The Warmup That Worked: Validating an OOM Fix Across 2TB of Belgian RAM

In the middle of a long debugging session that had consumed multiple Docker rebuilds, instance recreations, and formula tweaks, a single message arrived that felt like a quiet exhale. The assistant, having just deployed two new Vast.ai instances running a hardened Docker image, checked in on the Belgium-based machine — a 2x A40 GPU instance with a staggering 2TB of RAM — and found it executing its warmup proof without crashing. The message at <msg id=1152> captures this moment: a brief observation, a five-minute sleep, and then the triumphant return of a completed proof result.

The Context: An OOM Saga

To understand why this message matters, one must appreciate what preceded it. The assistant had been locked in a battle against Out of Memory (OOM) failures that plagued low-RAM GPU instances during the cuzk PoRep proving benchmark. The core problem was subtle: when the daemon started for the first time on a fresh instance, it had no Pre-Compiled Constraint Evaluator (PCE) cache. Without this cache, the daemon would synthesize all partition constraints simultaneously during the warmup proof, consuming vastly more memory than during normal operation. A machine with 125GB RAM would be killed by the kernel's OOM killer before the warmup could complete.

The assistant had traced this to two interacting issues. First, the benchmark.sh script started the daemon with the full complement of partition workers (e.g., 10 or 16) even during the initial PCE extraction, causing a memory spike as every partition's constraints were synthesized in parallel. Second, the entrypoint.sh script used a hardcoded concurrency=5 regardless of available RAM, which meant a machine with 251GB could be asked to run 5 concurrent proofs each consuming 50-60GB — a recipe for disaster.

The fix, deployed over several iterations, was twofold. The benchmark.sh script was refactored to detect the absence of a PCE 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. Separately, entrypoint.sh was rewritten to dynamically scale benchmark concurrency based on available RAM and GPU count, replacing the hardcoded value with a formula that reserved 100GB overhead and estimated 6GB per partition worker per proof.

The Message: Checking In on Belgium

The subject message opens with the assistant assessing the Belgium instance's state:

2TB RAM, 122GB used (SRS + daemon), 1.8TB available. Tons of headroom. GPUs not engaged yet — still synthesizing partitions on CPU.

This line reveals the assistant's reasoning process in real time. The assistant is performing a mental safety check: it reads the memory usage (122GB used out of 2TB), computes the headroom (1.8TB available), and cross-references this against the known memory profile of the warmup phase. The observation that GPUs are not yet engaged — showing 0% utilization and only 359 MiB of memory used on each A40 — confirms that the daemon is still in the CPU-intensive partition synthesis phase. This is exactly the phase that had caused OOM crashes on smaller machines.

The assistant then issues a command that encapsulates the entire debugging methodology of this session: sleep 300 followed by a remote SSH call to tail the benchmark log. The five-minute sleep is a deliberate pacing mechanism. The assistant knows that warmup takes time — the previous Norway instance had taken over 20 minutes for its full benchmark — and there is no point polling every few seconds. The assistant is working asynchronously, checking in at intervals that match the expected timescale of the operation.

The Result: A Completed Warmup

When the assistant checks back, it receives the output that every prior iteration of this session had been chasing:

=== Proof Result ===
status:    COMPLETED
job_id:    cb5dea71-3ead-454e-aa2a-90883ff7b8b1
timings:   total=304606 ms (queue=418 ms, srs=0 ms, synth=586373 ms, gpu=85531 ms)
wall time: 305227 ms

The warmup proof completed in approximately 305 seconds (just over 5 minutes). The timing breakdown is revealing: synthesis (synth) took 586 seconds — wait, this is odd. The total field shows 304,606 ms (about 5 minutes), but synth shows 586,373 ms (about 9.8 minutes). This apparent inconsistency is actually a clue about how the timing is reported. The synth value likely represents cumulative synthesis time across all partitions, which can exceed wall time because synthesis of different partitions happens in parallel across CPU cores. The gpu time of 85,531 ms (about 85 seconds) represents the GPU proving phase after synthesis completed.

The srs=0 ms field is noteworthy: it indicates that the Structured Reference String (SRS) parameters were already cached and did not need to be fetched or generated. This aligns with the earlier observation that the Belgium host had cached parameters from a previous instance (134GB of params were already present).

What This Message Validates

This single completed proof result validates several assumptions and fixes:

The PCE-cache-dependent warmup strategy works. By starting the daemon with partition_workers=2 during the warmup, the assistant avoided the memory spike that had killed smaller instances. The Belgium machine had 2TB of RAM, so it probably would have survived even with 16 partition workers, but the fact that the warmup completed cleanly confirms the approach is sound.

The dynamic concurrency formula is safe. The Belgium instance auto-configured to partition_workers=16 and concurrency=6. With 2TB of RAM, the formula gave available=1903GB, per_proof~96GB (16 workers × 6GB), 1903/96=19, capped by gpu_cap=6 (2 GPUs × 3 proofs per GPU). This conservative configuration meant the machine was operating well within its memory envelope.

The hardware-aware pipeline works end-to-end. From parameter download to registration to warmup, the entire lifecycle functioned without manual intervention. The entrypoint script detected the hardware, configured itself, fetched parameters, started the daemon, and executed the warmup — all without human oversight.

Assumptions and Knowledge

The assistant makes several assumptions in this message. It assumes that a completed warmup proof implies the PCE cache was successfully generated, which is necessary for the subsequent batch benchmark. It assumes that the timing breakdown is accurate and that the synthesis time being larger than wall time is due to parallelization rather than a bug. It assumes that the daemon will correctly restart with partition_workers=16 for the batch benchmark, since the warmup was done with partition_workers=2.

The input knowledge required to interpret this message includes understanding of the cuzk proving pipeline (synthesis vs GPU proving phases), the role of the PCE cache, the memory profile of partition workers, and the lifecycle of a Vast.ai instance from registration through parameter download to benchmarking. The output knowledge created by this message is the first validated data point for the Belgium machine's performance: a warmup time of ~5 minutes and a synthesis/GPU timing breakdown that can inform future configuration decisions.

The Thinking Process

The assistant's reasoning is visible in the structure of the message itself. It opens with a situational assessment ("2TB RAM, 122GB used... Tons of headroom"), then issues a monitoring command with an appropriate delay, and finally interprets the result. The assistant is not just collecting data — it is actively evaluating whether the fixes it deployed are working. The tone is one of cautious optimism: the warmup completed, but the real test — the batch benchmark of 12 proofs at concurrency=6 — is still to come.

This message sits at a turning point in the session. The debugging phase is ending and the validation phase is beginning. The assistant has moved from asking "why is it crashing?" to asking "how fast does it run?" — a subtle but profound shift in the nature of the investigation.