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2022-09-23 17:58:49
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XC7K420T-2FFG901E_AD1895AYRSRL Introduction
Whether it's a server platform or network infrastructure, it can leverage existing open source standards and frameworks to scale performance and share workloads and memory across hundreds of Alveo cards. MPI integration capabilities allow HPC developers to extend Alveo data processing from the Xilinx Vitis unified software platform.
Xilinx's recent major developments in EDA will have a real impact on FPGA design productivity.
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Both Xilinx and EDA companies have decades of data and are now leveraging AI to make the most of it. However, an important challenge in adopting machine learning in EDA companies is the lack of more specialized technical accumulation in a specific field. In the past few years, Xilinx has invested heavily in the field of machine learning, continuously acquiring AI technology and talents.
Architecturally, FPGA accelerators like Alveo cards can provide high performance at a lower cost for many compute-intensive workloads. We enable customers to build Alveo HPC clusters on existing infrastructure and networks by introducing a standards-based approach.
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