The Pivot Question: Tracing Memory Across the Rust/C++ Boundary in Phase 12's Split GPU Proving API

In the high-stakes world of Filecoin proof generation, every millisecond counts and every gigabyte is precious. The SUPRASEAL_C2 pipeline, responsible for producing Groth16 proofs for 32 GiB sectors, operates at the edge of a 755 GiB memory ceiling, orchestrating a complex dance of CPU synthesis, GPU computation, and cross-language memory management. When the Phase 12 "split GPU proving API" was implemented to offload the b_g2_msm computation from the GPU worker's critical path, initial benchmarks were promising: 37.1 seconds per proof at partition_workers=10. But when the team tried to push synthesis parallelism higher — pw=12, pw=15 — the system crashed with out-of-memory errors. Message 2989 marks the critical turning point where the investigation shifted from assuming a simple capacity ceiling to hunting a genuine memory leak, and it begins with a single, precise question.

The Context: Phase 12's Split API and the OOM Wall

To understand message 2989, one must first understand what Phase 12 accomplished. The Groth16 proving pipeline for Filecoin's Proof-of-Replication (PoRep) is a multi-stage beast. After circuit synthesis (running on CPU), the GPU performs a series of multi-scalar multiplications (MSMs) and number-theoretic transforms (NTTs) to produce the proof. One of these MSMs — b_g2_msm — operates on the G2 curve and is relatively slow (~1.7 seconds). In the original architecture, the GPU worker thread would block during this computation, unable to pick up the next partition's work. Phase 12 split the API into prove_start (which launches the GPU kernels and returns immediately, spawning a background thread for b_g2_msm) and prove_finish (which waits for the background work to complete). This allowed the GPU worker to immediately begin processing the next partition, improving throughput by ~2.4%.

The initial benchmark at pw=10 succeeded with 37.1s/proof. Encouraged, the user asked to try higher partition worker counts ([msg 2964]: "Try higher synthesis partition_workers in config, maybe 15/20?"). The assistant tried pw=15 — immediate OOM. Then pw=12 — it completed 8 proofs before crashing. The assistant initially attributed this to simple capacity pressure ([msg 2984]: "The memory pressure is too high with 12 concurrent partition synthesis workers when you also have 15 concurrent jobs"). But the user pushed back ([msg 2985]: "OOM-ish again"; [msg 2986]: "Maybe we're not freeing b_g2_m mem?"), suspecting something more insidious than a capacity issue.

The Message: A Precise Question About Memory Lifecycles

Message 2989 is deceptively simple. The assistant writes:

Now let me check what the C++ side actually needs during b_g2_msm. The key question: does b_g2_msm reference any Rust-owned memory? Let me look at the C++ groth16_pending_proof struct and what generate_groth16_proofs_start_c copies:

Then it issues a read command to examine the C++ source file groth16_cuda.cu, specifically the generate_groth16_proofs_start_c function and the groth16_pending_proof struct.

This single question — does the background C++ thread reference Rust-owned memory? — is the linchpin of the entire memory investigation. If the answer is yes, then the PendingProofHandle (the Rust-side struct that holds synthesis data) must keep its contents alive until the background thread completes, which could explain elevated memory pressure. If the answer is no, then the Rust data could be freed immediately after prove_start returns, and the OOM must have a different cause.

The Reasoning: Methodical Debugging Across Language Boundaries

The assistant's thinking process in this message is a textbook example of cross-language memory debugging. The Phase 12 architecture introduced a new temporal decoupling: the GPU worker no longer waits for b_g2_msm to complete before picking up the next partition. But this decoupling creates a new question about ownership: who owns the synthesis data (the provers, input_assignments, and aux_assignments vectors) during the background computation?

In the pre-Phase 12 code, the answer was straightforward: the GPU worker thread held all data on its stack, and everything was freed when gpu_prove returned. In Phase 12, the PendingProofHandle struct was created to hold this data alive until finalization. But the assistant's earlier calculation ([msg 2987]) suggested this added only ~26 GiB of peak memory pressure (two pending handles × ~13 GiB each). The user's response ([msg 2990]: "It's not 400GB tho") made it clear that the OOM was far worse than 26 GiB could explain.

The assistant's reasoning in message 2989 shows a crucial insight: before diving into complex instrumentation or guessing about memory leaks, one must first understand the minimum memory that must be retained. The question "does b_g2_msm reference any Rust-owned memory?" is asking: is the ~13 GiB per partition necessarily alive during the background computation, or could it be freed? If the C++ code copied all needed data into its own heap structures during generate_groth16_proofs_start_c, then the Rust-side data could be freed immediately, and the PendingProofHandle would be holding memory unnecessarily. If the C++ code only captured raw pointers to Rust memory, then the Rust data must stay alive.

Assumptions and the User's Challenge

The assistant entered this message with an implicit assumption that the OOM at pw=12 was primarily a capacity problem — that 12 concurrent syntheses at ~13 GiB each, plus 15 concurrent job parsings at ~3 GiB each, plus the SRS (44 GiB) and PCE (26 GiB), simply exceeded the 755 GiB system memory. This assumption is visible in [msg 2984]: "The memory pressure is too high with 12 concurrent partition synthesis workers when you also have 15 concurrent jobs."

The user's challenge — "Maybe we're not freeing b_g2_m mem?" — was the catalyst that broke this assumption. The user suspected that the Phase 12 split API had introduced a genuine leak, not just a capacity ceiling. The assistant's response in [msg 2987] attempted to quantify the leak (26 GiB from two pending handles) but the user's follow-up ([msg 2990]: "It's not 400GB tho") revealed the true scale: the system was accumulating hundreds of gigabytes of extra memory, far beyond what two pending handles could explain.

This exchange reveals a subtle but important incorrect assumption in the assistant's initial thinking: that the memory pressure from the split API was proportional to the number of GPU workers (gw=2, so 2 pending handles). The actual problem, as later discovered (see Chunk 1), was that the partition semaphore released its permit immediately after synthesis completed, allowing synthesized partitions to pile up in a queue waiting for the single-slot GPU channel. The provers counter peaked at 28, meaning 28 synthesized partitions were holding their full ~16 GiB datasets simultaneously — over 448 GiB of accumulated synthesis data.

Input Knowledge Required

To fully understand message 2989, one needs knowledge of several interconnected systems:

  1. The Phase 12 split API architecture: How prove_start and prove_finish decouple the GPU worker from b_g2_msm, and how PendingProofHandle bridges the Rust and C++ sides.
  2. The C++ groth16_pending_proof struct: The heap-allocated C++ struct that holds GPU-side data (device pointers, split vectors) during the background computation.
  3. The Rust FFI boundary: How Rust passes provers, input_assignments, and aux_assignments to C++ via raw pointers, and the ownership semantics of those pointers.
  4. The b_g2_msm computation: The G2-curve multi-scalar multiplication that runs in a background prep_msm_thread, reading the prover's assignment data to compute the G2 proof elements.
  5. The memory lifecycle of a partition: From synthesis (allocating ~13 GiB of prover data), through GPU kernel launch (which reads this data on the device), to finalization (which joins the background thread and frees everything). Without this context, the question "does b_g2_msm reference any Rust-owned memory?" seems like a narrow technical detail. With this context, it becomes the central question governing whether the Phase 12 design is fundamentally sound or whether it has introduced a structural memory leak.

Output Knowledge Created

The immediate output of message 2989 is a file read — the assistant retrieves the C++ source code to examine the groth16_pending_proof struct and the generate_groth16_proofs_start_c function. But the knowledge created extends far beyond this single read:

  1. The confirmation that b_g2_msm reads Rust-owned memory: The subsequent messages ([msg 2995], [msg 2996]) reveal that the prep_msm_thread captures provers by reference and reads prover.inp_assignment_data and prover.aux_assignment_data — raw pointers into Rust's Vec<Arc<Vec<Fr>>>. This confirms that the Rust data must stay alive during the background computation, validating the PendingProofHandle design.
  2. The realization that the leak is elsewhere: Since the Rust data must stay alive anyway, the ~26 GiB from pending handles is necessary, not a leak. The real OOM cause — 28 queued partitions — lies in the pipeline's synchronization logic, not in the split API's memory retention.
  3. The methodological template: This message establishes a pattern for cross-language memory debugging — first establish what must be alive (by examining the C++ code's references), then measure what is actually alive (via instrumentation), then find the discrepancy.

The Thinking Process: A Debugging Microcosm

What makes message 2989 particularly interesting is what it reveals about the assistant's thinking process in miniature. The assistant could have responded to the OOM in many ways: by adding more instrumentation, by reverting to Phase 11, by tuning memory limits, or by guessing at leaks. Instead, it chose to ask a foundational question about memory ownership across the language boundary.

This is visible in the structure of the reasoning: "Now let me check what the C++ side actually needs during b_g2_msm." The word "actually" is telling — it signals a shift from assumption to verification. The assistant had been assuming that the PendingProofHandle was the source of extra memory, but the user's pushback ("It's not 400GB tho") demanded a deeper investigation. The assistant's response is to go to the source code and check what references exist.

The question is phrased as a binary: "does b_g2_msm reference any Rust-owned memory?" This binary framing is powerful because it reduces a complex memory analysis to a simple yes/no question that can be answered by reading the C++ code. If yes, the data must stay alive (necessary memory). If no, the data could be freed (potential leak). The assistant then proceeds to examine the evidence — reading the C++ struct definition and the generate_groth16_proofs_start_c function — to determine which case applies.

Significance in the Larger Narrative

Message 2989 sits at a crucial inflection point in the Phase 12 optimization journey. Before this message, the team was operating under the assumption that pw=10 was the memory ceiling and that further optimization would require reducing per-partition memory footprint. After this message, the investigation pivoted to understanding the pipeline's queuing dynamics — why 28 partitions could accumulate despite only 12 partition workers.

The subsequent investigation ([msg 2994] onwards) built global buffer trackers with atomic counters, discovered that the partition semaphore released too early, and ultimately fixed the memory buildup by increasing the GPU channel capacity from 1 to partition_workers. This fix reduced peak RSS from 668 GiB to 294.7 GiB and enabled pw=12 to run without OOM for the first time — a far more impactful optimization than the 2.4% throughput gain from the split API itself.

But none of that would have happened without the pivot initiated in message 2989. The question "does b_g2_msm reference any Rust-owned memory?" was the thread that, when pulled, unraveled the entire memory lifecycle and revealed the true bottleneck. It is a reminder that in complex systems, the most powerful debugging tool is not instrumentation or profiling — it is asking the right question about what must be true.