Chunk 11.0
This chunk documents the completion of Phase 2 of the **cuzk** pipelined SNARK proving engine, marking a major architectural milestone. The central achievement is the implementation of a true async overlap pipeline where CPU-bound circuit synthesis for proof *N+1* runs concurrently with GPU-bound proving for proof *N*, mediated by a bounded tokio channel for backpressure. A critical technical pivot was the discovery that per-partition pipelining was 6.6x slower than batch synthesis, leading to a default strategy where all 10 PoRep partitions are synthesized at once via rayon. E2E validation on an RTX 5070 Ti confirmed a 1.27x speedup over sequential execution, with three consecutive 32 GiB PoRep proofs completing in 212.7 seconds (~60s/proof steady-state throughput). The chunk reveals extensive reverse-engineering and deep integration work required to achieve this. Key discoveries include the exact JSON-within-JSON serialization format of C1 outputs, the necessity of a bellperson fork to expose private synthesis/assignment internals (`ProvingAssignment`, `synthesize_circuits_batch`, `prove_from_assignments`), and the decision to bypass the global `GROTH_PARAM_MEMORY_CACHE` by using `SuprasealParameters::new()` directly for explicit SRS lifetime control. The architecture now supports all four proof types (PoRep, WinningPoSt, WindowPoSt, SnapDeals) through a unified two-stage pipeline, with a dedicated `SrsManager` handling tiered memory residency. Detailed performance baselines, circuit sizes (e.g., ~136 GiB intermediate state for a full PoRep batch), and exact param file mappings are meticulously documented, showcasing a deeply data-driven engineering approach. The project is in a clean, well-committed state (8 commits, branch `feat/cuzk`, 15 passing tests, zero warnings) and is ready to advance to Phase 3: cross-sector batching. Immediate remaining tasks include E2E GPU validation for the WinningPoSt, WindowPoSt, and SnapDeals pipeline paths. The roadmap extends through Phase 5 (Pre-Compiled Constraint Evaluator), with Phase 4 targeting compute optimizations like SmallVec and parallel MSMs. Overall, this chunk serves not just as a status report, but as a comprehensive technical reference capturing every critical detail from CID parsing to feature flag architecture, ensuring the project is built on a foundation of empirical evidence and precise implementation.