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Cisco UCSC-GPU-A16 | NVIDIA A16 Graphics Card, 64GB GDDR6, 250W Passive

SKU:UCSC-GPU-A16

Stock Status: Enquire

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Description

The Cisco UCSC-GPU-A16 is an enterprise GPU accelerator featuring four NVIDIA Ampere-architecture processors with 64GB total GDDR6 memory. Purpose-built for high-density virtual desktop infrastructure (VDI), it delivers exceptional graphics performance for remote workstations and virtual desktops. The passive-cooled, 250W design integrates seamlessly into Cisco UCS rack servers for virtualized environments requiring advanced graphics capabilities.

Features

NVIDIA Ampere Architecture with 2nd-generation RT cores and 3rd-generation Tensor cores
- Quad-GPU board design enabling independent vGPU profile allocation per GPU
- ECC memory protection across all 64GB GDDR6 for enterprise reliability
- Passive cooling design for integration into server airflow architectures
- Support for up to 64 concurrent virtual desktop sessions (configuration dependent)
- Hardware-accelerated AV1 decode for efficient video streaming
- DirectX 12 Ultimate, OpenGL 4.6, and Vulkan API support
- NVIDIA GRID technology for virtual GPU sharing and management
- Secure Boot, Secure Firmware Update, and Firmware Rollback Protection
- PCIe lane reversal support for flexible server deployment
- Mixed precision computing with FP32, FP16, and INT8 operations
- Real-time ray tracing acceleration for visual applications

Warranty

All products sold by XS Network Tech include a 12-month warranty on both new and used items. Our in-house technical team thoroughly tests used hardware prior to sale to ensure enterprise-grade reliability.

All technical data should be verified on the manufacturer data sheets.

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Technical Specifications

FAQs

Technical Specifications

GPU: NVIDIA A16 with Ampere architecture, quad-GPU design (4 GPUs on single board)
- Memory: 64GB total (4x 16GB GDDR6 with ECC), 800 GB/s aggregate memory bandwidth
- Interface: PCIe Gen4 x16 (backward compatible with Gen3 x16)
- Power: 250W TDP, passive cooling, requires CPU 8-pin auxiliary power connector
- Shading Units: 5,120 total CUDA cores (1,280 per GPU), 160 Tensor cores, 40 RT cores
- Boost Clock: Up to 1.7 GHz per GPU
- vGPU Support: NVIDIA Virtual PC (vPC), NVIDIA RTX Virtual Workstation (vWS), NVIDIA vApps
- Form Factor: Full-height, half-length (FHHL), dual-slot width
- Encode/Decode: AV1 decode, H.264, H.265 hardware encoding
- Management: Compatible with Cisco UCS C-Series and X-Series servers

FAQs

Q: What is the primary use case for the UCSC-GPU-A16?
A: This GPU is designed specifically for high-density virtual desktop infrastructure (VDI) deployments. It enables organizations to deliver graphics-rich virtual desktops and entry-level virtual workstations to remote users, supporting knowledge worker applications and CAD workloads with up to double the user density of previous generations.

Q: Which Cisco servers are compatible with this GPU?
A: The UCSC-GPU-A16 is compatible with Cisco UCS C-Series rack servers (such as C240 M8) and UCS X-Series modular systems (such as X440p PCIe Node). It requires a PCIe Gen4 x16 slot, appropriate riser configuration, and additional power cabling (UCS-P100CBL-240-D for C240 deployments).

Q: How many virtual desktops can one A16 GPU support?
A: The quad-GPU architecture allows flexible provisioning with mixed user profiles. Each of the four GPUs can be allocated independently, enabling different vGPU profile sizes on the same card. This unique design optimizes user density for VDI environments, supporting dozens of concurrent knowledge worker sessions or multiple virtual workstation users depending on workload requirements.

Q: What NVIDIA vGPU software is required?
A: The A16 requires NVIDIA vGPU software licensing: NVIDIA Virtual PC (vPC) for virtual desktops or NVIDIA RTX Virtual Workstation (vWS) for virtual workstations. Licensing is per-GPU basis. The hardware supports NVIDIA vGPU 13.0 and later versions.

Q: Does this GPU support compute workloads or just graphics?
A: While optimized for VDI graphics, the A16's NVIDIA Ampere architecture includes Tensor cores and RT cores, enabling AI inference, machine learning acceleration, and ray tracing capabilities. The CUDA cores can be leveraged for compute tasks when VDI resources are underutilized, providing deployment flexibility.

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