The Memory Ceiling Speaks: "OOM-ish again" as a Pivot Point in GPU Proving Optimization

"OOM-ish again" — [msg 2985]

This single, four-word message from a user to an AI assistant during an intense optimization session for the cuzk SNARK proving engine carries far more weight than its brevity suggests. It is not merely a status report; it is a diagnosis, a frustration, and a pivot signal all compressed into a single line. To understand why this message was written and what it means, one must trace the chain of events that led to it, the assumptions that preceded it, and the architectural realities it brutally exposed.

The Context: A Pipeline at the Edge of Memory

The message arrives at a critical juncture in a months-long optimization campaign for Filecoin's Groth16 proof generation pipeline. The assistant had just completed implementing Phase 12, a sophisticated "split GPU proving API" that decoupled the expensive b_g2_msm computation from the GPU worker's critical path. The initial benchmark results were promising: with the baseline configuration of partition_workers=10 (pw=10), the system achieved 37.1 seconds per proof — a 2.4% improvement over the Phase 11 baseline of 38.0 seconds ([msg 2962]). The split API was working correctly, offloading work to background threads and letting GPU workers pick up new partitions faster.

But the optimization journey never stops at one win. The user, seeing the successful split API and understanding that the GPU worker was now freed sooner, proposed a natural next step: increase synthesis parallelism ([msg 2964]). The reasoning was sound — if the GPU worker finishes its critical path faster, the bottleneck might shift to CPU-side synthesis throughput. More partition_workers (pw) could keep the GPU better fed, potentially improving overall throughput beyond 37.1s/proof.

The assistant agreed and set out to test pw=15 and pw=20 ([msg 2965]). This is where the assumptions collided with reality.

The First OOM: pw=15

The assistant killed the existing daemon, created a new config with partition_workers = 15, and launched the benchmark ([msg 2973]-[msg 2975]). The result was immediate failure: the daemon crashed with a broken pipe error, the benchmark reporting "Prove RPC failed" with a transport error ([msg 2975]). The assistant correctly diagnosed this as an out-of-memory (OOM) kill: the Linux kernel's OOM killer had terminated the daemon process when it exceeded the system's 755 GiB of RAM.

The assistant's analysis in [msg 2979] reveals the arithmetic of the memory wall:

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 is a critical moment of knowledge creation: the memory budget of the system is now explicitly enumerated. The SRS (Structured Reference String) consumes 44 GiB, the PCE (Prover Cache Element) consumes 26 GiB, each partition synthesis consumes approximately 13 GiB, and each parsed proof (with j=15 concurrent jobs) consumes roughly 3 GiB. The total demand at pw=15 with j=15 would be:

• SRS: 44 GiB
• PCE: 26 GiB
• Synthesis (15 × 13 GiB): 195 GiB
• Parsed proofs (15 × 3 GiB): 45 GiB
• Other overhead: ~50 GiB
• Total: ~360 GiB Wait — that should fit in 755 GiB. The actual OOM suggests the per-partition memory footprint is larger than the 13 GiB estimate, or that there are additional memory consumers not accounted for. This discrepancy would later drive deeper investigation (see Chunk 1 of Segment 30).

The Second OOM: pw=12

The user's response to the pw=15 failure was a concise "oom" ([msg 2977]), followed by another "oom" ([msg 2978]). These two messages, each just three characters, are the user's way of saying: "I see the problem. This is the memory ceiling. What are you going to do about it?"

The assistant, undeterred, tried a more conservative configuration: pw=12 ([msg 2980]-[msg 2982]). The daemon started successfully, and the benchmark began running. But the results told the same story: the benchmark output shows proofs completing with increasing latency (78.3s, 119.2s, 158.8s, 192.2s...) before the daemon was presumably killed again ([msg 2983]). The assistant's analysis in [msg 2984] identifies the compounding effect:

OOM again at pw=12. The memory pressure is too high with 12 concurrent partition synthesis workers when you also have 15 concurrent jobs. The issue is that with j=15, up to 15 proofs are being parsed simultaneously, each allocating ~3 GiB for parsing, plus 12 synthesizing at ~13 GiB each.

This is where the user's message — "OOM-ish again" ([msg 2985]) — lands. It is the third OOM-related message in a rapid sequence, and its tone carries a subtle but important shift. The first user response ("oom") was a simple observation. The second ("oom") was a repetition, perhaps with a hint of "I told you so." The third — "OOM-ish again" — adds a qualifier: "-ish". This is not accidental. The "-ish" suffix suggests the user is acknowledging that the OOM is not a clean, deterministic failure but rather a fuzzy, probabilistic one. The system might not crash every time at pw=12; it might depend on timing, on which proofs are being processed, on the exact sequence of allocations. The "-ish" communicates: "This is right at the boundary. Sometimes it works, sometimes it doesn't. We are living on the edge of memory capacity."

Why This Message Matters

The "OOM-ish again" message is a pivot point in the optimization session for several reasons.

First, it confirms a fundamental architectural constraint. The Phase 12 split API successfully improved GPU utilization, but it did not reduce memory consumption. In fact, by allowing more partitions to be in flight simultaneously, it may have exacerbated memory pressure. The system has a hard ceiling at approximately pw=10 with j=15 on a 755 GiB machine. Any attempt to increase synthesis parallelism beyond this point risks OOM.

Second, it reveals an incorrect assumption. The user and assistant both assumed that the split API's efficiency gains would create headroom for more synthesis workers. The reasoning was: "GPU worker finishes faster → GPU is the bottleneck → more synthesis parallelism will feed the GPU better." But the actual bottleneck was not GPU throughput — it was memory capacity. The system was already at its memory limit with pw=10. The split API improved GPU-side latency but did nothing to reduce the memory footprint of in-flight partitions.

Third, it drives the next phase of investigation. The assistant's response to "OOM-ish again" in [msg 2984] shows a shift in strategy: "Let me try pw=10 baseline again... Or maybe we should just commit what we have since 37.1s is already a nice improvement." This is the assistant acknowledging that the low-hanging fruit has been picked, and further gains require deeper work on memory reduction, not just parallelism tuning.

The Deeper Problem: Memory Architecture

To fully understand "OOM-ish again," one must understand the memory architecture of the Groth16 proving pipeline. Each partition synthesis produces several large data structures:

• NTT evaluation vectors (a, b, c): ~12 GiB per partition, needed for GPU computation
• Proving assignments: the circuit values and wire assignments
• Input/auxiliary assignments: the public and private inputs These allocations are not freed until the GPU finishes processing the partition. With the split API, the GPU worker's critical path is shorter, but the memory lifetime of these structures is unchanged. They must persist until the GPU kernel completes its work. The channel between synthesis and GPU is a single-slot queue (in the Phase 12 implementation). When the GPU worker is fast, it drains this queue quickly. But when synthesis produces partitions faster than the GPU can consume them — which is the goal of increasing pw — the queue backs up, and memory piles up. Each partition in the queue holds its full ~16 GiB dataset. The "-ish" in "OOM-ish" captures this dynamic: the system does not have a deterministic OOM at pw=12. It depends on whether the GPU can keep up with synthesis, on whether partition sizes vary, on the exact interleaving of allocations and deallocations. The system is dancing at the edge of its memory budget, and sometimes it falls off.

The Thinking Process Visible in the Conversation

The user's message is brief, but the thinking behind it is revealed by the surrounding context. The user has been following the optimization journey closely. They saw the pw=15 crash. They saw the pw=12 near-crash. They understand the memory arithmetic. The "-ish" qualifier tells us the user is thinking probabilistically: "This isn't a clean OOM — it's a flaky, near-OOM situation that will plague us in production."

The user is also implicitly asking: "Is this good enough, or do we need to fix the memory problem?" The assistant's response — suggesting they might just commit the 37.1s improvement and move on — shows that the assistant interpreted the message as a signal to either push harder or accept the current state. The user's "OOM-ish again" is a gentle but firm nudge: "We have a memory problem. Don't ignore it."

Input and Output Knowledge

To understand this message, the reader needs:

• Knowledge of the memory budget: SRS (44 GiB), PCE (26 GiB), per-partition synthesis (~13 GiB), per-proof parsing (~3 GiB), total system RAM (755 GiB)
• Knowledge of the Phase 12 split API: what it does (offloads b_g2_msm from GPU critical path) and what it doesn't do (reduce memory footprint)
• Knowledge of the concurrency model: partition_workers (synthesis parallelism), gpu_workers (GPU parallelism), job concurrency (j=15)
• Knowledge of the previous OOM attempts: pw=15 (hard crash), pw=12 (near-crash) The message creates new knowledge:
• Confirmation of the memory ceiling: pw=10 is the maximum safe synthesis parallelism on this hardware
• Identification of the next bottleneck: memory capacity, not GPU throughput
• A signal to pivot: further optimization must focus on reducing per-partition memory footprint, not increasing parallelism

Conclusion

"OOM-ish again" is a masterclass in concise technical communication. In four words, the user communicates a diagnosis (OOM), a qualification (it's fuzzy, not deterministic), a pattern (again — this is recurring), and a call to action (we need to address this). The message marks the end of one phase of optimization — the phase focused on GPU throughput and API restructuring — and the beginning of another: the phase focused on memory reduction.

The assistant's subsequent work in Chunk 1 of Segment 30 — building a global buffer tracker with atomic counters, diagnosing the partition pileup, and iterating on semaphore release timing and channel capacity — is the direct consequence of this message. Without "OOM-ish again," the investigation might have stopped at "pw=10 is the sweet spot" and moved on. Instead, the user's gentle but persistent signal drove a deep dive into memory instrumentation that ultimately revealed the root cause and led to a more robust pipeline.

In the high-stakes world of Filecoin proof generation, where each second of proving time translates directly into operational cost, the difference between 37.1s and a crash is the difference between a working system and a failed benchmark. "OOM-ish again" captures that knife-edge reality in four words.