Seeing the Unseen: How Buffer Instrumentation Revealed the True Memory Bottleneck in a GPU Proving Pipeline

Introduction

In the high-stakes world of Filecoin proof generation, memory is the ultimate constraint. The SUPRASEAL_C2 Groth16 proving pipeline, a critical component of the Curio storage mining system, consumes enormous amounts of RAM — upwards of 650 GiB during peak operation. When the Phase 12 split GPU proving API was implemented and tested with partition_workers=12 (pw=12), the daemon repeatedly crashed with out-of-memory (OOM) errors, despite careful engineering to free buffers early. The team was flying blind: they knew memory was being consumed, but not where or why.

This article examines a single, pivotal message in the optimization conversation — message index 3104 — where the assistant first analyzed the output of a newly built buffer instrumentation system and began to see the memory problem with clarity. It is a story about the power of measurement, the danger of incomplete data, and the iterative process of diagnosis that drives high-performance systems engineering.

The Context: A Persistent OOM Mystery

The conversation leading up to this message had been a deep investigation into the memory characteristics of the SUPRASEAL_C2 pipeline. Earlier phases had identified that the pipeline's peak memory footprint of ~200 GiB was driven by several factors: the SRS (Structured Reference String) loading, the PCE (Partitioned Constraint Extraction), and most importantly, the massive intermediate buffers produced during circuit synthesis. Each partition's synthesis produced ProvingAssignment structures containing a/b/c NTT evaluation vectors (~12 GiB per partition) and aux_assignment buffers (~4 GiB per partition).

Phase 12 had introduced a "split API" that decoupled GPU proving from CPU post-processing, allowing the expensive b_g2_msm operation to run in a background thread. But when the team tried to increase synthesis parallelism from pw=10 to pw=12, the daemon OOM'd with RSS peaking at 668 GiB — nearly the entire 755 GiB system memory. An early deallocation of the a/b/c vectors after prove_start returned had been implemented, but it only saved ~18 GiB. Something else was consuming the remaining ~300 GiB of unexpected memory.

The user, frustrated by the opaque memory behavior, asked a simple but powerful question in message 3076: "Can we count and report number of each large buffer in flight and maybe the stage?"

The Instrumentation Effort

The assistant responded by building a global buffer tracker — a set of atomic counters in the pipeline.rs module that tracked five buffer classes:

• synth: Number of synthesis tasks in flight
• provers: Number of ProvingAssignment sets (a/b/c vectors) alive
• aux: Number of aux_assignment buffers alive
• shells: Number of density-only shell structures (tiny)
• pending: Number of pending proof handles in the C++ layer Each counter was incremented and decremented at precise points in the pipeline: buf_synth_start() at synthesis spawn, buf_synth_done() at synthesis completion, buf_abc_freed() after prove_start returned, and buf_finalize_done() after proof finalization. A log_buffers() helper printed the current state along with an estimated memory footprint. The hooks were inserted into the engine's synthesis dispatcher, the GPU worker's receive path, and the bellperson deallocation thread. After rebuilding and running a benchmark with pw=12, concurrency=10, and jobs=10, the daemon survived without OOM — a promising sign. The assistant then examined the first 40 lines of buffer counter output.

The Subject Message: First Analysis

Message 3104 is the moment of first interpretation. The assistant writes:

Now I can see the problem clearly. Look at the peak:

>

- synth=12-14 — up to 14 synthesis tasks launched (semaphore should cap at 12!) - provers=12 — 12 ProvingAssignment sets alive, each ~12 GiB = 144 GiB just for a/b/c - aux=12 — 12 aux_assignment buffers, each ~4 GiB = 48 GiB

>

The synth counter goes above 12 because buf_synth_start() is called before the semaphore acquire. Let me also look at the peak state:

The assistant then runs a grep to extract the estimated memory values from the log, finding peaks ranging from 714 GiB to 732 GiB.

This message is deceptively short but contains several layers of reasoning. Let us unpack them.

The Reasoning Process

First observation: the semaphore leak. The assistant immediately notices that synth=12-14 exceeds the configured partition_workers=12. This is a diagnostic triumph — the counter has revealed a subtle ordering bug. The buf_synth_start() call is placed before the semaphore acquire, meaning the counter inflates by 1-2 before the semaphore actually gates the launch. This is not a memory leak, but it means the buffer counter's synth field slightly overcounts relative to the intended cap. The assistant correctly identifies the root cause: "The synth counter goes above 12 because buf_synth_start() is called before the semaphore acquire."

Second observation: the memory breakdown. The assistant computes: provers=12 × 12 GiB = 144 GiB for a/b/c vectors, plus aux=12 × 4 GiB = 48 GiB for aux assignments. This is a rough but useful estimate. At 192 GiB for just these two buffer classes, plus the SRS/PCE (~70 GiB) and other overhead, the total plausibly reaches the observed 650+ GiB range.

Third action: seeking the worst case. The assistant runs a grep to find the peak estimated memory values, sorting numerically and taking the top 10. The values — 714, 716, 718, 720, 722, 723, 724, 727, 732 GiB — confirm that the system is operating at the very edge of the 755 GiB capacity.

What the Message Gets Right

The assistant's analysis in this message is fundamentally sound. The buffer counters are working correctly and providing actionable data. The identification of the semaphore ordering issue is a genuine bug find — though minor, it explains the slight overshoot in synthesis launches. The memory breakdown, while based on preliminary data, correctly identifies the a/b/c and aux buffers as the dominant consumers.

More importantly, the message demonstrates a crucial engineering principle: you cannot optimize what you cannot measure. Before the buffer counters, the team could only observe the RSS curve and guess at the internal state. Now, for the first time, they have real-time visibility into exactly how many buffers of each class are alive at any moment. This transforms the debugging process from speculation to science.

What the Message Misses

However, the analysis in message 3104 is based on incomplete data. The assistant is looking at the first 40 lines of buffer output, which capture the ramp-up phase — synth climbing from 1 to 12, provers and aux gradually accumulating. The true peak state is far more extreme, as the assistant discovers in the very next message (3105):

• provers=28 (not 12) — 28 ProvingAssignment sets alive = ~336 GiB
• aux=97-99 (not 12) — nearly 100 aux buffers alive = ~392 GiB
• shells=69-72 — density-only shells The peak estimated memory reaches 732 GiB, dangerously close to the 755 GiB system limit. This reveals a much deeper problem than the initial analysis suggested. The provers counter reaching 28 means that 28 synthesized partitions are sitting in the queue waiting for the GPU, each holding their full ~16 GiB dataset (12 GiB a/b/c + 4 GiB aux). The GPU can only process one partition at a time (~3.5 seconds each), while synthesis completes partitions faster (~5 seconds each with 12 workers). The queue grows inexorably. The aux counter reaching 97-99 is partly a counter bug — the buf_dealloc_done() decrement is never called from bellperson because that crate doesn't have access to the pipeline module's counters. But the provers=28 is real and represents genuine memory pressure.

The Deeper Insight: Pipeline Imbalance

The subject message sets the stage for a critical realization that crystallizes in the following messages: the pipeline is fundamentally imbalanced. The synthesis phase (CPU-bound) can produce partitions faster than the GPU phase can consume them, even with a single-slot channel (synthesis_lookahead=1). The partition semaphore (pw=12) limits concurrent synthesis but does not limit the backlog of completed syntheses waiting for the GPU.

The channel capacity of 1 means only one completed job can be queued at a time, but the synthesis tasks are spawned independently via tokio::spawn. When a synthesis completes and finds the channel full, the send operation blocks the async task — but the synthesized data (the SynthesizedProof struct holding the ~16 GiB buffers) remains alive in the task's local variables, waiting for the channel to accept it. With 12 concurrent syntheses all finishing around the same time, they pile up.

This is the root cause of the OOM at pw=12: not a memory leak, but a scheduling and buffering problem where the synthesis pipeline overproduces relative to the GPU's consumption rate.

Input and Output Knowledge

To understand this message, the reader needs knowledge of: the Groth16 proving pipeline architecture (synthesis phase vs. GPU phase), the buffer classes being tracked (ProvingAssignment a/b/c, aux_assignments), the semaphore mechanism for limiting concurrent synthesis, and the channel-based communication between pipeline stages. The estimated sizes (12 GiB per ProvingAssignment, 4 GiB per aux_assignment) are also essential context.

The message creates new knowledge: confirmation that the buffer instrumentation works and produces interpretable data; identification of the semaphore ordering issue; a preliminary memory breakdown showing a/b/c and aux as dominant consumers; and the discovery that the system operates at 714-732 GiB peak, leaving only ~20-40 GiB of headroom on a 755 GiB machine.

The Broader Narrative

Message 3104 represents a turning point in the optimization effort. Before this message, the team was guessing about memory usage. After this message, they have data. The subsequent investigation (messages 3105-3110) reveals the full extent of the problem: provers=28, aux=99, and the realization that the synthesis-to-GPU channel needs fundamental rethinking.

The ultimate resolution comes later in the segment, when the assistant implements two key fixes: (1) holding the semaphore permit until the synthesized job is delivered to the GPU channel, which drops peak RSS from 668 GiB to 294.7 GiB and enables pw=12 to run without OOM; and (2) increasing the channel capacity from 1 to partition_workers, allowing a natural buffer of completed jobs without blocking the semaphore. The first fix solves the memory problem but introduces a throughput regression; the second fix restores throughput while keeping memory under control.

Conclusion

Message 3104 is a masterclass in diagnostic reasoning under uncertainty. The assistant, armed with fresh instrumentation data, makes a preliminary analysis that is partially correct but incomplete. The true picture — 28 provers and 99 aux buffers at peak — only emerges with deeper probing. But the message's value lies not in its completeness but in its direction: it confirms that the instrumentation works, that the memory problem is real and measurable, and that the path forward requires addressing the fundamental imbalance between synthesis throughput and GPU consumption.

For the systems engineer, the lesson is timeless: measure first, then optimize. The buffer counters transformed an opaque OOM crash into a tractable pipeline engineering problem, and message 3104 is the moment that transformation began.