
Over seven months, Simone Campanoni engineered advanced optimization passes for the google/xls compiler, focusing on resource sharing, select operation transformation, and IR narrowing. Leveraging C++ and Python, Simone developed features such as Select Lifting and resource sharing passes that fold identical operations, optimize bit-widths, and merge select nodes to improve hardware efficiency and compilation speed. The work involved algorithm design, BDD analysis, and static analysis to ensure correctness and maintainability. Each feature was accompanied by comprehensive test coverage and careful refactoring, resulting in a more performant, reliable, and scalable compiler infrastructure for array-heavy and performance-critical workloads.

September 2025 monthly summary for google/xls: Key features delivered and major accomplishments focusing on performance improvements in the XLS compiler's negation handling. Two targeted narrowing-pass optimizations were implemented in the IR to improve efficiency for negation operations. No major bugs documented in this period. Overall impact: faster builds and more efficient code generation through reduced IR workload and narrower bit-widths. Technologies demonstrated: IR-level optimization, bit-width analysis, MSB/predictability detection, trailing-zero handling, and robust Git commit discipline.
September 2025 monthly summary for google/xls: Key features delivered and major accomplishments focusing on performance improvements in the XLS compiler's negation handling. Two targeted narrowing-pass optimizations were implemented in the IR to improve efficiency for negation operations. No major bugs documented in this period. Overall impact: faster builds and more efficient code generation through reduced IR workload and narrower bit-widths. Technologies demonstrated: IR-level optimization, bit-width analysis, MSB/predictability detection, trailing-zero handling, and robust Git commit discipline.
2025-07 monthly summary: Delivered a major performance feature in google/xls by enhancing Resource Sharing Memoization, achieving >10x speedup in the BDD engine through optimized node-side-effect and def-use analysis. No critical bugs reported this month. Overall impact: faster resource-sharing pass enables larger workloads, faster builds, and improved runtime responsiveness. Technologies/skills demonstrated: advanced memoization, performance profiling, BDD internals, and commit-level impact.
2025-07 monthly summary: Delivered a major performance feature in google/xls by enhancing Resource Sharing Memoization, achieving >10x speedup in the BDD engine through optimized node-side-effect and def-use analysis. No critical bugs reported this month. Overall impact: faster resource-sharing pass enables larger workloads, faster builds, and improved runtime responsiveness. Technologies/skills demonstrated: advanced memoization, performance profiling, BDD internals, and commit-level impact.
2025-06 Monthly Summary for google/xls: Delivered a significant IR-level optimization improvement via an expanded Resource Sharing Pass, focusing on area efficiency and performance trade-offs through delay-aware folding.
2025-06 Monthly Summary for google/xls: Delivered a significant IR-level optimization improvement via an expanded Resource Sharing Pass, focusing on area efficiency and performance trade-offs through delay-aware folding.
May 2025: Delivered correctness and performance improvements to the Resource Sharing Pass in google/xls, along with test suite modernization. Impact includes faster builds, more robust folding decisions, and reduced maintenance burden, enabling scalable IR optimization.
May 2025: Delivered correctness and performance improvements to the Resource Sharing Pass in google/xls, along with test suite modernization. Impact includes faster builds, more robust folding decisions, and reduced maintenance burden, enabling scalable IR optimization.
April 2025 (2025-04) monthly summary for google/xls: Delivered core IR optimization passes focused on performance, correctness, and maintainability in the XLS compiler. Implemented and extended resource sharing optimization to fold identical IR multiplications, with flag-based enablement and extended coverage across def-use chains, select cases, and varying bit-widths. Added a pass to merge consecutive PrioritySelect and OneHotSelect operations to simplify the IR and improve pipeline efficiency. Strengthened correctness by refining mutual-exclusivity analysis to properly classify multiplications in non post-dominated scenarios. All changes accompanied by unit/integration tests to guard regressions and support safe rollout.
April 2025 (2025-04) monthly summary for google/xls: Delivered core IR optimization passes focused on performance, correctness, and maintainability in the XLS compiler. Implemented and extended resource sharing optimization to fold identical IR multiplications, with flag-based enablement and extended coverage across def-use chains, select cases, and varying bit-widths. Added a pass to merge consecutive PrioritySelect and OneHotSelect operations to simplify the IR and improve pipeline efficiency. Strengthened correctness by refining mutual-exclusivity analysis to properly classify multiplications in non post-dominated scenarios. All changes accompanied by unit/integration tests to guard regressions and support safe rollout.
March 2025 for google/xls: Implemented binary priority select support in the receive_default_value_simplification path, including IsBinaryPrioritySelect helper and extended matching logic to handle both Select and PrioritySelect; added TransformableConditionalReceiveWithPrioritySelect test. Introduced a dedicated select_merging_pass to consolidate PrioritySelect and OneHotSelect optimizations, deferred merging to avoid blocking other passes, and refactored tests and build config to reflect structural changes. These changes improve correctness and reliability of optimization passes, modularize the pipeline for future enhancements, and reduce build fragility, with tests updated accordingly.
March 2025 for google/xls: Implemented binary priority select support in the receive_default_value_simplification path, including IsBinaryPrioritySelect helper and extended matching logic to handle both Select and PrioritySelect; added TransformableConditionalReceiveWithPrioritySelect test. Introduced a dedicated select_merging_pass to consolidate PrioritySelect and OneHotSelect optimizations, deferred merging to avoid blocking other passes, and refactored tests and build config to reflect structural changes. These changes improve correctness and reliability of optimization passes, modularize the pipeline for future enhancements, and reduce build fragility, with tests updated accordingly.
In 2024-11, delivered the Select Lifting optimization pass for arrays in the XLS compiler (google/xls), delivering measurable performance improvements and reduced hardware area on array-heavy code paths. The feature transforms select operations on arrays into a two-step select/index followed by a single array access, enabling more compact hardware and faster execution. The work includes generalization of applicability and profitability guards to accommodate different input types, support for select nodes with no cases, and comprehensive test coverage to prevent regressions. In addition to implementing the core optimization, the changes included targeted refactors and naming improvements to improve maintainability.
In 2024-11, delivered the Select Lifting optimization pass for arrays in the XLS compiler (google/xls), delivering measurable performance improvements and reduced hardware area on array-heavy code paths. The feature transforms select operations on arrays into a two-step select/index followed by a single array access, enabling more compact hardware and faster execution. The work includes generalization of applicability and profitability guards to accommodate different input types, support for select nodes with no cases, and comprehensive test coverage to prevent regressions. In addition to implementing the core optimization, the changes included targeted refactors and naming improvements to improve maintainability.
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