Xilinx Vitis-AI Release 1.0 | 902.8 mb
Xilinx, Inc., the leader in adaptive and intelligent computing, is pleased to announce the availability of Vitis AI Release 1.0 is Xilinx’s development platform for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards. Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards. It consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease of use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Vitis AI is composed of the following key components: AI Model Zoo - A comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices.
AI Optimizer - An optional model optimizer that can prune a model by up to 90%. It is separately available with commercial licenses.
AI Quantizer - A powerful quantizer that supports model quantization, calibration, and fine tuning.
AI Compiler - Compiles the quantized model to a high-efficient instruction set and data flow.
AI Profiler - Perform an in-depth analysis of the efficiency and utilization of AI inference implementation.
AI Library - Offers high-level yet optimized C++ APIs for AI applications from edge to cloud.
DPU - Efficient and scalable IP cores can be customized to meet the needs for many different applications Xilinx is the inventor of the FPGA, programmable SoCs, and now, the ACAP. Our highly-flexible programmable silicon, enabled by a suite of advanced software and tools, drives rapid innovation across a wide span of industries and technologies - from consumer to cars to the cloud. Xilinx delivers the most dynamic processing technology in the industry, enabling rapid innovation with its adaptable, intelligent computing. Product: Xilinx Vitis AI
Version: Release 1.0
Supported Architectures: x64
Website Home Page : http://www.xilinx.com
Language: english
System Requirements: Linux *
Supported Operating Systems: *
Size: 902.8 mb
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发表于 2020-5-12 16:10:02
发表于 2020-6-4 14:31:51
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