Chunk 29.0

In this chunk, the assistant completed the implementation and benchmarking of Phase 11's three memory-bandwidth interventions, then began designing a split API to offload b_g2_msm from the GPU worker's critical path. After committing the Phase 10 post-mortem and Phase 11 design spec, the assistant implemented Intervention 1 (serializing async_dealloc with a static mutex in both C++ and Rust), Intervention 2 (reducing `groth16_pool` from 192 to 32 threads via `gpu_threads = 32`), and Intervention 3 (a global atomic throttle flag set by C++ around b_g2_msm and checked by Rust's SpMV with `yield_now`). A full benchmark sweep at c=20 j=15 showed that Intervention 2 alone delivered the best result: 36.7 s/proof, a 3.4% improvement over the Phase 9 baseline of 38.0 s. Interventions 1 and 3 had negligible additional impact, and increasing GPU workers to 3 or 4 made throughput worse due to CPU contention. After the user asked whether b_g2_msm could be shipped to a separate thread to unblock the GPU worker, the assistant analyzed the dependency chain and confirmed that b_g2_msm (~1.7 s with 32 threads) runs after the GPU lock is released but still blocks the worker from picking up the next job. A split API design was devised: `generate_groth16_proofs_start_c` returns an opaque handle after GPU unlock, and a separate `finalize_groth16_proof` call joins the b_g2_msm thread, runs the epilogue, and writes the final proof. The assistant began restructuring the C++ code to allocate a `groth16_pending_proof` struct early so that its fields serve as the shared state for both GPU threads and the deferred finalization, ensuring stable memory addresses while allowing the GPU worker to loop back immediately. The overarching themes are deep memory-subsystem bottleneck analysis (TLB shootdowns, L3 thrashing, DDR5 bandwidth contention), iterative microbenchmark-driven optimization with careful attention to not killing parallelism, and a pragmatic split-API approach that decouples GPU kernel execution from CPU post-processing to hide latency. The work balances aggressive optimization against the risk of introducing complexity, with the user explicitly guiding the trade-off between performance gains and code maintainability.

From Memory Bandwidth to Architectural Restructuring: The Phase 11–12 Transition in a GPU Proving Pipeline 2206 words

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