Xilinx Alveo U250 FPGA Accelerator Card with Active Cooling

XilinxSKU: 5967857

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Sale price$10,987.85

Description

Xilinx Alveo U250 FPGA Accelerator Card with Active Cooling

The Xilinx Alveo U250 Data Center FPGA accelerator is engineered to meet the ever-evolving demands of modern data centers. With programmable acceleration that delivers dramatic performance gains over traditional CPUs for core workloads, the U250 empowers enterprises to push the boundaries of machine learning inference, video transcoding, and database search and analytics. Built to integrate seamlessly into standard server environments, the U250 delivers scalable, low-latency compute with the flexibility to adapt as workloads evolve. Its active cooling design ensures sustained performance under heavy utilization, making it ideal for dense rack deployments where consistent throughput matters most. By combining massive parallelism, programmable hardware, and a rich software ecosystem, the Alveo U250 turns complex workloads into predictable, repeatable results at scale.

  • Unmatched data-center acceleration for key workloads: The U250 leverages FPGA architecture to deliver substantial speedups across machine learning inference, real-time video transcoding, and fast, in-database analytics. Its flexible compute fabric enables you to implement custom accelerators tailored to your exact workloads, enabling faster insight and decision-making without overhauling your software stack.
  • Active cooling for sustained peak performance: Designed for dense, high-density racks, the U250’s integrated active cooling system reduces thermal throttling during long-running tasks. This means longer runtimes at higher clock rates, more consistent performance under sustained workloads, and improved reliability in demanding data-center environments.
  • Programmable, future-ready architecture: Built on Xilinx UltraScale+ technology, the U250 supports a broad ecosystem of tools and libraries, including the Xilinx Vitis development suite. This enables rapid development of custom accelerators, AI inference pipelines, and data-path optimizations, while maintaining compatibility with established AI frameworks and data processing pipelines.
  • Comprehensive software and runtime support: The Alveo U250 is complemented by a robust software stack, including the Xilinx Runtime (XRT) and Vitis AI libraries, along with ready-to-run samples. This ecosystem accelerates deployment, simplifies integration with existing software stacks, and provides debugging, profiling, and optimization capabilities to maximize performance per watt.
  • Enterprise-grade reliability and flexibility: With features tailored for data-center operations, the U250 offers robust reliability and repeatable performance. Its flexible programmability enables virtualization-friendly deployment, multi-tenant workloads, and streamlined updates to adapt to evolving business needs without hardware replacement.

Technical Details of Xilinx Alveo U250 FPGA Accelerator Card with Active Cooling

  • Form Factor: PCIe-based data center accelerator card designed for server platforms
  • FPGA Architecture: Xilinx UltraScale+ FPGA device on board, delivering programmable compute for a wide range of workloads
  • Memory: On-board high-bandwidth memory solution to accelerate data movement and processing
  • Cooling: Integrated active cooling implementation to maintain peak performance under load
  • Interfaces: PCIe interface for high-throughput communication with host systems
  • Software Support: Includes Xilinx Runtime (XRT), Vitis development environment, and associated libraries for rapid deployment and optimization

How to install Xilinx Alveo U250 FPGA Accelerator Card with Active Cooling

  • Power down the server, unplug from power, and discharge any static electricity before handling the hardware. Remove the chassis cover to access PCIe slots.
  • Identify a compatible PCIe slot (typically a PCIe x16 slot) and align the U250 card with the slot connector. Gently but firmly seat the card into the slot until the metal bracket sits flush against the chassis.
  • Secure the card with the retaining screw to ensure stability within the chassis. If your server requires power connectors for PCIe devices, connect them according to the server’s wiring diagram and security guidelines.
  • Power the system back on and install the required Xilinx software stack, including XRT (Xilinx Runtime) and the Vitis development environment. Follow the on-screen prompts or vendor documentation to complete driver and runtime installation.
  • Load your accelerator design or a sample bitstream, configure the runtime, and run validation workloads to verify the U250’s operation. Use profiling and monitoring tools to confirm performance targets and stability under expected workloads.

Frequently asked questions

  • Q: What workloads is the Xilinx Alveo U250 best suited for? A: It excels at machine learning inference, video transcoding pipelines, and search and analytics workloads that benefit from hardware-accelerated data paths and parallel processing.
  • Q: Does the card include an active cooling solution? A: Yes. The Alveo U250 features an integrated active cooling system to maintain performance under sustained heavy workloads.
  • Q: What software is required to run the U250? A: You’ll typically use the Xilinx Runtime (XRT) and the Vitis development environment, along with any framework-specific libraries or toolchains needed for your workload. These tools enable you to deploy, optimize, and manage custom accelerators on the card.
  • Q: What are the server and software requirements? A: The U250 is designed for standard data-center servers with compatible PCIe slots. It requires a supported operating system and drivers provided by Xilinx or the server vendor, plus the appropriate runtime and development tools for your workload.
  • Q: How does the U250 integrate into existing AI and analytics pipelines? A: Its programmable fabric allows you to implement custom inferencing kernels, data-path accelerators, and streaming analytics blocks that plug into your existing software stack, enabling lower latency, higher throughput, and better resource utilization.

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