EPFL-LAP/dynamatic
Nov 2024 – Aug 2025
6 Months active
Languages Used
C++CMakeLLVMLLVM IRShellVHDLVerilogC
Technical Skills
Algorithm DesignBoolean LogicCompiler DesignCompiler DevelopmentControl Flow AnalysisData Structures
Giacomo Sansone
PROFILE
Giacomo Sansone
Giacomo Sansone contributed to the EPFL-LAP/dynamatic repository by developing and optimizing compiler infrastructure for hardware design flows. Over six months, he engineered features such as the Fast Token Delivery (FTD) algorithm for efficient control-flow to handshake dialect conversion, advanced Boolean logic analysis, and robust Gated Single Assignment (GSA) analysis. His work involved deep integration with MLIR and LLVM, leveraging C++ and Python to implement static analysis, IR manipulation, and HDL simulation support. By refactoring conversion pipelines and enhancing analysis passes, Giacomo improved circuit generation scalability, maintainability, and reliability, demonstrating strong expertise in compiler development and hardware description languages.
Overall Statistics
Feature vs Bugs
82%Features
Repository Contributions
14Total
Bugs
2
Commits
14
Features
9
Lines of code
5,515
Activity Months6
Your Network
12 people
Work History
August 2025
1 Commits • 1 Features
Aug 1, 2025In August 2025, EPFL-LAP/dynamatic delivered the Fast Token Delivery (FTD) algorithm for cf to handshake dialect conversion, refactoring the conversion flow to use FTD methodology, and added new conversion passes alongside updates to analysis and support libraries. This work lays the foundation for faster, more scalable circuit generation and smoother future extensibility. There were no major defects fixed this month; focus was on delivering the new capability and stabilizing the conversion pipeline.
1 Commits • 1 Features
Aug 1, 2025In August 2025, EPFL-LAP/dynamatic delivered the Fast Token Delivery (FTD) algorithm for cf to handshake dialect conversion, refactoring the conversion flow to use FTD methodology, and added new conversion passes alongside updates to analysis and support libraries. This work lays the foundation for faster, more scalable circuit generation and smoother future extensibility. There were no major defects fixed this month; focus was on delivering the new capability and stabilizing the conversion pipeline.
August 2025
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 in EPFL-LAP/dynamatic focused on foundational work for the Fast Token Delivery (FTD) algorithm, establishing the groundwork for a new conversion pass and introducing an experimental transform pass to simplify circuit design. The work is exploratory but strategically important, setting the stage for future refactoring feedback, performance improvements, and a more scalable token delivery pipeline.
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 in EPFL-LAP/dynamatic focused on foundational work for the Fast Token Delivery (FTD) algorithm, establishing the groundwork for a new conversion pass and introducing an experimental transform pass to simplify circuit design. The work is exploratory but strategically important, setting the stage for future refactoring feedback, performance improvements, and a more scalable token delivery pipeline.
February 2025
3 Commits • 1 Features
Feb 1, 2025February 2025: Key delivery across the EPFL-LAP/dynamatic project focused on reliability, extensibility, and future readiness. Key features delivered include an extension of the GSA analysis to handshake::MergeOp with refactored headers and new constructors/analysis methods to support future FTD integration. Major bugs fixed include CI/test suite stability for release builds and VHDL simulation: skipping invalid MLIR tests in release mode to avoid segmentation faults; resolving missed dependencies in VHDL floating-point ops (sitofp and fptosi) preventing instantiation failures; and correcting erroneous marking of the float_basic test as failing. Overall impact: improved release reliability and HDL simulation stability, enabling faster feedback loops and more predictable releases. Foundational work also strengthens readiness for future integration efforts. Technologies/skills demonstrated: MLIR/GSA analysis extension, VHDL floating-point dependency fixes, CI/CD reliability improvements, and code refactoring for maintainability and extensibility.
3 Commits • 1 Features
Feb 1, 2025February 2025: Key delivery across the EPFL-LAP/dynamatic project focused on reliability, extensibility, and future readiness. Key features delivered include an extension of the GSA analysis to handshake::MergeOp with refactored headers and new constructors/analysis methods to support future FTD integration. Major bugs fixed include CI/test suite stability for release builds and VHDL simulation: skipping invalid MLIR tests in release mode to avoid segmentation faults; resolving missed dependencies in VHDL floating-point ops (sitofp and fptosi) preventing instantiation failures; and correcting erroneous marking of the float_basic test as failing. Overall impact: improved release reliability and HDL simulation stability, enabling faster feedback loops and more predictable releases. Foundational work also strengthens readiness for future integration efforts. Technologies/skills demonstrated: MLIR/GSA analysis extension, VHDL floating-point dependency fixes, CI/CD reliability improvements, and code refactoring for maintainability and extensibility.
February 2025
January 2025
4 Commits • 2 Features
Jan 1, 2025January 2025 focused on delivering foundational improvements for Fast Token Delivery (FTD), stabilizing HDL integration paths, and optimizing loop bitwidth handling. Key outcomes include a groundwork for FTD built on BlockIndexing and region-based Control Dependence Analysis, enabling faster token delivery planning and extensible analysis tools; HDL merge-related fixes that restore reliable Verilog generation and VHDL merge integration for simulation and synthesis; and a loop optimization that uses unsigned comparisons for positive bounds, improving bitwidth handling and the efficiency of subsequent compilation steps. Collectively, these efforts enhance performance, reliability, and readiness for future FTD integration while expanding MLIR/Region-based analysis and HDL tooling capabilities.
January 2025
4 Commits • 2 Features
Jan 1, 2025January 2025 focused on delivering foundational improvements for Fast Token Delivery (FTD), stabilizing HDL integration paths, and optimizing loop bitwidth handling. Key outcomes include a groundwork for FTD built on BlockIndexing and region-based Control Dependence Analysis, enabling faster token delivery planning and extensible analysis tools; HDL merge-related fixes that restore reliable Verilog generation and VHDL merge integration for simulation and synthesis; and a loop optimization that uses unsigned comparisons for positive bounds, improving bitwidth handling and the efficiency of subsequent compilation steps. Collectively, these efforts enhance performance, reliability, and readiness for future FTD integration while expanding MLIR/Region-based analysis and HDL tooling capabilities.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 Monthly Summary for EPFL-LAP/dynamatic: Key feature delivered: - HandshakeOptimizeBitwidths: preserve operation names during optimization. This enhancement integrates a NameAnalysis to rewrite patterns and updates operations to retain meaningful names, improving debuggability and readability of the optimized IR. Major bugs fixed: - None recorded in this dataset. Overall impact and accomplishments: - Increased maintainability and traceability of the optimization pipeline by guaranteeing consistent naming across transformed IR, enabling faster debugging and easier handoffs to downstream consumers. - Strengthened the reliability of the HandshakeOptimizeBitwidths pass and set a foundation for future name-preserving optimizations. Technologies/skills demonstrated: - NameAnalysis integration and pattern rewriting in MLIR-like IR pipelines - Compiler optimization pass design and robust naming discipline - Change ownership traceability (commit: 86e50729d5ed52561f9fe3e3011a95094138d6b8) and issue linkage (#212).
1 Commits • 1 Features
Dec 1, 2024December 2024 Monthly Summary for EPFL-LAP/dynamatic: Key feature delivered: - HandshakeOptimizeBitwidths: preserve operation names during optimization. This enhancement integrates a NameAnalysis to rewrite patterns and updates operations to retain meaningful names, improving debuggability and readability of the optimized IR. Major bugs fixed: - None recorded in this dataset. Overall impact and accomplishments: - Increased maintainability and traceability of the optimization pipeline by guaranteeing consistent naming across transformed IR, enabling faster debugging and easier handoffs to downstream consumers. - Strengthened the reliability of the HandshakeOptimizeBitwidths pass and set a foundation for future name-preserving optimizations. Technologies/skills demonstrated: - NameAnalysis integration and pattern rewriting in MLIR-like IR pipelines - Compiler optimization pass design and robust naming discipline - Change ownership traceability (commit: 86e50729d5ed52561f9fe3e3011a95094138d6b8) and issue linkage (#212).
December 2024
November 2024
3 Commits • 3 Features
Nov 1, 2024November 2024 monthly summary for EPFL-LAP/dynamatic: Delivered three core capabilities improving boolean reasoning, SSA/GSA semantics, and control-flow analysis, enabling faster optimization decisions and deeper program analysis. These efforts deliver business value through faster boolean reasoning and token delivery, improved program analysis, and groundwork for further optimizations and gating semantics.
November 2024
3 Commits • 3 Features
Nov 1, 2024November 2024 monthly summary for EPFL-LAP/dynamatic: Delivered three core capabilities improving boolean reasoning, SSA/GSA semantics, and control-flow analysis, enabling faster optimization decisions and deeper program analysis. These efforts deliver business value through faster boolean reasoning and token delivery, improved program analysis, and groundwork for further optimizations and gating semantics.
Activity
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Quality Metrics
Correctness82.8%
Maintainability79.2%
Architecture77.2%
Performance69.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
CC++CMakeLLVMLLVM IRPythonShellVHDLVerilog
Technical Skills
Algorithm DesignAlgorithm ImplementationBoolean LogicBuild SystemsCI/CDCode OptimizationCompiler DesignCompiler DevelopmentControl Flow AnalysisData StructuresHDL DevelopmentHardware Description Language (HDL)Hardware DesignIR ManipulationIntermediate Representation (IR) Manipulation
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