Chunk 1.0

This chunk represents a comprehensive shift from high-level architectural memory optimizations (Proposals 1-3) to deep, compute-level micro-optimizations across the entire C2 proof generation pipeline. The assistant systematically investigated the GPU kernel internals (NTT, MSM, batch addition), the CPU synthesis hotpath in bellperson, and the host-to-device transfer patterns. By reading dozens of source files across the C++ CUDA kernels, Rust prover, and blst assembly, the assistant identified 18 specific optimization opportunities, ranging from eliminating ~780 million heap allocations per partition in the `enforce()` loop to tuning GPU kernel occupancy and fixing shared memory bank conflicts. The findings were synthesized and documented in `c2-optimization-proposal-4.md`, providing a detailed implementation roadmap. Key achievements include the quantification of transfer pipeline penalties (pageable vs pinned memory for a,b,c vectors and tail MSM bases), the identification of a critical cooperative kernel bottleneck in the batch addition routine, and the ruling out of several previously hypothesized optimizations with concrete evidence (tensor cores, streaming NTT, SoA layout, and NUMA/THP impact). The analysis also confirmed the feasibility of parallelizing the B_G2 CPU MSM phase and fusing LDE_powers into NTT steps. The combined estimated speedup from these compute-level improvements is 30-43% on existing hardware, directly complementing the memory and throughput gains from Proposals 1-3. The chunk concludes with the user posing a sophisticated new research question: can the *known structure of the constraints*—specifically the dominance of SHA-256 boolean circuits (99% of aux assignment)—be exploited for pre-computation (compile or runtime) or mathematical batching transpositions? This moves the optimization frontier from generic compute improvements to domain-specific circuit exploitation, leveraging the deep understanding of the constraint structure already documented. The assistant is now prepared to investigate this new direction, which could unlock further significant performance gains by transforming how the prover handles the highly repetitive SHA-256 constraint patterns.

From Architecture to Assembly: The Complete Arc of the SUPRASEAL_C2 Optimization Campaign 2435 words

Message Articles

Subagent Sessions