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## Summary This chunk represents a deep-dive investigation into the SUPRASEAL_C2 Groth16 proof generation pipeline for Filecoin PoRep, driven by the goal of understanding and dramatically reducing its ~200 GiB peak memory footprint. The work proceeded in two major phases: first, a comprehensive mapping of the entire call chain from Curio's Go task layer through Rust FFI (bellperson) into C++/CUDA kernels (supraseal-c2), with detailed memory accounting showing exactly where each GiB goes (10 parallel partition circuits at ~16 GiB each, plus ~48 GiB SRS in pinned memory). Second, after the user challenged to "think bigger," the analysis expanded to include the Curio orchestration model, circuit value distribution statistics (~99% boolean aux_assignment), and computational hotpath characterization at the instruction level (SHA-256 bit manipulation, Fr field arithmetic, NTT memory bandwidth, GPU kernel occupancy). The key achievements were the production of four comprehensive documents: a background reference capturing the full pipeline architecture with file:line references and nine identified structural bottlenecks, plus three composable optimization proposals. Proposal 1 (Sequential Partition Synthesis) breaks the all-10-partitions-in-parallel model to reduce peak memory from ~200 GiB to ~64-103 GiB by streaming partitions one-at-a-time through the GPU. Proposal 2 (Persistent Prover Daemon) eliminates the ~60s per-proof SRS loading overhead by keeping the proving process alive across proofs. Proposal 3 (Cross-Sector Batching) exploits the freed memory headroom to batch multiple sectors' circuits into single GPU invocations, projecting 2-3× throughput per GPU and 5-6× reduction in $/proof when combined. A final round of micro-optimization analysis then examined CPU synthesis hotpaths (enforce() loop, SHA-256 bit manipulation, Fr addition), GPU NTT/MSM compute characteristics, H-to-D transfer patterns, and the feasibility of recomputing a/b/c vectors on-the-fly to avoid materialization entirely. The overarching theme is a shift from optimizing individual proof generation toward architecting a continuous, memory-efficient proving pipeline optimized for heterogeneous cloud rental markets where RAM cost dominates.

From 200 GiB to Pipeline Architecture: The Complete SUPRASEAL_C2 Groth16 Optimization Journey 2522 words

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