Transcription of Vitis AI User Guide
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Vitis AI User Guide UG1414 ( ) July 22, 2021. Revision History Revision History The following table shows the revision history for this document. Section Revision Summary 07/22/2021 Version Chapter 1: Vitis AI Overview Added Versal AI Core Series: DPUCVDX8G section TensorFlow Version (vai_q_tensorflow2) Added vai_q_tensorflow2 Quantization Aware Training, Quantizing with Custom Layers, and vai_q_tensorflow2. Usage sections PyTorch Version (vai_q_pytorch) Updated vai_q_pytorch QAT. Chapter 5: Deploying and Running the Model Updated Apache TVM, Microsoft ONNX Runtime, and TensorFlow Lite Chapter 6: Profiling the Model Added Text Summary Updated VAI Trace Usage 02/03/2021 Version Entire document Updated links 12/17/2020 Version Entire document Minor changes Deep-Learning Processor Unit Added new topics: Alveo U200/U250 Card: DPUCADF8H, Alveo U50/U50LV/U280 Card: DPUCAHX8L, and V
• Customizes efficient and scalable IP cores to meet your needs for many different applications from a throughput, latency, and power perspective. V i t i s A I T o o l s O v e r v i e w. D e e p - L e a r n i n g P r o c e s s o r U n i t. The deep-learning processor unit (DPU) is a programmable engine optimized for deep neural networks.
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