Xilinx Alveo U200 FPGA Accelerator Card with Passive Cooling

• Compute
• INT8 TOPs (peak): 18.6
• Dimensions
• Height: Full
• Length: �
• Width: Dual Slot
• Memory
• Off-chip Memory Capacity: 64 GB
• Off-chip Total Bandwidth: 77 GB/s
• Internal SRAM Capacity: 35 MB
• Internal SRAM Total Bandwidth: 31 TB/s
• Interfaces
• PCI Express: Gen3x16
• Network Interfaces: 2x QSFP28 (100GbE)
• Logic Resources
• Look-up Tables (LUTs): 892000
• Power and Thermal
• Maximum Total Power: 225W
• Thermal Cooling: Passive

• Dell EMC PowerEdge R740 Rack Server
• Dell EMC PowerEdge R740xd Rack Server
• Dell EMC PowerEdge R7425 Rack Server
• Dell EMC PowerEdge R840 Rack Server
• Dell EMC PowerEdge R940xa Rack Server
• DELL PowerEdge R730 Rack Server
• HPE ProLiant DL380 G10
• SuperMicro SYS-4028GR-TR
• SuperMicro SYS-4029GP-TRT
• SuperMicro SYS-7049GP-TRT

Xilinx® Alveo™ U200 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 3X 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