Placa gráfica NVIDIA A10 GPU Processador 24 GB GDDR6

The NVIDIA A10 GPU Processor 24 GB GDDR6 Graphics Card is a server-class accelerator designed to deliver compute performance for machine learning, inference, and data analytics workloads. Equipped with 24 GB of GDDR6 memory and a PCIe 4.0 x16 interface, this passive-cooled card provides silent operation suitable for noise-sensitive environments and dense server deployments. The card supports typical GPU-accelerated frameworks and libraries used in AI model training and inference.

Advantages

The A10 offers a high memory capacity of 24 GB GDDR6, enabling larger models and bigger datasets to be processed without frequent memory transfers. The PCIe 4.0 x16 interface provides increased throughput for data exchanges between the host and the GPU. Passive (fanless) cooling reduces acoustic output and simplifies integration into systems where active cooling is handled at the chassis or rack level. Compatibility with common GPU compute ecosystems ensures straightforward deployment in existing AI and analytics pipelines.

Suitable for

• Training and inference of machine learning and deep learning models
• Data analysis and high-throughput analytics
• Multi-GPU server configurations and virtualization platforms
• Noise-sensitive server rooms and compact chassis with external cooling

Key specifications

• Graphics memory: 24 GB GDDR6
• Interface: PCIe 4.0 x16
• Cooling type: Passive (fanless)
• Intended use: AI acceleration, data analytics, compute workloads
• Form factor: Full-height, standard server card dimensions

How to use

Install the NVIDIA A10 into a compatible PCIe 4.0 x16 slot on a server or workstation motherboard. Ensure the host system provides appropriate power and chassis airflow since the card relies on external cooling rather than on-board fans. Install manufacturer-provided or vendor-recommended drivers and CUDA/cuDNN libraries as required by your software stack. Configure your AI frameworks or analytics applications to recognize and utilize the GPU accelerator for training, inference, or data-processing tasks.

Recommendations

For reliable operation, deploy the card in systems with controlled airflow and adequate rack cooling. Use updated drivers and validated software stacks for optimal performance and stability. For multi-GPU configurations, follow motherboard and chassis vendor guidelines to ensure sufficient PCIe lanes, power delivery, and thermal management.