Over the past year, contributed to the tathagatasrimani/codesign repository by building a comprehensive hardware/software co-design framework focused on scalable modeling, optimization, and benchmarking. Developed and integrated advanced scheduling algorithms, hardware modeling infrastructure, and automated testing workflows using Python, C++, and CVXPY. Enhanced simulation fidelity and performance analysis by implementing robust support for technology models such as BSIM4 and Virtual Source, and streamlined design-space exploration with YAML-driven configuration and GUI-based installers. Addressed reliability and maintainability through extensive code refactoring, environment setup automation, and continuous integration, enabling reproducible builds, faster onboarding, and consistent results across complex hardware design and optimization pipelines.
March 2026 — Tathagatasrimani/codesign: Delivered Codesign Framework Enhancements with Automated Testing, Setup Scripts, and GUI Installer. Implemented automated testing workflows, improved environment setup scripts for reproducible dev/test environments, and introduced a user-friendly GUI installer to simplify installation. This work was delivered via PR #181 (codesign-build-improvements-2) merged by Srikar, commit be4bdcbf6c5f4c8f2e866c1b94e46e01e3953c59. Impact: faster release cycles, reduced setup time and manual errors, improved onboarding for new contributors. Technologies demonstrated: automated testing frameworks, shell scripting for setup scripts, GUI development for installer, Git-based collaboration and build workflow improvements.
March 2026 — Tathagatasrimani/codesign: Delivered Codesign Framework Enhancements with Automated Testing, Setup Scripts, and GUI Installer. Implemented automated testing workflows, improved environment setup scripts for reproducible dev/test environments, and introduced a user-friendly GUI installer to simplify installation. This work was delivered via PR #181 (codesign-build-improvements-2) merged by Srikar, commit be4bdcbf6c5f4c8f2e866c1b94e46e01e3953c59. Impact: faster release cycles, reduced setup time and manual errors, improved onboarding for new contributors. Technologies demonstrated: automated testing frameworks, shell scripting for setup scripts, GUI development for installer, Git-based collaboration and build workflow improvements.
January 2026 (2026-01) monthly summary for tathagatasrimani/codesign highlighting business value and technical achievements. Key accomplishments include expanded StreamHLS testing and build integration, groundwork for DSE sweep infra, and progress on persistence/optimization tooling. Critical bug fixes were deployed to improve reliability and data integrity, and build/environment enhancements increased stability and reproducibility across submodules and toolchains.
January 2026 (2026-01) monthly summary for tathagatasrimani/codesign highlighting business value and technical achievements. Key accomplishments include expanded StreamHLS testing and build integration, groundwork for DSE sweep infra, and progress on persistence/optimization tooling. Critical bug fixes were deployed to improve reliability and data integrity, and build/environment enhancements increased stability and reproducibility across submodules and toolchains.
December 2025 consolidated a focused cycle on stability, modeling capabilities, and measurement across the codesign project. The team delivered targeted features for design-space exploration and performance analysis, stabilized core scheduling/optimization paths, expanded testing and benchmarking, and strengthened OpenRoad/StreamHLS integration. This work reduces risk in production merges, accelerates iteration cycles, and improves visibility into system behavior under realistic workloads. Key business outcomes included: improved scheduling reliability for llama and scalehls paths, richer analysis with sensitivity tooling, and broader hardware-aware testing and benchmarking support. The work also lays groundwork for future optimizations by exposing better metrics and integration hooks while simplifying repository maintenance and visibility into performance bottlenecks. What was delivered (highlights): - Sensitivity Analysis Module wired into the analysis pipeline and exposed for experiments. (commit: 477585a7...) - New Tech Model integration across the system, including multiple refinements and integration edits. (commits: 9f0766d..., a50f1383..., 9e50bb5d..., df7523f7...) - Display enhancements to improve operational visibility and decision-making dashboards. (commit: 4f61f3f3...) - ScaleHLS test configuration improvements to enable configurable DSP settings for hardware-tuned tests. (commit: e75a17d2...) - Power constraint feature added to broaden design-space exploration around energy efficiency. (commit: 4d9533ee...) - Benchmark suite expansion and testing infrastructure improvements to broaden coverage and facilitate regression testing. (commits: 195c314a..., c22e2a9d..., 88be3cf7...) - OpenRoad integration and analysis enhancements, including improved output handling, log barriers for sensitivity analysis, and enhanced graph construction. (multiple commits: c3dc7bc5..., 2e5bb9b4..., 6f2c3d10..., 41b67fe4...) - Llama scheduling and HLS scale fixes, PD checkpoint resolution, constraint slack/scaling fixes, and related robustness improvements to the optimization loop. (commits: e3ce8e14..., 13558f21..., 2089f2a2..., 01352526..., 587eb12f..., 21d4fb55...) - Testing/test-compatibility refinements including PyTorch ScaleHLS test fixes, Vitis schedule parse fixes, and robustness/two-way parsing enhancements. (commits: a4b12278..., 6b681af1..., 3481e16b..., b1c9d01c..., 870f10c3...) - Submodule cleanup to simplify repository topology and reduce maintenance burden by removing codesign-opt submodule. (commit: 885a85ad...) Overall impact: The month yielded a stronger, more reliable design-evaluation loop with improved tooling for exploring design decisions, better hardware-aware testing, and richer instrumentation for performance analysis. These improvements position the team to accelerate features-to-production while reducing the risk of regressions in critical scheduling and optimization paths.
December 2025 consolidated a focused cycle on stability, modeling capabilities, and measurement across the codesign project. The team delivered targeted features for design-space exploration and performance analysis, stabilized core scheduling/optimization paths, expanded testing and benchmarking, and strengthened OpenRoad/StreamHLS integration. This work reduces risk in production merges, accelerates iteration cycles, and improves visibility into system behavior under realistic workloads. Key business outcomes included: improved scheduling reliability for llama and scalehls paths, richer analysis with sensitivity tooling, and broader hardware-aware testing and benchmarking support. The work also lays groundwork for future optimizations by exposing better metrics and integration hooks while simplifying repository maintenance and visibility into performance bottlenecks. What was delivered (highlights): - Sensitivity Analysis Module wired into the analysis pipeline and exposed for experiments. (commit: 477585a7...) - New Tech Model integration across the system, including multiple refinements and integration edits. (commits: 9f0766d..., a50f1383..., 9e50bb5d..., df7523f7...) - Display enhancements to improve operational visibility and decision-making dashboards. (commit: 4f61f3f3...) - ScaleHLS test configuration improvements to enable configurable DSP settings for hardware-tuned tests. (commit: e75a17d2...) - Power constraint feature added to broaden design-space exploration around energy efficiency. (commit: 4d9533ee...) - Benchmark suite expansion and testing infrastructure improvements to broaden coverage and facilitate regression testing. (commits: 195c314a..., c22e2a9d..., 88be3cf7...) - OpenRoad integration and analysis enhancements, including improved output handling, log barriers for sensitivity analysis, and enhanced graph construction. (multiple commits: c3dc7bc5..., 2e5bb9b4..., 6f2c3d10..., 41b67fe4...) - Llama scheduling and HLS scale fixes, PD checkpoint resolution, constraint slack/scaling fixes, and related robustness improvements to the optimization loop. (commits: e3ce8e14..., 13558f21..., 2089f2a2..., 01352526..., 587eb12f..., 21d4fb55...) - Testing/test-compatibility refinements including PyTorch ScaleHLS test fixes, Vitis schedule parse fixes, and robustness/two-way parsing enhancements. (commits: a4b12278..., 6b681af1..., 3481e16b..., b1c9d01c..., 870f10c3...) - Submodule cleanup to simplify repository topology and reduce maintenance burden by removing codesign-opt submodule. (commit: 885a85ad...) Overall impact: The month yielded a stronger, more reliable design-evaluation loop with improved tooling for exploring design decisions, better hardware-aware testing, and richer instrumentation for performance analysis. These improvements position the team to accelerate features-to-production while reducing the risk of regressions in critical scheduling and optimization paths.
November 2025 monthly summary for tathagatasrimani/codesign: Delivered significant business value by advancing the BBV optimization pipeline, strengthening correctness with new constraints, enabling hierarchical preload across iterations, and extending support for the PyTorch DSE pipeline. Completed the first version of the schedule subsystem refactor with doitgen support, and expanded testing infrastructure to improve reliability and coverage. Concurrently, fixed critical issues that impacted stability and runtimes, and prepared the environment for broader experimentation with ScaleHLS and related pipelines.
November 2025 monthly summary for tathagatasrimani/codesign: Delivered significant business value by advancing the BBV optimization pipeline, strengthening correctness with new constraints, enabling hierarchical preload across iterations, and extending support for the PyTorch DSE pipeline. Completed the first version of the schedule subsystem refactor with doitgen support, and expanded testing infrastructure to improve reliability and coverage. Concurrently, fixed critical issues that impacted stability and runtimes, and prepared the environment for broader experimentation with ScaleHLS and related pipelines.
October 2025 performance summary for tathagatasrimani/codesign. Delivered foundational optimization flow and multiple subproblem strategies, including approximate and non-convex subproblems, with progress saving and performance enhancements. Implemented robust scheduling and hardware-modeling improvements (ResNet vector generation, AHMDAL limit, OpenRoad area/scale refinements, new metal layers, and wire length normalization). Significant reliability and stability gains via broad bug fixes across optimization, DSP usage, environment setup, and testing workflows, plus improvements to experiment workflows, logging, and deployment hygiene. Enabled higher throughput with concurrent codesign runs and improved visual feedback via dynamic plotting. Demonstrated strong technical skills in optimization, hardware design tooling, and software maintenance, delivering measurable business value: faster iterations, scalable workflows, and consistent results in test environments.
October 2025 performance summary for tathagatasrimani/codesign. Delivered foundational optimization flow and multiple subproblem strategies, including approximate and non-convex subproblems, with progress saving and performance enhancements. Implemented robust scheduling and hardware-modeling improvements (ResNet vector generation, AHMDAL limit, OpenRoad area/scale refinements, new metal layers, and wire length normalization). Significant reliability and stability gains via broad bug fixes across optimization, DSP usage, environment setup, and testing workflows, plus improvements to experiment workflows, logging, and deployment hygiene. Enabled higher throughput with concurrent codesign runs and improved visual feedback via dynamic plotting. Demonstrated strong technical skills in optimization, hardware design tooling, and software maintenance, delivering measurable business value: faster iterations, scalable workflows, and consistent results in test environments.
September 2025 performance summary for tathagatasrimani/codesign. Focused delivery across end-to-end scheduling, interface enhancements, and benchmarking readiness, elevating throughput, reliability, and business value for hardware/software co-design. Key outcomes include ScaleHLS UI/interface improvements with delay customization, robust schedule parsing (including multi-port memories), and integrated netlist-to-schedule flow for GEMM/Jacobi/ResNet with ResNet benchmarking. Preparations for additional Vitis interfaces and ongoing CNFET/MVS modeling laid groundwork for broader platform support. Enhanced execution-time measurement, debuggability, and a parallelism-driven performance push underpin rapid exploration and target tuning. Overall impact: accelerated design-space exploration, reduced configuration friction, and a scalable, testable path toward production-ready Vitis/ResNet workflows with measurable performance signals.
September 2025 performance summary for tathagatasrimani/codesign. Focused delivery across end-to-end scheduling, interface enhancements, and benchmarking readiness, elevating throughput, reliability, and business value for hardware/software co-design. Key outcomes include ScaleHLS UI/interface improvements with delay customization, robust schedule parsing (including multi-port memories), and integrated netlist-to-schedule flow for GEMM/Jacobi/ResNet with ResNet benchmarking. Preparations for additional Vitis interfaces and ongoing CNFET/MVS modeling laid groundwork for broader platform support. Enhanced execution-time measurement, debuggability, and a parallelism-driven performance push underpin rapid exploration and target tuning. Overall impact: accelerated design-space exploration, reduced configuration friction, and a scalable, testable path toward production-ready Vitis/ResNet workflows with measurable performance signals.
August 2025 monthly summary for tathagatasrimani/codesign. Key initiatives centered on advancing high-fidelity hardware modeling and scalable workflows. Virtual Source (VS) modeling: introduced, integrated, and validated across technology nodes; added configurability (tunable body thickness) and VS-specific equations, with YAML-based configuration and improved validation. BSIM4: enhanced configurability and accuracy, exposing effect toggles and updating parameters for dielectric constants, gate leakage, drain current, and capacitance. Optimization framework: improved workflow and scheduling around hardware modeling; added plotting linked to objective functions, new optimization constraints, and multicycle DFG optimization support. Project structure: refactor for maintainability, reorganized hardware model, forward/inverse passes, and import paths. These efforts increased modeling accuracy, reduced validation risk, and accelerated iteration, delivering business value through better design insights and scalable engineering processes. Technologies demonstrated include CVXPY integration for convex optimization, YAML-driven configuration, and Python-based tooling for model validation and scheduling.
August 2025 monthly summary for tathagatasrimani/codesign. Key initiatives centered on advancing high-fidelity hardware modeling and scalable workflows. Virtual Source (VS) modeling: introduced, integrated, and validated across technology nodes; added configurability (tunable body thickness) and VS-specific equations, with YAML-based configuration and improved validation. BSIM4: enhanced configurability and accuracy, exposing effect toggles and updating parameters for dielectric constants, gate leakage, drain current, and capacitance. Optimization framework: improved workflow and scheduling around hardware modeling; added plotting linked to objective functions, new optimization constraints, and multicycle DFG optimization support. Project structure: refactor for maintainability, reorganized hardware model, forward/inverse passes, and import paths. These efforts increased modeling accuracy, reduced validation risk, and accelerated iteration, delivering business value through better design insights and scalable engineering processes. Technologies demonstrated include CVXPY integration for convex optimization, YAML-driven configuration, and Python-based tooling for model validation and scheduling.
July 2025 monthly summary for tathagatasrimani/codesign. Focus on delivering robust BSIM4 transistor modeling, architecture improvements for tech models, and groundwork for scalable, reliable simulations. Key business value delivered through enhanced model accuracy, performance potential, and maintainability.
July 2025 monthly summary for tathagatasrimani/codesign. Focus on delivering robust BSIM4 transistor modeling, architecture improvements for tech models, and groundwork for scalable, reliable simulations. Key business value delivered through enhanced model accuracy, performance potential, and maintainability.
February 2025 monthly summary for tathagatasrimani/codesign. Focused on delivering core architecture improvements and establishing a robust hardware-design workflow with stronger memory modeling, scheduling accuracy, and graph/IR robustness. Resulted in improved simulation fidelity for multi-memory systems, more reliable scheduling decisions, and scalable infrastructure for hardware exploration.
February 2025 monthly summary for tathagatasrimani/codesign. Focused on delivering core architecture improvements and establishing a robust hardware-design workflow with stronger memory modeling, scheduling accuracy, and graph/IR robustness. Resulted in improved simulation fidelity for multi-memory systems, more reliable scheduling decisions, and scalable infrastructure for hardware exploration.
January 2025 performance summary for tathagatasrimani/codesign focused on strengthening modeling accuracy, debugging efficiency, and scheduling reliability to accelerate design-space exploration and decision-making. Delivered enhancements to the inverse pass and cacti controls, corrected latency scaling behavior, and introduced parasitics into the computation DFG. Strengthened debugging capabilities with a no-cacti flag and critical-path support, while improving documentation, tests, and tooling for maintainability and onboarding.
January 2025 performance summary for tathagatasrimani/codesign focused on strengthening modeling accuracy, debugging efficiency, and scheduling reliability to accelerate design-space exploration and decision-making. Delivered enhancements to the inverse pass and cacti controls, corrected latency scaling behavior, and introduced parasitics into the computation DFG. Strengthened debugging capabilities with a no-cacti flag and critical-path support, while improving documentation, tests, and tooling for maintainability and onboarding.
2024-12 Monthly Summary for tathagatasrimani/codesign focusing on feature delivery, bug fixes, and overall impact.
2024-12 Monthly Summary for tathagatasrimani/codesign focusing on feature delivery, bug fixes, and overall impact.
November 2024 monthly summary for tathagatasrimani/codesign. Delivered critical fixes and feature improvements across energy/latency scaling, symbolic expressions optimization, CACTI tooling, and data provenance for reproducible figures, plus a bug fix for unit scaling. These efforts enhanced model fidelity, plotting reproducibility, performance, and maintainability, enabling exact re-analysis of results and reducing manual debugging effort.
November 2024 monthly summary for tathagatasrimani/codesign. Delivered critical fixes and feature improvements across energy/latency scaling, symbolic expressions optimization, CACTI tooling, and data provenance for reproducible figures, plus a bug fix for unit scaling. These efforts enhanced model fidelity, plotting reproducibility, performance, and maintainability, enabling exact re-analysis of results and reducing manual debugging effort.
Overview of all repositories you've contributed to across your timeline