaneously and spike memory usage far beyond what the system could handle. Second, the entrypoint.sh script used a hardcoded concurrency=5 regardless of available RAM, meaning multiple proofs could be in flight simultaneously on a machine that barely had enough memory for one.

The BC Canada instance (125GB RAM) was the first casualty. Then the Norway instance (1x RTX 4090, 500GB RAM) survived its benchmark but scored only 41.32 proofs/hour — below the 50 proofs/hour minimum — and revealed a lifecycle bug: the manager's handleBenchDone endpoint set the instance state to killed but never actually called vastai destroy, leaving the underperforming instance running and incurring cost.

Two major fixes were implemented and deployed in a new Docker image. First, benchmark.sh was refactored to detect the absence of a PCE (Pre-Compiled Constraint Evaluator) cache and start the daemon with partition_workers=2 for the warmup proof only. After the PCE file was generated, the daemon was restarted with the full partition count for the actual benchmark. This prevented the memory spike that had been killing low-RAM instances. Second, entrypoint.sh was rewritten to dynamically scale benchmark concurrency based on available RAM and GPU count, replacing concurrency=5 with a formula that reserved 100GB overhead and estimated 6GB per partition worker per proof. Additionally, the lifecycle bug was fixed so that failing instances are immediately destroyed.

Why This Message Was Written

Message 1107 is fundamentally a validation checkpoint. The assistant had just waited two minutes (via sleep 120 in the previous message) and was checking whether the US instance — the first to run the new Docker image — had survived the critical early phases of the benchmark lifecycle.

The assistant's "Excellent!" exclamation reveals the emotional weight of this moment. After rounds of debugging OOM kills, fixing lifecycle bugs, rebuilding Docker images, redeploying the manager, and manually cleaning up orphaned instances, the system was finally running as designed. The message serves multiple purposes:

  1. Confirming the param fetch completed. The 134GB of Filecoin proof parameters had finished downloading without error. This was non-trivial — earlier instances had failed at this stage due to network issues or disk space problems.
  2. Validating the hardware-aware configuration. The instance auto-configured to partition_workers=10, not the maximum of 16. The assistant explicitly notes this is "correctly using 10, not 16, since this machine has < 400GB RAM — 75GB." This confirms the dynamic configuration logic in entrypoint.sh is working as intended, scaling down partition workers for a low-RAM machine.
  3. Verifying the daemon started without OOM. The cuzk daemon is running at 100% CPU with only ~3.6GB RSS so far. This is the first evidence that the warmup-phase memory spike has been tamed.
  4. Capturing the benchmark start. The benchmark-full.log shows the system downloading c1.json — a pre-computed challenge file needed for the benchmark. This is the normal, expected first step of a healthy benchmark run.

The Thinking Process Visible in the Message

The assistant's reasoning is telegraphically clear in the structure of the message. It lists three bullet points in order of significance: param fetch completion, correct partition worker count, and daemon health. Each bullet is a gate that must pass before the next can be evaluated.

The parenthetical "(correctly using 10, not 16, since this machine has < 400GB RAM — 75GB)" is particularly revealing. It shows the assistant is actively reasoning about the configuration logic it wrote. The threshold of 400GB RAM for allowing partition_workers=16 was a design decision made during the entrypoint rewrite. Here, the assistant verifies that the logic produces the expected output for a 75GB machine — confirming both that the code is correct and that the instance's reported RAM matches expectations.

The calculation "4.8% of 75GB = ~3.6GB RSS" shows the assistant performing real-time resource accounting, cross-referencing the percentage from ps with the known system RAM to derive an absolute memory figure. This is not idle curiosity — it's checking whether the daemon's memory usage is growing dangerously or staying within safe bounds during the warmup phase.

Assumptions Made

Several assumptions underpin this message:

  1. The Docker image on the instance is the latest build. The assistant assumes that the image pushed to Docker Hub before instance creation is what's running. This was verified earlier (msg 1101-1102) by checking the benchmark.sh content on the live instance.
  2. The SSH tunnel is stable. The connection goes through ssh1.vast.ai on a non-standard port (33080) via a portavailc tunnel. The assistant assumes this tunnel remains operational for the duration of the benchmark.
  3. The benchmark will complete without error. The message treats the benchmark start as good news, implicitly assuming it will run to completion. In reality, this instance will later fail — but at this moment, the assistant has no reason to expect trouble.
  4. The partition worker count of 10 is safe for 75GB RAM. This is based on the formula in entrypoint.sh, which was itself a heuristic. The assistant trusts this heuristic without independent verification at this point.
  5. The c1.json download will succeed. The benchmark depends on downloading this file from a remote URL. The assistant assumes network connectivity is reliable.

Input Knowledge Required

To fully understand this message, a reader needs knowledge of:

Output Knowledge Created

This message produces several valuable pieces of knowledge:

  1. The OOM fix works for a 75GB instance. This is the first successful warmup on a low-RAM machine after multiple failures. It validates the two-phase warmup strategy empirically.
  2. The dynamic configuration logic is correct. The instance auto-selected partition_workers=10 based on its 75GB RAM, confirming the threshold logic in entrypoint.sh produces sensible values.
  3. Param fetch completes successfully on this instance. The 134GB download finished without error, confirming network and disk are adequate.
  4. The daemon starts cleanly. No crashes, no OOM kills, no configuration errors.
  5. A baseline for future comparison. The benchmark rate this instance achieves will become data for the hardware-performance database being built in the next chunk.

The Broader Significance

Message 1107 sits at a inflection point in the session. The previous ~30 messages were consumed with debugging, fixing, rebuilding, and redeploying. This message is the first moment where the assistant can simply observe the system working as intended. The tone shifts from reactive debugging to proactive monitoring.

Yet the reader of the full conversation knows what the assistant does not: this instance will later fail too. The Belgium and Czechia instances in the next chunk will encounter new problems — benchmark timeout, gRPC transport errors, and ultimately performance below the 50 proofs/hour threshold. The hard-won OOM fix solves one class of problem but does not guarantee benchmark success. This message captures the brief optimism before the next wave of failures forces a fundamental strategic shift toward data-driven hardware discovery.

In that sense, message 1107 is a snapshot of a system in transition: the reactive fixes are working, but the deeper problem — that hardware specs alone cannot predict proving performance — has not yet been fully appreciated. The assistant's "Excellent!" is earned, but premature. The real lesson — that a self-tuning, experimental system is needed — will emerge only after more failures force the pivot.