Executive Summary
The semiconductor industry is undergoing a transformation driven by increasing design complexity, tighter performance requirements, and the need for faster time to market. To meet these demands, engineering teams must unify traditionally siloed workflows across analog, digital, and verification domains. MATLAB® and Simulink® enable this unification through a Model-Based Design approach that spans the entire semiconductor lifecycle—from early algorithm development and architectural modeling to power-performance-area (PPA)–aware RTL generation, UVM verification, signal integrity analysis, and integration with industry-standard electronic design automation tools.
This white paper explores how MATLAB and Simulink tools facilitate end-to-end semiconductor design and verification workflows, aiding teams in accelerating innovation, reducing risk, and delivering highperformance systems. MATLAB and Simulink help engineering teams shift verification left, streamline collaboration, and optimize outcomes by enabling early verification and architectural exploration, supporting PPA-aware RTL generation, and integrating with EDA workflows from Cadence®, Synopsys®, and Siemens EDA®.
Traditional semiconductor workflows are fragmented. Analog and digital teams typically operate in isolation, using disconnected tools and processes. This fragmentation often leads to inefficiencies, latestage design issues, and missed performance targets. MATLAB and Simulink can help address these challenges by providing a unified modeling and simulation environment that connects all phases of the design process thanks to the integration with EDA tools.
This integration is more than a convenience—it’s a strategic enabler. By reusing existing MATLAB and Simulink models as golden references, as stimuli generators, or for generating synthesizable PPAaware RTL and IBIS-AMI models, teams can bridge the gap between architectural modeling and hardware implementation. This not only enhances productivity but also ensures consistency and collaboration across design and verification stages. The following sections illustrate this by describing three examples of critical workflows in semiconductor design and verification:
Each of these workflows contributes to a cohesive, end-to-end semiconductor design strategy, while also reflecting a broader industry trend toward model-based design and early verification.
High-speed mixed-signal systems, such as 200+ Gb/s SerDes, present unique challenges due to their integration of analog and digital components. These systems require components like data converters, clock synthesizers, and voltage references to be robust against process variations, temperature drifts, and supply voltage fluctuations.
Traditional workflows often delay validation until late in the design cycle, increasing the risk of costly redesigns. Early behavioral modeling addresses this by enabling simulation and validation of system components before final implementation. Engineers can use architectural models to generate behavioral models that can be simulated within EDA simulators, allowing parallel development of subsystems.
For example, in a SerDes system, an analog-to-digital converter (ADC) behavioral model can be used to design a calibration scheme without waiting for the finalized ADC design. This parallelism accelerates development and fosters iterative improvements.
By incorporating early behavioral models, engineers reduce design risk, increase flexibility, and enhance overall system performance. This approach is essential for managing the complexity of modern mixed-signal systems and staying ahead in a competitive landscape.
Figure 1. System model with a correction loop
Modern semiconductor systems, especially those used in automotive radar applications, must perform reliably under diverse and dynamic environmental conditions. Traditional verification approaches often rely on abstract test patterns that fail to capture the complexity of real-world scenarios. This disconnect can lead to late-stage issues and misalignment with customer expectations.
MATLAB and Simulink allow engineers to model IC architectures and evaluate their behavior within realistic environments, in what’s called environment-in-the-loop verification. For instance, radar IC architectures can be modeled and evaluated against realistic driving scenarios based on industry standards such as Euro NCAP®. These driving scenarios simulate on-road conditions, enabling early validation of system-level metrics such as signal-to-noise ratio (SNR) and total harmonic distortion (THD).
This methodology shifts verification left by focusing on datasheet-level performance metrics rather than low-level implementation details. Engineers can use high-level models to generate realistic test environments and use them to verify their architectural IC models, ensuring that verification criteria align with end-user requirements. This approach also supports iterative refinement, allowing engineering teams to adapt quickly to design changes without redesigning the testbench.
Figure 2. Simulated driving radar scenario
By integrating realistic scenarios into architectural verification, teams can improve coverage, reduce risk, and ensure that semiconductor systems meet performance expectations in real-world conditions.
Translating high-level algorithms into efficient, synthesizable RTL is a critical step in digital design. Engineers must meet stringent PPA constraints while ensuring functional correctness.
Using HDL Coder™, engineers can automatically convert MATLAB code and Simulink models into RTL (in the Verilog, SystemVerilog, or VHDL language) or into synthesizable SystemC, which is compatible with high-level synthesis tools such as Cadence Stratus (Figure 3).
Figure 3. PPA analysis workflow
For example, an encryption algorithm developed in MATLAB can be converted to SystemC and synthesized into RTL using Cadence Stratus. The tool provides detailed PPA reports, including sequential and combinational area, register usage, clock frequency, latency, and power consumption.
This rapid feedback loop allows engineers to evaluate design tradeoffs and optimize implementations early in the development cycle (Figure 3). The workflow includes functional verification using generated testbenches and interface wrappers, ensuring correctness before hardware deployment.
By integrating algorithm design, code generation, and PPA analysis, MATLAB can enable engineers to deliver high-performance, power-efficient hardware solutions. This approach bridges the gap between software modeling and hardware realization, accelerating innovation and reducing time to market.
MATLAB and Simulink provide a comprehensive platform that unifies semiconductor design and verification workflows across analog and digital domains. By enabling early modeling of system architectures, realistic verification environments, RTL generation, and integration with EDA workflows, engineering teams can accelerate development, reduce risk, and deliver high-performance systems.
As the semiconductor industry continues to evolve, adopting an end-to-end Model-Based Design approach is becoming increasingly critical for organizations seeking to remain competitive and responsive to market demands. By enabling early architectural exploration, the reuse of existing models, and realistic scenario-based verification, these tools help engineering teams streamline development cycles, improve collaboration, and ensure that semiconductor systems meet performance expectations in real-world conditions.
