MATLAB® and Simulink® facilitate the design space exploration and top-down design of semiconductor devices, letting engineers collaborate to describe, analyze, simulate, and verify their multidomain systems using a combination of modeling approaches and levels of abstraction. Domain examples are analog, digital, RF, software, and thermal; and abstraction can vary from transistor level up to algorithm level.
System models, verification environments, and test cases defined in MATLAB and Simulink can be reused in EDA tools in several ways, including co-simulation, export of models, test benches, and test vectors, and through C and HDL code generation. These pathways integrate system design, verification, and implementation workflows and enable engineers to significantly shorten the design iterations, reduce the risk of delays in the project schedule, and enable the continuous integration of specification and design changes.
"Using MathWorks tools, we identified the best algorithm choice. Because the model ran much faster than our circuit simulator, we caught implementation errors much quicker and shortened our time to market."Cory Voisine, Allegro MicroSystems
Using MATLAB and Simulink for Semiconductor Development
Model and simulate digital systems using wireless, vision, and signal processing algorithms, along with extensive math and trigonometry functions and complex state control logic. Build your models using the level of abstraction that allows the right tradeoff between accuracy and simulation speed. This rapid design space exploration helps you make the right choices on system architecture and quantizations. Existing Verilog®, VHDL®, and C/C++ models can be imported, enabling continuous integration.
Perform System-on-Chip (SoC) hardware/software co-design and simulation with MATLAB and Simulink, which consider SoC architecture as well as task execution and OS effects. This action permits a high-fidelity analysis of software performance and hardware utilization very early in the product development process.
Analog and Mixed-Signal Design
Combine and simulate analog, digital, software, and RF components with MATLAB and Simulink, speeding up the evaluation of numerous design alternatives and optimizing system performance.
Design and analyze analog mixed signal components, such as ADC, PLL, Power Converters, and SerDes, starting from MathWorks® reference models and libraries. Explore architectural tradeoffs at the system-level, evaluate the effects of physical impairments (such as phase noise, jitter, nonlinearity, leakage, and timing errors), and verify the circuit behavior in different conditions and scenarios.
Reuse MATLAB and Simulink models and test benches in IC and PCB design environments such as Cadence® Virtuoso® AMS Designer and Cadence® PSpice®. Speed up the implementation process and bridge the gap between systems engineering and ASIC design.
RF IC and System Design
Design, analyze, and simulate RF systems using measurement data such as S-parameters, data sheet specifications, or physical properties. Build models of RFIC transceivers and integrate them with digital signal processing algorithms and control logic to accurately simulate adaptive architectures such as automatic gain control (AGC), digital predistortion (DPD), and tunable matching networks. Integrate the RF front-end with antenna arrays to model beamforming architectures taking into account near and far field coupling.
With MATLAB and Simulink, you can model RF systems at different levels of abstraction. Circuit envelope simulation enables high-fidelity multi-carrier simulation of networks with arbitrary topologies. Harmonic balance analysis computes the effects of non-linearity on gain and on second-order and third-order intercept points (IP2 and IP3). The Equivalent Baseband library enables fast, discrete-time simulation to validate the performance of a single-carrier cascaded RF system.
MATLAB also provides LTE, 5G, WLAN, and Bluetooth standard-compliant functions, apps, and reference examples for modeling, simulating, and verifying various communications systems. You can configure, simulate, measure, and analyze end-to-end communications links. You can also create and reuse a conformance test bench to verify that your designs, prototypes, and implementations complying with RF standards.
Battery Management System
Battery Management System (BMS) is responsible for safe operation, performance, and battery life under diverse charge-discharge and environmental conditions. Simulink modeling and simulation capabilities enable BMS development, including single-cell-equivalent circuit formulation and parameterization, electronic circuit design, control logic, automatic code generation, and verification and validation.
In addition, C code or HDL can be generated from Simulink models for rapid prototyping of systems or microcontrollers. This enables you to perform real-time simulation for hardware-in-the-loop (HIL) testing to validate the algorithm before hardware implementation.
Verify MATLAB and Simulink models in a structured way, defining verification environments, test cases, and formal properties. Regression tools and formal engines are provided, enabling you to find bugs early in the design flow. In order to quantify the verification results, coverage measurement and requirement traceability tools are supplied.
Export system models, verification environments, and test cases from MATLAB or Simulink as SystemVerilog DPI-C or UVM components and reuse them as drivers, checkers, or reference using HDL simulators such as Cadence® Xcelium, Siemens® Questa, or Synopsys® VCS. You can also use HDL cosimulation to compare MATLAB and Simulink models with their Verilog or VHDL representations.
Focus on optimizing the hardware architecture of your algorithms rather than coding: progressively refine and verify models of digital systems and convert them into RTL code. Once you have verified the functionality of your algorithm’s hardware architecture, automatic code generation ensures your intent is correctly implemented. Compared to hand coding, this workflow not only permits a faster exploration of different architectural options, but it also makes the overall process more agile to quickly adapt to changes.
Yield is the most important factor in overall semiconductor operations. With MATLAB and Simulink, you can develop, integrate, and deploy systems that use technologies like deep learning, predictive maintenance, and image processing. These systems enable increased production yield by enhancing semiconductor process control; minimizing maintenance overhead by deploying a photolithography system with fault detection; and improving equipment reliability by estimating the remaining useful life of a machine.
Use MATLAB to conduct bench testing for semiconductors. MATLAB enables you to communicate with test equipment directly through instrument drivers or text-based commands. The waveform generated in MATLAB can be transmitted to an instrument as a stimulus to the Design Under Test (DUT). Alternatively, the measurement data from the DUT can be captured by the instrument and sent to MATLAB for post-processing, analysis, and visualization. You can also automate tests, verify hardware designs, and build test systems based on LXI, PXI, and AXIe standards.