Free Download UVM Debug Masterclass (Part 1) Built-in Features, ML hooksPublished 2/2026
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Language: English |
Duration: 1h 24m |
Size: 1.6 GB
A deep dive into UVM reporting, SVA hooks, and UVMLint guidelines to prepare your testbench for AI/ML analytics.
Master UVM built-in debug hooks to gain deep visibility into the environment
Implement streamlined printing and advanced log management to achieve up to 100x savings in log file storage.
Integrate SVA (SystemVerilog Assertions) with UVM action blocks to create an intelligent, unified error-reporting strategy.
Prepare "ML-ready" environments by leveraging UVM Report Servers and JSON logging for automated data analysis.
Apply UVMLint guidelines to enforce high-performance verbosity and severity standards across the team.
RequirementsSolid Foundation in UVM: You should be comfortable with the UVM hierarchy (Agents, Drivers, Monitors, Scoreboards) and the base class library.
Basic Familiarity with Simulation Flows: Experience running a standard EDA simulator (VCS, Questasim, Xcelium, etc.) and looking at log files.
Not a "UVM 101" Course: This course is designed for those who already know how to build a testbench and now want to optimize and debug it at a professional level.
DescriptionStop drowning in log files and start leveraging your simulation data.Most UVM courses teach you how to build a testbench, but very few teach you how to efficiently debug, optimize, and extract value from it. In a production environment, simulation performance and debug turnaround time (TAT) are the true bottlenecks to tape-out. This course, UVM Debug Masterclass (Level 1), is designed to bridge the gap between basic testbench construction and professional-grade verification architecture.We begin with a quick UVM recap to ensure a solid foundation before diving deep into the built-in debug hooks that many engineers overlook. You will learn how to implement streamlined printing and master the UVM log API. With real-life project data, we show how users can achieve up to 100x savings in log file storage by choosing appropriate verbosity and using analytics -a critical factor for large-scale regressions.Why this course is different: We don't just talk about debugging; we talk about Data Readiness. You will learn how to prepare your environment for the future of verification by creating "data beacons." By utilizing UVM Report Servers and JSON logging, you will learn how to transform messy text logs into structured data ready for Machine Learning (ML) analysis, automated coverage closure, and advanced ID analysis.Key Topics Covered:Optimization: Impact of Verbosity and Severity on simulation speed.Integration: Connecting SVA action blocks with UVM for unified reporting.Standardization: Implementing UVMLint guidelines to enforce team-wide best practices.Architecture: Visualizing UVM Topology and Phasing to resolve complex parent-child issues.Case Study: A hands-on look at generating JSON logs for ML-driven regressions.Whether you are a Junior engineer looking to write better code, a Lead Architect optimizing a global regression suite, or a CAD engineer setting up ML-ready flows, this course provides the technical hooks and methodology needed for the next generation of Design Verification.
Who this course is forJunior to Mid-level DV Engineers: Those on the front lines of testbench implementation who want to master advanced debug hooks and write "production-grade" optimized code.
Verification Architects & Leads: Senior engineers looking to reduce debug turnaround time (TAT) and standardize high-performance verification methodologies across their teams.
CAD & Methodology Engineers: Professionals tasked with building the infrastructure for "ML-ready" flows, automated regressions, and data-driven verification.
Verification Managers: Leads who need to understand the ROI of log optimization and how to transform simulation data into actionable analytics.
SystemVerilog/UVM Practitioners: Anyone who has the basics down but feels "stuck" in traditional, slow, and noisy logging and debugging cycles.
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