Purdue-SoCET/tensor-core
Feb 2025 – Mar 2025
2 Months active
Languages Used
MakefileSystemVerilogVerilog
Technical Skills
Build SystemsDigital DesignDigital Logic DesignHardware Description LanguageHardware Description Language (HDL)Hardware Design
cmiotto20
PROFILE
Cmiotto20
Chris Miotto contributed to the Purdue-SoCET/tensor-core repository by developing foundational hardware modules for both GEMM computation and branch prediction. He refactored the GEMM core interface, clarified signal handling, and expanded verification coverage through new SystemVerilog testbenches and Verilator-based static analysis, improving reliability and maintainability. In parallel, Chris designed and integrated a configurable branch prediction path, implementing BPT and BTB modules with parameterized interfaces and comprehensive testbenches in Verilog. His work established modular, reusable hardware blocks and robust build systems, enabling rapid experimentation and safer optimizations in the tensor-core pipeline while reducing regression risk and maintenance overhead.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
10Total
Bugs
0
Commits
10
Features
4
Lines of code
1,347
Activity Months2
Work History
March 2025
4 Commits • 2 Features
Mar 1, 2025Month: 2025-03 — Focused on delivering foundational branch-prediction hardware and its integration into Purdue-SoCET/tensor-core. Key features delivered include: (1) Branch Prediction Core: BPT and BTB modules with configurable size, interfaces for branch-prediction interactions, and accompanying testbenches. (2) TBP Integration: Tournament Branch Predictor (TBP) top-level integrating GShare and 2-bit predictors with a Branch Target Buffer, updated interfaces, and parameterization to enable configurable predictor sizes within fetch_tbp. Major bugs fixed: No explicit bug fixes reported in this period; work emphasized feature development, integration, and verification. Overall impact and accomplishments: Establishes a reusable, configurable branch-prediction path for performance studies and optimization in the tensor-core pipeline. The work enables rapid experimentation with TBP configurations and lays groundwork for performance-driven tuning in subsequent sprints. Technologies/skills demonstrated: Verilog/SystemVerilog design, hardware interface design, testbench construction, TBP architecture (GShare/2-bit predictors with BTB), and parameterization techniques for configurable hardware blocks. Business value delivered includes enabling more accurate branch prediction simulations, faster iteration on predictor configurations, and improved evaluation capabilities for performance improvements in the core tensor pipeline.
4 Commits • 2 Features
Mar 1, 2025Month: 2025-03 — Focused on delivering foundational branch-prediction hardware and its integration into Purdue-SoCET/tensor-core. Key features delivered include: (1) Branch Prediction Core: BPT and BTB modules with configurable size, interfaces for branch-prediction interactions, and accompanying testbenches. (2) TBP Integration: Tournament Branch Predictor (TBP) top-level integrating GShare and 2-bit predictors with a Branch Target Buffer, updated interfaces, and parameterization to enable configurable predictor sizes within fetch_tbp. Major bugs fixed: No explicit bug fixes reported in this period; work emphasized feature development, integration, and verification. Overall impact and accomplishments: Establishes a reusable, configurable branch-prediction path for performance studies and optimization in the tensor-core pipeline. The work enables rapid experimentation with TBP configurations and lays groundwork for performance-driven tuning in subsequent sprints. Technologies/skills demonstrated: Verilog/SystemVerilog design, hardware interface design, testbench construction, TBP architecture (GShare/2-bit predictors with BTB), and parameterization techniques for configurable hardware blocks. Business value delivered includes enabling more accurate branch prediction simulations, faster iteration on predictor configurations, and improved evaluation capabilities for performance improvements in the core tensor pipeline.
March 2025
February 2025
6 Commits • 2 Features
Feb 1, 2025February 2025 — Purdue-SoCET/tensor-core monthly summary focusing on business value and technical achievements. The main work centered on the GEMM core path to improve reliability, signal clarity, and verification coverage, with build hygiene enhancements to support scalable development. Key features delivered: - GEMM core interface refactor and verification enhancements: Refactor fu_gemm interface and weight handling for clearer signals; rename and repurpose new_weight signals; simplify gemm_matrix_num handling when gemm_enable is active; added a new testbench and expanded verification coverage for fu_gemm. - Build tooling and static analysis improvements for GEMM verification: Added Verilator linting target to the Makefile and enabled static checks; ensured proper inclusion of dependencies; minor build/test tooling refinements. Major bugs fixed: - Stabilized the GEMM verification path by addressing previously untested logic, with commits progressing from 'untested logic for gemm' to 'done and tested' and 'tested'; introduced a TB to validate the end-to-end flow and reduce regression risk. Overall impact and accomplishments: - Increased reliability of the GEMM core and confidence in hardware/software co-design; expanded test coverage enables safer optimizations and faster iteration cycles; improved build hygiene reduces maintenance costs and regression risk for future GEMM enhancements. Technologies/skills demonstrated: - SystemVerilog/Verilog verification, testbench development, Verilator linting, static analysis, Makefile-based build tooling, dependency management, and verification methodology.
February 2025
6 Commits • 2 Features
Feb 1, 2025February 2025 — Purdue-SoCET/tensor-core monthly summary focusing on business value and technical achievements. The main work centered on the GEMM core path to improve reliability, signal clarity, and verification coverage, with build hygiene enhancements to support scalable development. Key features delivered: - GEMM core interface refactor and verification enhancements: Refactor fu_gemm interface and weight handling for clearer signals; rename and repurpose new_weight signals; simplify gemm_matrix_num handling when gemm_enable is active; added a new testbench and expanded verification coverage for fu_gemm. - Build tooling and static analysis improvements for GEMM verification: Added Verilator linting target to the Makefile and enabled static checks; ensured proper inclusion of dependencies; minor build/test tooling refinements. Major bugs fixed: - Stabilized the GEMM verification path by addressing previously untested logic, with commits progressing from 'untested logic for gemm' to 'done and tested' and 'tested'; introduced a TB to validate the end-to-end flow and reduce regression risk. Overall impact and accomplishments: - Increased reliability of the GEMM core and confidence in hardware/software co-design; expanded test coverage enables safer optimizations and faster iteration cycles; improved build hygiene reduces maintenance costs and regression risk for future GEMM enhancements. Technologies/skills demonstrated: - SystemVerilog/Verilog verification, testbench development, Verilator linting, static analysis, Makefile-based build tooling, dependency management, and verification methodology.
Activity
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Quality Metrics
Correctness76.0%
Maintainability80.0%
Architecture74.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MakefileSystemVerilogVerilog
Technical Skills
Branch PredictionBuild SystemsComputer ArchitectureDigital DesignDigital Logic DesignHardware Description LanguageHardware Description Language (HDL)Hardware DesignHardware VerificationMakefile scriptingRTL DesignStatic AnalysisSystemVerilogTestbench DevelopmentTestbench development
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