Xilinx Alveo Accelerator Cards | BeiLuo Distributor

About Alveo Accelerator Cards

Alveo data center accelerator cards deliver significant performance improvements for database, AI, and video processing workloads in cloud and on-premises deployments.

As an authorized distributor of Xilinx, BeiLuo provides a comprehensive range of Alveo Accelerator Cards products. These products are widely used in industrial control, automotive electronics, consumer electronics, and communication equipment. We offer a complete product line with multiple series to meet various application requirements. All products are genuine and original, backed by professional technical support and comprehensive after-sales service.

Selection Guide: How to Choose the Right Alveo Accelerator Cards

Product List

2 products available

Part Number ↕	FPGA ↕	HBM2 Memory ↕	Network ↕	PCIe Interface ↕	Form Factor ↕	Package ↕	Stock Status	Action
Alveo U55C	XCU55N UltraScale+	16 GB (460 GB/s)	Dual QSFP28 (200G total)	Gen4 x8	Half-height, half-length	-	In Stock	View Details
Alveo U50	XCU50 UltraScale+	8 GB (316 GB/s)	Dual QSFP28 (200G total)	Gen4 x8	Low-profile (half-height, half-length)	-	In Stock	View Details

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Frequently Asked Questions

What workloads benefit most from Alveo acceleration?

Best Alveo workloads: 1) Database analytics - 10-50x faster queries with FPGA preprocessing, 2) AI inference - low-latency inference for real-time applications, 3) Video transcoding - up to 20x faster than CPU encoding, 4) Financial computing - sub-microsecond latency for trading, 5) Genomics - accelerated DNA sequence alignment. Workloads with parallel processing and dataflow patterns show best results.

Use Alveo for parallelizable workloads with high data throughput. Contact FAE for workload assessment.

How do I deploy Alveo cards in my data center?

Alveo deployment options: 1) On-premises - install in standard PCIe servers, 2) Cloud - AWS F1, Azure NP, Alibaba Cloud f3, 3) Containers - Docker support with Xilinx runtime, 4) Kubernetes - device plugin for orchestration, 5) VM - pass-through or SR-IOV for virtualization. Requires XRT (Xilinx Runtime) installation. Cards are hot-swappable in supported servers.

Start with cloud instances for evaluation. Deploy on-premises for production workloads.

What is the programming model for Alveo?

Alveo programming uses Vitis: 1) Kernels - develop acceleration kernels in C/C++ or RTL, 2) Host code - standard C/C++ using XRT APIs, 3) XCLBIN - compile kernels to FPGA bitstream, 4) XRT - runtime for card management and execution, 5) Libraries - Vitis Libraries for common functions. Programming model is similar to GPU but with FPGA flexibility.

Use Vitis for application development. Start with Vitis Libraries for common workloads.

How does Alveo compare to GPU acceleration?

Alveo vs GPU comparison: 1) Latency - Alveo provides deterministic low latency, 2) Power - Alveo typically 30-50% lower power, 3) Flexibility - FPGA can be customized per workload, 4) Ecosystem - GPU has larger software ecosystem, 5) Development - FPGA requires hardware expertise. Alveo excels at latency-sensitive and custom dataflow applications. GPUs better for training and standard AI models.

Use Alveo for latency-sensitive and custom workloads. Use GPU for training and standard inference.

What support is available for Alveo deployment?

Alveo support resources: 1) Vitis Libraries - optimized for common workloads, 2) Application examples - reference designs for popular use cases, 3) Developer forums - community support from Xilinx, 4) Professional services - consulting for custom solutions, 5) Training - online courses and workshops. As an authorized distributor, we provide additional technical support for deployment and optimization.

Start with Vitis Libraries and examples. Contact FAE for custom workload optimization.