Xilinx ALVEO U55C DATA CENTER ADAPTER A-U55C-P00G-PQ-G

Description

Xilinx AMD Alveo U55C High Performance Compute Card – 4.4″ Height x 6.6″ Length [, , , , , , , , , , , , , , , , , , , , , ]

The AMD Alveo™ U55C high performance compute cardprovides optimized acceleration for workloads in high performance computing (HPC), big data analytics and search, financial computing, computational storage and machine learning.

Featuring powerfulVirtex™ XCU55 UltraScale+ FPGA from AMD, the Alveo U55C card packs in high bandwidth memory (HBM2) and 200Gbps of high-speed networking into a single slot, small form factor card, and is designed for deployment in any server.

The U55C accelerator is paired with the new standards-based API-driven clustering solution from AMD and equipped with C/C++ programmability. This solution empowers a broad spectrum of customers with large-scale compute workloads to realize the performance advantages of FPGAs at 1000+ node scale, easily implementing HPC clustering using their existing data center infrastructure and network, with no proprietary hardware required.

The U55C card supports PCI Express® (PCIe®) Gen3x16 or dual Gen4x8, contains 16 GB of High-Bandwidth Memory (HBM2) at 460GB/s of bandwidth, and Ethernet networking capability with dual QSFP28 connectors capable of 2 x 100 Gb/s.

Enabling Alveo accelerator cards is an ecosystem of AMD and partner applications for common data center workloads. For custom solutions, the Application Developer Tool Suite (Vitis™ environment) and Machine Learning Suite from AMD provide the frameworks for developers to bring differentiated applications to market.

Key Features & Benefits

Built for Performance & Efficiency

• Faster application performance with 16GB HBM memory and PCIe Gen4 interconnect
• Low latency network capability through 2x100G networking with support for 8x 25GbE, or 2x 100GbE

Adaptable – Accelerate Any Workload

• Accelerates compute, network, storage workloads
• Perfect for HPC workloads: Computer Aided Engineering (CAE), Big Data Analytics, Finite Engineering Method (FEM), Signal Processing
• Ideal for Scale Up and Scale Out system architectures

Accessible – Cloud <-> On-Premises Mobility

• Built for scale out architectures for deployment solutions on the cloud or on-premises interchangeably
• Network Attached
• Ready for Scale COTS
• Ready to deploy in Standard DCs
• Using existing DC infrastructure