The Calm Before the OOM: A Verification Message That Hides a Memory Ceiling

In the middle of a high-stakes optimization campaign for the SUPRASEAL_C2 Groth16 proof generation pipeline, a single assistant message appears deceptively simple. Message [msg 2974] contains nothing more than a bash command — sleep 30 && tail -5 — followed by five lines of daemon log output confirming that the cuzk-daemon has started successfully with a new configuration. On its surface, this is a routine operational check: the assistant killed the old daemon, wrote a new config file, launched the process, waited for initialization, and verified it was listening on TCP. But this message sits at a critical inflection point in the optimization journey, where an assumption about available memory headroom collides with the physical reality of a 755 GiB system.

The Context: Phase 12 and the User's Suggestion

To understand why this message was written, we must trace back through the preceding conversation. The assistant had just completed implementing Phase 12 — a "split GPU proving API" that offloaded the b_g2_msm computation from the GPU worker's critical path. After fixing a series of Rust/C++ FFI compilation errors and a critical use-after-free bug in the CUDA code where a background prep_msm_thread captured a dangling reference to a stack-allocated provers array, the assistant had achieved a clean build and benchmarked the implementation. With the optimal configuration of gw=2 (GPU workers per device), pw=10 (partition workers), gt=32 (GPU threads), and j=15 (concurrent jobs), the Phase 12 split API delivered 37.1 seconds per proof — a ~2.4% improvement over the Phase 11 baseline of 38.0 seconds.

The user then made a suggestion at [msg 2964]: "Try higher synthesis partition_workers in config, maybe 15/20?" The reasoning was intuitive: if the split API frees up GPU workers faster by moving b_g2_msm off the critical path, the bottleneck may shift to synthesis throughput. More partition workers could keep the GPU pipeline better fed, potentially improving overall throughput beyond the modest 2.4% gain already observed.

The assistant agreed at [msg 2965], updating the todo list to mark "Benchmark Phase 12 with pw=15" as in progress. What followed was a surprisingly difficult process of killing the running daemon — the process resisted multiple kill and kill -9 attempts across several messages ([msg 2966] through [msg 2971]) before finally being terminated. The assistant then wrote two config files (/tmp/cuzk-p12-pw15.toml and /tmp/cuzk-p12-pw20.toml) and launched the daemon with the pw=15 configuration using nohup.

The Message: A Routine Verification

The subject message itself is straightforward:

[assistant] [bash] sleep 30 && tail -5 /home/theuser/cuzk-p12-pw15.log

The sleep 30 is deliberate — the daemon needs time to initialize, load the SRS parameters (which are tens of gigabytes), and start the synthesis dispatcher. The tail -5 extracts the most recent log entries, which should show the daemon's final startup status. The output confirms success:

The Hidden Drama: What Comes Next

The very next message ([msg 2975]) tells a different story. The assistant runs the benchmark command and receives:

Error: Prove RPC failed
Caused by:
    0: status: Unknown, message: "transport error"
    2: connection error
    3: stream closed because of a broken pipe

The daemon has crashed. The user confirms with two succinct messages at [msg 2977] and [msg 2978]: "oom".

The assistant's realization at [msg 2979] is telling: "OOM with pw=15 — 15 concurrent partition syntheses is too much RAM. Each partition synthesis uses ~13 GiB, so 15 × 13 = ~195 GiB just for synthesis, plus the SRS (44 GiB) + PCE (26 GiB) + other overhead exceeds the 755 GiB."

This moment reveals a critical assumption that went unexamined when the assistant agreed to try higher parallelism. The assistant knew the memory characteristics of each partition — approximately 13 GiB for the NTT evaluation vectors (a, b, c), plus the proving assignment data. It knew the SRS consumed 44 GiB and the PCE (proving circuit evaluator) used another 26 GiB. But the arithmetic was not done proactively. The assistant assumed, implicitly, that the system had enough headroom to scale from pw=10 to pw=15. It did not.

Assumptions, Mistakes, and What Was Learned

The primary mistake here is not the OOM itself — empirical testing is a valid approach to finding system limits. The mistake is the absence of a pre-check. A simple calculation before launching the daemon would have revealed that 15 concurrent partitions × 13 GiB = 195 GiB for synthesis buffers alone, plus 44 GiB SRS, plus 26 GiB PCE, plus GPU pinned memory, plus the operating system's own needs. The system has 755 GiB total, but the peak working set would approach or exceed that when accounting for fragmentation, allocation overhead, and the fact that not all memory is available to a single process.

The chunk summary from the analysis pipeline confirms that this was a systemic issue: "Attempts to increase synthesis parallelism (partition_workers=12/15) led to OOM errors, with RSS peaking at 668 GiB, confirming the 755 GiB system is at its limit with the current concurrency model." Even pw=12 eventually failed with 668 GiB RSS, leaving only ~87 GiB of headroom — dangerously close to the ceiling.

The assistant's thinking process reveals another layer: the belief that the split API would shift the bottleneck to synthesis throughput. This was a reasonable hypothesis — if GPU workers are spending less time per partition because b_g2_msm runs asynchronously, then the pipeline needs more synthesized partitions ready to consume. More partition workers should produce more partitions faster. But this reasoning ignored the memory cost of those additional in-flight partitions. Each additional worker adds ~13 GiB of live memory for the duration of synthesis, and if the GPU channel cannot consume them fast enough, they pile up.

Input and Output Knowledge

To fully understand this message, the reader needs input knowledge about: the Groth16 proving pipeline structure (synthesis → NTT → MSM → proof assembly), the memory footprint of each stage (~13 GiB per partition for NTT evaluation vectors), the system's physical memory capacity (755 GiB), the Phase 12 split API design that offloads b_g2_msm to a background thread, and the config parameter partition_workers that controls how many CPU cores simultaneously synthesize circuit partitions.

The output knowledge created by this message and its aftermath is a concrete memory ceiling: the system cannot sustain more than 10-11 concurrent partition syntheses without OOM. This discovery directly drives the next phase of work — the chunk summary notes that "the memory capacity bottleneck identified here sets the stage for future work on reducing per-partition memory footprint." The assistant goes on to implement early deallocation of NTT evaluation vectors and build a global buffer tracker with atomic counters to diagnose and mitigate memory pressure.

The Broader Significance

This message exemplifies a pattern common in high-performance systems optimization: the tension between throughput and memory. Every optimization that improves one dimension often stresses another. The Phase 12 split API successfully reduced GPU worker idle time, but that success revealed a new bottleneck — not in compute, but in memory capacity. The assistant's willingness to push against this boundary empirically, even at the cost of an OOM crash, is a deliberate engineering strategy: find the wall by running into it, then measure how high it is.

The message also illustrates the value of instrumentation. After the pw=15 OOM, the assistant doesn't just reduce parallelism and move on. Instead, it builds a global buffer tracker with atomic counters (buf_synth_start, buf_abc_freed, buf_dealloc_done) to gain real-time visibility into every large buffer class in flight. This instrumentation reveals that the true bottleneck is not raw memory capacity but the interaction between the partition semaphore and the GPU channel — synthesized partitions queue up holding their full ~16 GiB datasets while waiting for the single-slot GPU channel. This insight leads to a channel capacity increase from 1 to partition_workers, which resolves the memory buildup without sacrificing throughput.

In the end, the humble verification message at [msg 2974] is the calm before the storm — a moment where everything appears to be running smoothly, just before the system hits its memory ceiling and crashes. It is a reminder that in systems engineering, the most informative experiments are often the ones that fail.