
Worked on the scroll-tech/ceno repository to deliver GPU-accelerated proof generation and high-throughput chip proving, focusing on memory-aware scheduling and concurrent execution. Leveraged C++, Rust, and CUDA to implement a GPU prover, optimize batch sumcheck operations, and refactor the proving pipeline for safe parallelism using per-thread CUDA streams. Enhanced memory management by introducing configurable GPU cache levels and memory estimation, reducing buffer usage and improving throughput. Improved code maintainability through API cleanup, documentation, and cross-repo alignment. The work resulted in measurable performance gains, streamlined deployment, and greater scalability for zero-knowledge proof workloads on GPU-enabled infrastructure without introducing new bugs.
March 2026 (Month: 2026-03) summary for scroll-tech/ceno focused on enabling high-throughput GPU-accelerated chip proving through memory-aware scheduling and safe parallelism. Implemented a GPU-aware concurrent proving pipeline, introduced memory estimation, per-thread CUDA streams, and a three-phase architecture to maximize throughput while controlling VRAM usage. Documentation and performance benchmarking were completed to aid deployment and future optimization.
March 2026 (Month: 2026-03) summary for scroll-tech/ceno focused on enabling high-throughput GPU-accelerated chip proving through memory-aware scheduling and safe parallelism. Implemented a GPU-aware concurrent proving pipeline, introduced memory estimation, per-thread CUDA streams, and a three-phase architecture to maximize throughput while controlling VRAM usage. Documentation and performance benchmarking were completed to aid deployment and future optimization.
December 2025 focused on GPU performance and memory management improvements in the scroll-tech/ceno stack, delivering two targeted features and improving observability and API quality. The work enhances throughput, reduces memory footprint, and strengthens maintainability for scalable tower witnesses and GPU prover flows.
December 2025 focused on GPU performance and memory management improvements in the scroll-tech/ceno stack, delivering two targeted features and improving observability and API quality. The work enhances throughput, reduces memory footprint, and strengthens maintainability for scalable tower witnesses and GPU prover flows.
Month 2025-11: Key delivery in scroll-tech/ceno centered on upgrading cudarc to v0.17.3 with batch sumcheck performance improvements and code cleanup. The upgrade enhances runtime for batch sumcheck operations, while cleaning up outdated performance evaluations for GPU and tower witness builds to reduce maintenance burden. Cross-repo alignment with cudarc-related work (scroll-tech/ceno-gpu) improved traceability and consistency across GPU paths.
Month 2025-11: Key delivery in scroll-tech/ceno centered on upgrading cudarc to v0.17.3 with batch sumcheck performance improvements and code cleanup. The upgrade enhances runtime for batch sumcheck operations, while cleaning up outdated performance evaluations for GPU and tower witness builds to reduce maintenance burden. Cross-repo alignment with cudarc-related work (scroll-tech/ceno-gpu) improved traceability and consistency across GPU paths.
October 2025 (2025-10) performance summary for scroll-tech/ceno: Key feature delivered is the Babybear GPU Prover, enabling GPU-accelerated proof generation with optimizations for proof creation, batch commits, and main/tower proofs. Dependency updates and internal type mappings were added to support the GPU prover. No major bugs fixed this month in this repository. Overall impact: faster proof throughput, improved scalability for GPU-enabled workloads, and a cleaner, more maintainable codebase. Technologies demonstrated: GPU-accelerated proving, dependency management, type system alignment, batch processing, and proof pipeline integration.
October 2025 (2025-10) performance summary for scroll-tech/ceno: Key feature delivered is the Babybear GPU Prover, enabling GPU-accelerated proof generation with optimizations for proof creation, batch commits, and main/tower proofs. Dependency updates and internal type mappings were added to support the GPU prover. No major bugs fixed this month in this repository. Overall impact: faster proof throughput, improved scalability for GPU-enabled workloads, and a cleaner, more maintainable codebase. Technologies demonstrated: GPU-accelerated proving, dependency management, type system alignment, batch processing, and proof pipeline integration.

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