XC7K480T-L2FF1156E_AD1981B-JSTZ Introduction

Software developers and data scientists can leverage the Vitis platform's advanced programming capabilities for applications and clusters to realize the benefits of Alveo and self-tuning computing. Xilinx has invested heavily in the Vitis development platform and tools to make self-tuning computing more accessible to software developers and data scientists without hardware expertise.

MPI integration capabilities allow HPC developers to extend Alveo data processing from the Xilinx Vitis unified software platform. 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.

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Machine learning is about finding patterns in big data. Machine learning is clearly better than humans when dealing with petabytes of data. As we all know, problems such as Go, autonomous driving, RNA translation and transformation, and protein folding can now be solved by machine learning.

We enable customers to build Alveo HPC clusters on existing infrastructure and networks by introducing a standards-based approach. Architecturally, FPGA accelerators like Alveo cards provide the highest performance at the lowest cost for many compute-intensive workloads.

relevant information