From Compilation to Capacity: The Full Arc of Phase 12's Split GPU Proving API

Introduction

In the world of high-performance GPU-accelerated cryptographic proof generation, the difference between a successful optimization and a catastrophic regression can hinge on a single dangling pointer, a misordered allocation, or an overlooked memory ceiling. This article examines a single chunk of an opencode coding session — spanning 144 messages from message index 2910 to 3053 — that captures the complete lifecycle of Phase 12: Split (async) GPU Proving API for the SUPRASEAL_C2 Groth16 proving engine used in Filecoin's Proof-of-Replication (PoRep) pipeline.

What makes this chunk remarkable is not just the technical complexity of the work — which spans Rust async runtimes, C++ CUDA kernels, and the fragile FFI boundary between them — but the narrative arc it traces. The chunk begins with a broken build and a comprehensive status document ([msg 2910]), proceeds through a systematic gauntlet of compilation fixes, achieves a clean build and a successful benchmark (37.1 seconds per proof, a 2.4% improvement), discovers a critical use-after-free concurrency bug in the C++ CUDA code, diagnoses a hard memory capacity ceiling at 668 GiB RSS, and finally culminates in a git commit and a completed todo list. It is a microcosm of the entire engineering process: design, implementation, debugging, measurement, discovery, and acceptance of limits.

This article synthesizes the key moments of this chunk, tracing the threads that connect the compilation fixes, the concurrency bug, the memory investigation, and the final commit. It is a story about how complex systems are built — not in a straight line from specification to delivery, but through a recursive cycle of hypothesis, experiment, failure, and refinement.

The State of Play: A Broken Build and a Plan

The chunk opens with message [msg 2910], a comprehensive status document that the assistant produces at a critical juncture. Phase 11 has been successfully committed, achieving 38.0 seconds per proof through memory-bandwidth interventions. Phase 12 — the split GPU proving API — is partially implemented but broken. The assistant's message is a masterclass in engineering transparency: it documents every file that has been modified, every function that exists, every compilation error, and every remaining task.

The core idea of Phase 12 is elegant in its simplicity. In the existing architecture, each GPU worker follows a cycle: acquire the GPU lock, run GPU kernels (~1.8s), release the GPU lock, run b_g2_msm (~1.7s), run the epilogue (~0ms), and loop back for the next partition. The 1.7 seconds spent on b_g2_msm — a CPU-side multi-scalar multiplication on the G2 curve — blocks the GPU worker from picking up the next synthesized partition. If synthesis is producing partitions faster than the GPU workers can consume them, the pipeline backs up, and the GPU eventually starves.

The Phase 12 split API decouples these operations. The GPU worker calls gpu_prove_start, which runs the GPU kernels, releases the GPU lock, and spawns a background C++ thread (prep_msm_thread) to compute b_g2_msm. The worker immediately loops back to pick up the next partition. A separate Rust tokio task (the finalizer) later joins the background thread, runs the epilogue, and routes the result. The goal is to hide the 1.7s b_g2_msm latency behind the GPU worker's next cycle.

But the status document reveals that the implementation is incomplete. The PendingGpuProof type alias doesn't exist. The helper functions process_partition_result and process_monolithic_result — which encapsulate ~300 lines of inline result-processing logic — haven't been extracted. The trait bounds on prove_start are mismatched. The continue statements inside async blocks are incorrect. The build is thoroughly broken.

This status document is not a confession of failure; it is a strategic pause. By writing down the exact state of every file, the assistant creates a navigable map of the remaining work. The subsequent messages in the chunk will systematically address each item on this map.

The Compilation Gauntlet: Seven Errors and Their Fixes

The next 45 messages (approximately [msg 2916] through [msg 2955]) document a systematic triage of compilation errors. The assistant runs cargo build and iteratively fixes each error that emerges. The errors span multiple layers of the system:

Missing types and structs. The SynthesisCapacityHint struct is missing from the Rust code — it's needed by the C++ FFI but hasn't been defined yet. The assistant adds it. The PendingGpuProof type alias is missing from pipeline.rs — the assistant defines it as a tuple type (PendingProofHandle<Bls12>, Option<usize>, Instant).

Unused generic parameters. The start_groth16_proof FFI function has an unused generic parameter E that causes a compilation error. The assistant removes it, recognizing that the FFI boundary doesn't need the generic — the C++ code works with a concrete curve type.

Trait bound mismatches. The prove_start method's parameter params has a trait bound that doesn't match how it's used. The assistant changes it from params: &P (by reference) to params: P (by value), resolving the mismatch. This is a subtle fix — the trait bound P: Parameters<E> was being satisfied by &P in one context but P in another, and the compiler's error message required careful interpretation.

Async control flow bugs. The spawned finalizer task contains continue statements that were intended to exit the task early under certain conditions. But in Rust, continue inside an async block or closure doesn't work the same way as in a loop body — it attempts to continue the enclosing loop, which doesn't exist. The assistant replaces them with return, which properly exits the spawned task.

Each of these fixes is individually small, but collectively they represent a deep engagement with the Rust type system, the FFI boundary, and the async runtime. The assistant is not just making the code compile — it is ensuring that the type-level invariants are correct, that ownership is properly managed across the language boundary, and that the async control flow matches the intended execution model.

The moment of clean compilation arrives at [msg 2955], and the assistant's relief is palpable. The message reads simply: Build succeeded. No errors. After dozens of messages of debugging, the code finally compiles. But as the assistant knows, compilation is only the first gate. Runtime correctness is a separate, more demanding test.

The Benchmark: 37.1 Seconds Per Proof

With a clean build achieved, the assistant launches the Phase 12 benchmark at [msg 2961]. The configuration matches the Phase 11 baseline: gw=2 (two GPU workers), pw=10 (ten partition workers), gt=32 (32 GPU threads), j=15 (15 concurrent jobs). The daemon starts, and the benchmark runs 20 proofs.

The result is 37.1 seconds per proof — a 2.4% improvement over the Phase 11 baseline of 38.0 seconds. The split API works. The b_g2_msm offloading is delivering the expected throughput gain.

But the assistant's analysis in [msg 2962] and [msg 2963] reveals nuance. The first proof takes 466 seconds due to cold-start effects (GPU warm-up, SRS cache population). The average gpu_ms per partition is 3.2 seconds, suggesting that the GPU workers are spending most of their time on GPU kernels and the split API is successfully hiding the b_g2_msm latency. The log confirms that the split code path is active: "GPU prove complete (split)" messages appear for every partition.

The 37.1 second result is a validation of the Phase 12 design. But it is also a modest improvement. The assistant has spent dozens of messages fixing compilation errors and concurrency bugs to gain 0.9 seconds per proof. The question now is: can the system be pushed further?

Probing the Memory Ceiling

The natural next step is to increase parallelism. If pw=10 works, perhaps pw=12 or pw=15 will yield even better throughput by reducing queueing. The assistant tries this at [msg 2974] and beyond, and the results are dramatic — but not in the way expected.

With pw=12, the daemon is killed by the OOM (Out of Memory) killer. The assistant, having set up an RSS monitoring loop, collects the trace and discovers the peak: 668 GiB on a system with 755 GiB total ([msg 3044]). The five highest RSS measurements are 653.1, 655.3, 665.5, 666.4, and 668.3 GiB. With only ~87 GiB of headroom, the system simply cannot sustain the additional memory pressure.

The user's response at [msg 2990] — "It's not 400GB tho, something is leaking somewhere" — pushes back against the assistant's initial hypothesis that the OOM is simply a capacity issue. The user suspects a memory leak. The assistant, despite having initial evidence that the memory returns to baseline after the benchmark completes (RSS drops to 71 GiB), takes the user's skepticism seriously and begins a deeper investigation.

This investigation, spanning [msg 2991] through [msg 3010], is a masterclass in systematic debugging. The assistant traces the memory lifecycle through the Rust async deallocation paths, examines the C++ DEALLOC_MTX mutex, checks whether malloc_trim is being called, and builds a global buffer tracker with atomic counters (buf_synth_start, buf_abc_freed, buf_dealloc_done). The instrumentation reveals that the provers counter peaks at 28 — meaning 28 synthesized partitions are queued holding their full ~16 GiB datasets, far more than the pw=12 limit would suggest.

The root cause is a subtle interaction between the partition semaphore and the GPU channel. The semaphore releases immediately after synthesis completes, allowing the next partition to start synthesizing. But the synthesized partition then blocks on the single-slot GPU channel, waiting for a GPU worker to pick it up. With pw=12 and gw=2, the GPU workers can process at most 2 partitions at a time, but synthesis can produce up to 12. The queue of synthesized partitions grows, each holding ~16 GiB of NTT evaluation vectors. The memory pressure is not a leak — it is a structural consequence of the pipeline's concurrency model.

The Use-After-Free: A Bug Within a Bug

While investigating the memory pressure, the assistant makes a discovery that changes the trajectory of the debugging session. At [msg 3011], while tracing whether Rust-owned memory must remain alive during the background b_g2_msm thread, the assistant realizes that the C++ provers array itself — a stack-local variable in generate_groth16_proofs_start_c — is captured by reference in the prep_msm_thread lambda.

The lambda capture [&, num_circuits] captures all automatic variables by reference. The provers parameter — a C-style array that decays to a stack pointer — is captured by reference. When generate_groth16_proofs_start_c returns, that stack variable is destroyed. The background thread continues running b_g2_msm, reading through a dangling reference. This is textbook undefined behavior.

The assistant's analysis is meticulous. It traces through the C++ code with grep and awk to identify every reference to provers inside the thread lambdas. It distinguishes between references that are safe (the GPU thread, which runs inside a lock that is joined before function return) and references that are unsafe (the prep_msm_thread, which runs after the function returns). It traces the Rust FFI chain in lib.rs to confirm the full picture of how provers flows from Rust through the FFI boundary into C++.

The fix, implemented across [msg 3017] through [msg 3034], is to copy the provers array into the heap-allocated groth16_pending_proof struct as provers_owned — a std::vector<Assignment<fr_t>> that lives on the heap and outlives the function call. The background thread references provers_owned instead of the stack-allocated provers. This is a small change in terms of lines of code, but it represents a fundamental understanding of C++ lambda capture semantics, stack lifetime, and the ownership model required for safe concurrency across the Rust/C++ boundary.

The assistant initially wonders whether this use-after-free bug might be causing the OOM — perhaps the undefined behavior is corrupting heap metadata and preventing proper deallocation. But after fixing the bug and re-running the benchmark at [msg 3043], the OOM persists. The RSS trace shows the same 668 GiB peak. The UB fix was necessary for correctness, but it was not the cause of the memory pressure. The hypothesis is cleanly rejected, and the assistant pivots back to structural analysis.

The Commit: Sealing Phase 12 into History

Despite the memory ceiling, Phase 12 is a success. The split API works, the benchmark shows a measurable improvement, and a critical concurrency bug has been fixed. At [msg 3051], the assistant commits the Phase 12 implementation to the feat/cuzk branch with a detailed changelog:

feat(cuzk): Phase 12 — split (async) GPU proving API

Decouple b_g2_msm CPU computation from the GPU worker loop so the GPU worker
can pick up the next synthesized partition ~1.7s faster.

Key changes:
- C++: generate_groth16_proofs_start_c / finalize_groth16_proof_c split
- C++: prep_msm_thread runs b_g2_msm in background
- C++: groth16_pending_proof struct holds all shared state
- Rust: PendingProofHandle<E> in bellperson
- Rust: PendingGpuProof type alias in pipeline.rs
- Rust: gpu_prove_start / finish_pending_proof in engine.rs
- Fix use-after-free: prep_msm_thread now reads provers_owned (heap copy)
- Fix compilation errors: missing structs, unused generics, trait bounds
- Benchmark: 37.1s/proof (2.4% improvement over Phase 11 baseline of 38.0s)

The commit adds 1,275 lines and deletes 439 across 6 files. It is the culmination of the entire chunk's work.

The todo list at [msg 3053] completes the narrative. Four items are marked completed: the compilation fixes, the pw=10 benchmark (37.1s/proof), the pw=12/15 OOM diagnosis (memory capacity, not leak), and the use-after-free fix. The todo list is not just a status update — it is a compressed narrative of the entire Phase 12 journey, from broken build to successful commit.

The Themes That Bind the Chunk

Several themes recur throughout this chunk, connecting the compilation fixes, the concurrency bug, and the memory investigation into a coherent narrative.

The primacy of measurement. The assistant's debugging methodology is grounded in empirical measurement. When the OOM strikes, the assistant doesn't guess at the cause — it sets up an RSS monitoring loop, collects data, and analyzes the trace. When the user suspects a leak, the assistant builds a global buffer tracker with atomic counters to get real-time visibility into memory state. When the use-after-free is discovered, the assistant traces every reference with grep to confirm the analysis. Every hypothesis is tested against data.

The fragility of cross-language boundaries. The Phase 12 split API spans three language boundaries: Rust async code (engine.rs, pipeline.rs), Rust FFI declarations (lib.rs, supraseal.rs), and C++ CUDA kernels (groth16_cuda.cu). Each boundary introduces its own failure modes. The Rust type system catches some errors at compile time (missing types, trait bound mismatches), but the most dangerous bugs — the use-after-free, the memory accumulation — are invisible to the compiler. They require runtime observation and careful reasoning about lifetimes.

The nonlinearity of memory scaling. The assistant's mental model of memory scaling is linear: 2 more workers = 2 more partitions × ~16 GiB = ~32 GiB more memory. The actual increase from pw=10 to pw=12 is 301 GiB — nearly 10× the expected value. This nonlinearity reveals complex interactions in the pipeline: faster synthesis (more workers) causes more proofs to be parsed from the queue, more PendingProofHandle objects to accumulate, and more partitions to be queued waiting for the GPU channel. The semaphore, designed to limit concurrency, releases too early, allowing the queue to grow unboundedly.

The acceptance of limits. The chunk ends not with a triumphant breakthrough but with an acceptance of the system's physical limits. The 668 GiB peak RSS at pw=12 is a hard ceiling for the current architecture. The assistant does not try to squeeze more parallelism out of the system — it documents the constraint and moves on. This is a mature engineering response: not every problem can be solved with code changes; some are fundamental to the hardware and the workload.

Conclusion

The 144 messages of this chunk trace a complete engineering cycle: from a broken build and a comprehensive status document, through a systematic gauntlet of compilation fixes, to a successful benchmark, a critical concurrency bug discovery, a memory capacity diagnosis, and finally a git commit that seals the work into the repository's history.

The Phase 12 split GPU proving API is now committed. It delivers a 2.4% throughput improvement — 37.1 seconds per proof versus 38.0 seconds — while fixing a dangerous use-after-free bug that could have caused corrupted proofs or crashes in production. The memory ceiling at 668 GiB is documented and understood, setting the stage for future work on reducing per-partition memory footprint.

But the deeper story of this chunk is about the engineering process itself. It is about how complex systems are built through iteration, measurement, and the willingness to confront failure. It is about the value of writing things down — the status document at [msg 2910] and the todo list at [msg 3053] bookend the chunk, providing structure and clarity at the beginning and closure at the end. It is about the interplay between human intuition (the user's "something is leaking somewhere") and empirical data (the RSS trace, the buffer counters). And it is about the quiet satisfaction of a clean build, a working benchmark, and a commit that captures the accumulated understanding of dozens of debugging hours.

In the end, Phase 12 is not just a code change. It is a documented journey through the challenges of high-performance GPU proving — a journey that reveals as much about the system's architecture as about the engineering discipline required to improve it.