FPGA, ASIC 및 SoC 개발
MATLAB®과 Simulink®를 사용하여 FPGA, ASIC, SoC 기기에 배포할 프로토타입 및 프로덕션 애플리케이션을 개발합니다. MATLAB과 Simulink를 사용하여 다음을 수행할 수 있습니다.
높은 추상화 수준에서 디지털, 아날로그, 소프트웨어를 함께 모델링하고 시뮬레이션합니다.
자동 제시되는 안내를 통해 고정소수점으로 변환하거나 모든 타깃 기기에 대해 네이티브 부동소수점 연산을 생성합니다.
메모리, 버스, I/O를 모델링하여 하드웨어와 소프트웨어 아키텍처를 분석합니다.
디지털 로직 구현을 위해 가독성 및 추적성이 좋은 최적화된 VHDL®, Verilog® 또는 SystemVerilog를 생성합니다.
임베디드 프로세서를 타깃으로 하기 위해 프로세서에 최적화된 C/C++ 코드를 생성합니다.
MATLAB 또는 Simulink 테스트 벤치에 연결된 FPGA나 SoC 기기 또는 HDL 시뮬레이터에서 실행되는 알고리즘을 검증합니다.

FPGA, ASIC 및 SoC 개발 관련 제품
HDL Coder
Generate Verilog, SystemVerilog, and VHDL code for FPGA and ASIC designs
HDL Verifier
Find RTL bugs and generate testbenches for ASICs or FPGAs
Deep Learning HDL Toolbox
Prototype and deploy deep learning networks on FPGAs and SoCs
Wireless HDL Toolbox
Design and implement wireless communications subsystems for FPGAs, ASICs, and SoCs
Vision HDL Toolbox
Design image processing, video, and computer vision systems for FPGAs and ASICs
DSP HDL Toolbox
Design digital signal processing applications for FPGAs, ASICs, and SoCs
Fixed-Point Designer
고정소수점 및 부동소수점 알고리즘 모델링 및 최적화
SoC Blockset
Design, analyze, and deploy hardware/software applications for AMD and Intel SoC devices
도움말 항목
모델링 및 시뮬레이션
- Use Simulink Templates for HDL Code Generation (HDL Coder)
Use Simulink model templates for HDL code generation to create efficient hardware designs. - Transmit and Receive Tone Using AMD RFSoC Device - Part 1 System Design (SoC Blockset)
Design and simulate data path using SoC Blockset™ on Xilinx® RFSoC device. - Wireless Communications Design for ASICs, FPGAs, and SoCs (HDL Coder)
Design wireless communication algorithms for hardware by using Wireless HDL Toolbox™ blocks. - Implement Digital Downconverter for FPGA (DSP HDL Toolbox)
Design a digital downconverter (DDC) for LTE on FPGAs. - Introduction to Custom OFDM (Wireless HDL Toolbox)
This example shows the design and verification of a transmitter and receiver for a custom OFDM communication system that is suitable for HDL code generation. (R2024b 이후) - Convert MATLAB Vision Algorithm to Hardware-Targeted Simulink Model (Vision HDL Toolbox)
Create a hardware-targeted design in Simulink that implements the same behavior as a MATLAB reference design.
검증
- Get Started with Simulink HDL Cosimulation (HDL Verifier)
Set up an HDL Verifier™ application using the Cosimulation Wizard in the Simulink® environment. - FPGA-in-the-Loop Simulation (HDL Verifier)
FPGA-in-the-loop (FIL) simulation provides the capability to use Simulink or MATLAB software for testing designs in real hardware for any existing HDL code. - Data Capture Workflow (HDL Verifier)
Capture signal data from a design running on an FPGA. - Access FPGA Memory Using JTAG-Based AXI Manager (HDL Verifier)
Use JTAG-based AXI manager to access memories connected to an FPGA. - UVM Component Generation Overview (HDL Verifier)
Generate a Universal Verification Methodology (UVM) environment from a Simulink model. - Generate SystemVerilog DPI Component (HDL Verifier)
Generate a DPI component from Simulink, and explore various configuration parameters. - Verify Generated Code Using HDL Test Bench from Configuration Parameters (HDL Coder)
Generate a HDL test bench to simulate and verify the generated HDL code for your design.
코드 생성 및 배포
- Basic HDL Code Generation Workflow (HDL Coder)
Follow the workflow for HDL code generation and FPGA synthesis from MATLAB and Simulink algorithms. - Generate IP Core with an AXI4-Stream Interface (HDL Coder)
Use the AXI4-Stream interface to enable high speed data transfer between the processor and FPGA on Zynq® hardware. - Custom IP Core Generation (HDL Coder)
Generate a custom IP core from a model or algorithm using the HDL Workflow Advisor. - Targeting FPGA & SoC Hardware Overview (HDL Coder)
High-level steps for targeting an FPGA or SoC platform. - Transmit and Receive Tone Using AMD RFSoC Device - Part 2 Deployment (SoC Blockset)
Implement and verify design using SoC Blockset on Xilinx RFSoC device. - Prototype Deep Learning Networks on FPGA and SoC Devices (Deep Learning HDL Toolbox)
Accelerate the prototyping, deployment, design verification, and iteration of your custom deep learning network running on a fixed bitstream by using thedlhdl.Workflowobject.




