Deep Learning
R2026bPrototype different network architectures on supported AMD® FPGAs and SoCs
Deep Learning HDL Toolbox™ provides functions and tools to prototype and implement deep learning networks on FPGAs and SoCs. Profiling and estimation tools let you customize a deep learning network by exploring design, performance, and resource utilization tradeoffs.
SoC Blockset™ Support Package for AMD FPGA and SoC Devices provides bitstreams to prototype different networks' architectures such as object detection networks and long short-term memory networks on the various supported AMD FPGAs and SoCs. Supported devices include AMD Zynq® SoC boards such as ZC706 and Zynq UltraScale+™ MPSoC boards such as ZCU102.
Categories
- Prototype Deep Learning Networks on FPGA
Create a bitstream containing user programming and download it to AMD FPGA and SoC devices
- Time Series and Sequence Data Networks
Deploy networks trained for time series classification, regression, and forecasting tasks to target FPGA and SoC boards
- Deep Learning Processor Customization and IP Generation
Configure, build, and generate custom bitstreams and processor IP cores, estimate and benchmark custom deep learning processor performance
- Quantization
Calibrate, validate, and deploy quantized pretrained series deep learning networks
