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Avi Patel

02 / Cadence Design Systems · Internship

Digital implementation

Following a design from logic into physical constraints.

Synthesis, physical design, timing analysis, and flow automation across two digital designs during my Cadence internship.

Context
Cadence Design Systems · Internship
When
May–August 2025
Stage
Professional experience
Tools & methods
Genus · Innovus · Tempus · Static timing analysis · Tcl · Python · Bash

Conceptual system sequence

  1. 01Constrain
  2. 02Implement
  3. 03Investigate
  4. 04Compare

A visual explanation of the workflow.

01 / Context

The problem

RTL describes a design's behavior. A realizable implementation must also account for clocking, placement, interconnect, power, area, and timing constraints. A change at one stage can shift the problem at another.

02 / Ownership

My contribution

I worked through synthesis, floorplanning, placement, clocking, routing, and signoff-oriented checks. I investigated timing and physical-design behavior using constraints, reports, and physical context, and scripted recurring implementation and analysis tasks.

03 / Architecture

How it works

  1. 01

    Constrain

    Connect the logical design to its clocks, timing intent, and implementation constraints.

  2. 02

    Implement

    Use Genus and Innovus through synthesis and the physical-design flow.

  3. 03

    Investigate

    Use Tempus reports and physical context to trace timing behavior across the flow.

  4. 04

    Compare

    Automate repeatable setup and analysis so implementation choices can be assessed consistently.

04 / Validation

Evidence & scope

  • Hands-on internship experience spanning two digital designs.
  • Report-driven timing and physical-design investigation.
  • Reusable automation for recurring flow and analysis tasks.

Project scope

Generalized internship overview with an original educational illustration of the implementation flow.

05 / Perspective

Engineering takeaway

Timing is a system-level interaction between logic, clocks, placement, and routing. A useful debugging approach follows the evidence across those boundaries and changes assumptions deliberately.