The Critical Grep: How a Single Command Uncovered ~12 GiB of Wasted Memory Per Partition

The Message

In the middle of a deep optimization session for the SUPRASEAL_C2 Groth16 proof generation pipeline, the assistant executed the following command:

[assistant] [bash] grep -n "provers\[.\]\.a\b\|provers\[.\]\.b\b\|provers\[.\]\.c\b\|prover\.a\b\|prover\.b\b\|prover\.c\b" /home/theuser/curio/extern/supraseal-c2/cuda/groth16_cuda.cu
847:        err = cudaHostRegister((void*)provers[0].a, abc_bytes, cudaHostRegisterDefault);
850:            err = cudaHostRegister((void*)provers[0].b, abc_bytes, cudaHostRegisterDefault);
854:            err = cudaHostRegister((void*)provers[0].c, abc_bytes, cudaHostRegisterDefault);
861:            if (host_c_registered) { cudaHostUnregister((void*)provers[0].c); host_c_registered = false; }
862:            if (host_b_registered) { cudaHostUnregister((void*)provers[0].b); host_b_registered = ...

At first glance, this appears to be a routine grep — the kind of command a developer runs dozens of times a day. But in the context of this optimization session, this single command was a turning point. It confirmed a hypothesis that would lead to freeing approximately 12 GiB of memory per partition, directly addressing a severe memory capacity bottleneck that had been causing out-of-memory (OOM) failures at higher parallelism levels.

Context: The Memory Wall

To understand why this grep mattered, we need to understand the problem it was solving. The Phase 12 split GPU proving API had just been implemented and benchmarked. The split API decoupled the b_g2_msm CPU computation from the GPU worker loop, allowing the GPU worker to pick up the next synthesized partition approximately 1.7 seconds faster. Benchmarking at pw=10 (partition workers = 10) showed a solid 37.1 seconds per proof — a ~2.4% improvement over the Phase 11 baseline of 38.0 seconds.

But there was a problem. When the team tried to increase partition workers to 12 (pw=12), the system ran out of memory. Peak RSS hit 668 GiB on a 755 GiB machine — only 87 GiB of headroom, and the kernel needed some of that for page tables and its own operations. The OOM killer struck. Even more puzzling, the memory jump from pw=10 to pw=12 was 301 GiB, far more than the expected 2 × ~13 GiB for two extra workers. Something was amplifying memory pressure.

The user's question — "the pending proof handle has nothing that can be freed early?" — set the assistant on a precise investigative path. The PendingProofHandle was a new data structure introduced in Phase 12. It held all the Rust-side data that needed to stay alive between prove_start (which dispatched the GPU work and returned immediately) and finalize (which completed the proof after the background b_g2_msm thread finished). If the handle was holding data that the background thread didn't actually need, that memory could be freed early, reducing peak pressure.

The Investigation

The assistant began by reading the PendingProofHandle struct definition in supraseal.rs ([msg 3056]). The handle contained an opaque C++ handle, a circuit count, and "Rust-side data" — but the struct definition was truncated in the read. The assistant then traced the C++ prep_msm_thread — the background thread that runs b_g2_msm — to understand exactly which data it read from the Rust-owned structures ([msg 3057]).

The prep_msm_thread accessed each partition's ProvingAssignment through a heap-copied provers_owned array (the use-after-free fix from earlier in Phase 12). Each ProvingAssignment contained pointers to several large data regions:

1. a, b, c — NTT evaluation vectors, each approximately 4 GiB (130 million elements × 32 bytes per scalar), totaling ~12 GiB per partition
2. inp_assignment_data / aux_assignment_data — the variable assignments, with aux_assignment being ~4 GiB and input_assignment being tiny (~10 KB)
3. Density trackers (a_aux_density, b_inp_density, b_aux_density) — bitvectors of approximately 16 MB each
4. r_s, s_s — small random scalars, already copied into C++ heap memory The critical question was: which of these did the prep_msm_thread actually read? The assistant ran a grep to find references to prover.a, prover.b, prover.c inside the prep_msm_thread lambda ([msg 3058]). The awk command failed due to a regex escaping issue, but the intent was clear: search the thread's code for reads of the NTT evaluation vectors.

The Discovery

This brings us to the subject message ([msg 3060]). The assistant ran a refined grep with a corrected regex pattern, searching the entire groth16_cuda.cu file for any reference to provers[N].a, provers[N].b, provers[N].c, prover.a, prover.b, or prover.c. The results were definitive:

• Lines 847, 850, 854: cudaHostRegister calls for provers[0].a, provers[0].b, provers[0].c — these register the host memory for GPU access
• Lines 861, 862: cudaHostUnregister calls for provers[0].c and provers[0].b — these release the registration after GPU kernels finish Every single reference to a, b, or c was in the GPU kernel region (lines 847–1195), which completes before generate_groth16_proofs_start_c returns. None of them appeared in the prep_msm_thread background thread code. This was the smoking gun. The massive ~12 GiB NTT evaluation vectors were only needed during the GPU kernel execution phase — the cudaHostRegister made them accessible to the GPU, the GPU kernels read them, and then cudaHostUnregister released them. By the time the C++ function returned to Rust, the GPU was done with a, b, and c. But the PendingProofHandle was holding onto them until finalize completed, approximately 1.7 seconds later.

The Reasoning Process

The assistant's thinking, visible across messages [msg 3056] through [msg 3062], reveals a methodical investigative approach:

1. Start with the data structure: Read the PendingProofHandle definition to understand what it holds
2. Trace the consumer: Examine the prep_msm_thread to see what it actually reads
3. Separate by lifetime: Distinguish between data needed during GPU execution (which completes before the function returns) and data needed during background CPU computation (which runs after)
4. Quantify the impact: Calculate the size of each data category — ~12 GiB for a/b/c, ~4 GiB for aux_assignment, ~48 MB for density trackers
5. Formulate the optimization: Free a/b/c immediately in prove_start, before storing the handle The assistant correctly identified that input_assignment and aux_assignment had already been moved out of the ProvingAssignment during synthesis (via std::mem::take), so those Vecs were already empty. The density trackers were small and genuinely needed by the background thread. But a, b, and c — the dominant memory consumers — were being held hostage.

Assumptions and Correctness

The assistant made one key assumption: that the GPU had truly finished reading a, b, and c by the time generate_groth16_proofs_start_c returned. This assumption was validated by the grep results showing cudaHostUnregister calls at lines 861–862, which occur within the function body (not in the background thread). CUDA's cudaHostUnregister is synchronous with respect to GPU kernel completion — it blocks until all pending GPU operations using the registered memory have completed. So the unregister calls serve as a guarantee that the GPU is done.

One subtle consideration: the grep only searched for direct references to provers[0].a, provers[0].b, provers[0].c and prover.a, prover.b, prover.c. Could the background thread access these vectors through an indirect path? The assistant had already confirmed in [msg 3057] that the prep_msm_thread uses provers_safe[c] (the heap-copied Assignment structs), and those copies contain pointers to the original a, b, c vectors. But the grep showed no code path in the thread that dereferences those pointers for a/b/c — the thread only accesses inp_assignment_data, aux_assignment_data, and the density bitvectors.

Input Knowledge Required

To understand this message, one needs:

1. The Phase 12 architecture: Knowledge that prove_start returns immediately after GPU work is dispatched, while finalize waits for the background b_g2_msm thread. The PendingProofHandle bridges these two calls.
2. CUDA memory model: Understanding of cudaHostRegister (pins host memory for GPU DMA access) and cudaHostUnregister (releases the pinning, implying GPU is done). The fact that unregister is synchronous with GPU completion is critical.
3. Groth16 proof structure: Knowledge that each partition produces NTT evaluation vectors a, b, c (polynomial evaluations over the scalar field) that are ~130M elements each, and that these are distinct from the variable assignments and density bitvectors.
4. The memory pressure problem: Awareness that pw=12 causes OOM with 668 GiB peak RSS, and that every GiB saved per partition directly increases the achievable parallelism.

Output Knowledge Created

This message produced several concrete insights:

1. Proof that a/b/c are GPU-only: The grep definitively showed that provers[0].a/b/c only appear in cudaHostRegister/cudaHostUnregister calls within the GPU kernel region. They are not referenced in the background thread.
2. Quantified savings opportunity: Approximately 12 GiB per partition can be freed immediately after prove_start returns, rather than being held for the ~1.7 seconds until finalize completes.
3. Actionable optimization path: The assistant immediately created a TODO item to "Free provers a/b/c immediately after prove_start (before finalize)" and began implementing the change in the next message ([msg 3063]).
4. Deeper understanding of memory pressure: The discovery explained why pw=12 caused such a dramatic memory increase. With j=15 concurrent jobs and pw=12 partition workers, up to 12 partitions could be in the PendingProofHandle state simultaneously, each holding ~12 GiB of unnecessary a/b/c data — that's 144 GiB of waste.

The Broader Impact

This grep command exemplifies a pattern that appears throughout high-performance systems optimization: the most impactful insights often come from simple questions about data lifetime. The user asked "can anything be freed early?" — a question about when data is last used, not when it was created. The assistant traced the data flow from allocation through GPU consumption to eventual deallocation, and found a mismatch between the actual last-use point and the deallocation point.

The fix was straightforward: in prove_start, after the C++ call returns, clear the a, b, c vectors from the ProvingAssignment structs before storing them in the PendingProofHandle. The Rust code would simply set provers[0].a = Vec::new(), provers[0].b = Vec::new(), provers[0].c = Vec::new(), allowing the allocator to reclaim ~12 GiB immediately.

This optimization would directly impact the achievable partition worker count. With 12 GiB freed per in-flight partition, and up to 12 partitions in flight simultaneously, the peak memory reduction could be as high as 144 GiB — potentially enough to make pw=12 viable on the 755 GiB machine, or to allow higher concurrency at pw=10.

Conclusion

The grep command in message 3060 is a masterclass in targeted investigation. It asked a precise question — "where are a/b/c referenced?" — and got a definitive answer. The answer revealed a significant memory waste that was invisible until someone thought to ask about data lifetimes across the split API boundary. In a system where every GiB of memory translates to throughput (through higher partition parallelism), this single command paved the way for a meaningful optimization.