
During October 2025, Tathagata Srimani enhanced the tathagatasrimani/codesign repository by developing alpha scaling features for dynamic layout density in OpenRoad runs, enabling proportional scaling of design parameters such as track pitches, LEFs, and die area across technology nodes. Using Python and Tcl, Tathagata extended the configuration management system to support these scaling capabilities and updated submodule references to maintain build consistency with external dependencies. The work also introduced PolyBench-based Vitis kernel benchmarks, improving performance evaluation readiness. This engineering effort deepened the stack’s scalability, benchmarking, and maintainability, reflecting a strong grasp of backend development and EDA tool integration.

Month: 2025-10 observations for tathagatasrimani/codesign focused on scaling, benchmarking, and build hygiene. Delivered alpha-scaling enhancements for dynamic layout density via OpenRoad run (initial track pitch scaling), extended alpha scaling across design parameters for cross-node layout scaling, added PolyBench-based Vitis kernel benchmarks, and refreshed submodule/dependency references to keep builds in sync with external components. Progress on grid-alignment refinements in scaling; improved test/config coverage and performance evaluation readiness across technology nodes. This work strengthens scalability, performance benchmarking capabilities, and overall maintainability of the codesign stack.
Month: 2025-10 observations for tathagatasrimani/codesign focused on scaling, benchmarking, and build hygiene. Delivered alpha-scaling enhancements for dynamic layout density via OpenRoad run (initial track pitch scaling), extended alpha scaling across design parameters for cross-node layout scaling, added PolyBench-based Vitis kernel benchmarks, and refreshed submodule/dependency references to keep builds in sync with external components. Progress on grid-alignment refinements in scaling; improved test/config coverage and performance evaluation readiness across technology nodes. This work strengthens scalability, performance benchmarking capabilities, and overall maintainability of the codesign stack.
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