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Xilinx® Alveo™ U250 Data Center Accelerator Card - Active - Part ID: A-U250-A64G-PQ-G

SKU: A-U250-A64G-PQ-G
Manufacturer: Xilinx
Dual-Port 100GbE PCIe 3.0 x16 QSFP28 More details...
Price: $9,235.00
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Xilinx® Alveo™ U250 Data Center Accelerator Card - Active - Part ID: A-U250-A64G-PQ-G
Xilinx® Alveo™ U250 Data Center Accelerator Card - Active - Part ID: A-U250-A64G-PQ-G
 
Product Details
Alveo U250 Data Center Accelerator Card

  • 33.3 Peak INT8 TOPs
  • 77GB/s DDR Memory Bandwidth
  • 38TB/s Internal SRAM Bandwidth
  • 1,341,000 LUTs

Xilinx® Alveo™ U250 Data Center accelerator cards are designed to meet the constantly changing needs of the modern Data Center, providing up to 90X higher performance than CPUs for key workloads, including machine learning inference, video transcoding, and database search & analytics. Built on the Xilinx 16nm UltraScale™ architecture, Alveo accelerator cards are adaptable to changing acceleration requirements and algorithm standards, capable of accelerating any workload without changing hardware, and reducing overall cost of ownership.

Enabling Alveo accelerator cards is an ecosystem of Xilinx and partner applications for common Data Center workloads. For custom solutions, Xilinx’s Application Developer Tool Suite (SDAccel™) and Machine Learning Suite provide the tools for developers to bring differentiated applications to market.


Key Features & Benefits

Fast - Highest Performance
  • Up to 90X higher performance than CPUs on key workloads at 1/3 the cost
  • Over 4X higher inference throughput and 3X latency advantage over GPU-based solutions
Adaptable – Accelerate Any Workload
  • Machine learning inference to video processing to any workload using the same accelerator card
  • As workload algorithms evolve, use reconfigurable hardware to adapt faster than fixed-function accelerator card product cycles
Accessible - Cloud <-> On-Premises Mobility
  • Deploy solutions on the cloud or on-premises interchangeably, scalable to application requirements
  • Applications available for common workloads, or build your own with the application developer tool


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