Chunk 24.0

This session implemented **Phase 8: Dual-Worker GPU Interlock**, which eliminated GPU idle gaps by narrowing the C++ static mutex in `generate_groth16_proofs_c` to cover only the CUDA kernel region (NTT+MSM, batch additions, tail MSMs). CPU preprocessing and `b_g2_msm` now run outside the lock, allowing two GPU workers per device to interleave — one does CPU work while the other runs CUDA kernels. The change spanned 7 files (~195 lines): the C++ CUDA kernel was refactored to accept a passed-in mutex pointer with narrowed scope, FFI plumbing threaded the mutex through `supraseal-c2` → `bellperson` → `pipeline.rs`, and the engine spawns `gpu_workers_per_device` workers (default 2) sharing a per-GPU C++ mutex allocated via new `create_gpu_mutex`/`destroy_gpu_mutex` helpers. Benchmark results were strong: single-proof GPU efficiency hit **100.0%** (zero idle gaps between partitions), and multi-proof throughput improved **13.2%** (44.0s/proof vs 50.7s for Phase 7 at c=5 j=3) and **17.2%** (49.5s vs 59.8s at c=5 j=2). A `partition_workers=30` test regressed to 60.4s/proof due to CPU contention starving GPU preprocessing threads, confirming pw=20 as the sweet spot for this 96-core machine. The implementation was committed as `2fac031f` on the `feat/cuzk` branch. The user then requested a sweep across `partition_workers` values 10, 12, 15, 18, and 20 to find the optimal setting, which the assistant began executing by restarting the daemon for each configuration.

From Implementation to Optimization: The Phase 8 Dual-Worker GPU Interlock and the Partition Workers Sweep 3321 words

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