FPGA 浮点库
您可以映射到浮点库来综合浮点设计，而无需从浮点设计转换为定点设计。消除此转换步骤可减少数据精度损失，并使您能够对更宽的动态范围进行建模。
如果模型设计使用 Single 或 Double 数据类型，请使用 FPGA 浮点目标库为 Simulink® 模型生成代码。HDL Coder™ 可以将您的设计映射到原生浮点库和供应商特定的 FPGA 浮点库，例如 Altera 或 Xilinx FPGA 浮点库。同时使用原生浮点和供应商特定 IP 可以更高效地利用 FPGA 上的资源，例如硬化的 DSP 浮点加法器或乘法器基元，这样就可以在 FPGA 结构中实现更大的设计。这种混合设计对于大型复杂模型是有利的。
类
hdlcoder.FloatingPointTargetConfig | Floating-point target configuration for floating-point library |
hdlcoder.FloatingPointTargetConfig.IPConfig | IP settings for selected floating-point configuration |
主题
- Generate HDL Code for Vendor-Specific FPGA Floating-Point Target Libraries
How to set up and generate HDL code for Altera and AMD floating-point target libraries.
- Customize Floating-Point IP Configuration
Learn how to customize the latency or target frequency of the floating-point IP library.
- HDL Coder Support for FPGA Floating-Point Library Mapping
Blocks supported in Simulink for mapping to floating-point target libraries.
精选示例
FPGA Floating-Point Library IP Mapping
Use vendor-specific floating-point IP libraries, such as Altera® and Xilinx®, to generate target specific HDL code. For more information on how to map designs to floating-point libraries, see Generate HDL Code for Vendor-Specific FPGA Floating-Point Target Libraries.
Design Model by Using HDL Coder Native Floating Point and Intel Hard Floating Point
Create a model design that uses both HDL Coder™ native floating-point (NFP) and Intel® hard floating-point (HFP) IP. Using the NFP and HFP blocks together in a mixed design offers better FPGA resource utilizations. For complex models, this mixed design allows you to have bigger design into the FPGA fabric.
Generate HDL Code Using HDL Coder Native Floating Point and AMD Floating Point Library IP
Create a model design that uses both HDL Coder™ native floating-point (NFP) and AMD® floating-point IP. You can use this mixed-design approach to accommodate larger and more complex designs into the FPGA fabric. You can use this hybrid design with AMD floating-point libraries on AMD devices such as Versal, Zynq® UltraScale+™, and more.
