Chunk 22.1

This chunk began with a critical correction from the user, dispelling the assistant's earlier assumption that PoRep C2 partitions were independent ~4s work units. The user revealed the actual timing: each partition requires ~29-36s of synthesis (25-27s sequential witness generation plus 4-10s SpMV evaluation), and they currently all run in parallel via rayon, finishing simultaneously in a "thundering herd." This forces the GPU to idle until all 10 partitions are ready, consumes massive memory (~136 GiB), and creates CPU contention. The user's key insight was to break the "10 circuits as a batch" abstraction and treat each partition as an independent work unit flowing through the pipeline one-by-one, enabling the GPU to start immediately on the first finished partition. The assistant rigorously analyzed this model through Python simulations, discovering a crucial nuance: for a single sector, reducing partition concurrency actually worsens performance due to the 10:1 synth-to-GPU time ratio. The real benefit of per-partition dispatch lies in **cross-sector pipelining**. This insight drove the design of a new Phase 7 architecture featuring a pool of 15-20 concurrent synthesis workers. These workers synthesize individual partitions and submit them to a bounded GPU channel, naturally throttling memory usage. The GPU worker proves each partition independently (using `num_circuits=1` to avoid the costly 25s `b_g2_msm` batch overhead), while a `ProofAssembler` in the `JobTracker` accumulates completed partitions. This allows Sector B's synthesis to begin immediately on freed workers while Sector A's partitions are still being GPU-proved, eliminating inter-sector GPU idle time. The session culminated in the creation of a comprehensive implementation specification (`c2-optimization-proposal-7.md`), which was committed to the repository. The document details the exact data structures, dispatch logic, error handling, memory budget (~429 GiB peak for 20 workers, well within the 754 GiB available), and expected performance gains (~30% throughput improvement to ~30s/proof steady-state with 100% GPU utilization). The key achievements were correcting the fundamental pipeline model, validating the cross-sector overlap concept through simulation, and producing a concrete, actionable Phase 7 design that promises to eliminate the structural GPU idle gap and significantly improve overall proving throughput.

From Thundering Herd to Continuous Pipeline: The Phase 7 Design Journey for PoRep C2 Proving 2816 words

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