900-2G171-0100-130 Nvidia 64GB GDDR6 Tesla A16 PCIe GPU

Nvidia 900-2G171-0100-130 64GB GDDR6 Tesla A16 Passive CUDA PCIe GPU Accelerator Overview

The Nvidia 900-2G171-0100-130 Tesla A16 is a high-performance GPU accelerator designed for enterprise workloads, virtualization, cloud data centers, and AI inference. With 64GB of high-bandwidth GDDR6 memory, this passive cooling GPU provides extensive capacity for demanding workloads such as video streaming, AI inferencing, virtual desktop infrastructure (VDI), and high-density GPU server deployments. Built on Nvidia’s Ampere architecture, the Tesla A16 delivers powerful CUDA performance, optimized tensor cores, and efficient passive thermal design for silent, energy-efficient operation in server racks and dense computing environments.

Ampere Architecture for Enterprise Performance

The Tesla A16 GPU is based on Nvidia’s Ampere architecture, combining CUDA cores, Tensor cores, and advanced NVLink capabilities to deliver scalable, high-throughput performance for compute-intensive enterprise workloads. Ampere architecture enhances processing efficiency, parallelism, and energy optimization, making the Tesla A16 suitable for large-scale AI inferencing, professional virtualization, and multi-tenant cloud solutions.

CUDA Cores for Parallel Compute Workloads

The Tesla A16 features thousands of CUDA cores designed for high-efficiency parallel processing. These cores accelerate floating-point and integer workloads simultaneously, enabling fast execution of machine learning models, simulations, rendering, and data analytics tasks. CUDA acceleration ensures that enterprise applications experience minimal latency and high throughput for both real-time and batch processing tasks.

Tensor Cores for AI Acceleration

Equipped with specialized Tensor cores, the Tesla A16 provides accelerated AI computation for neural networks, deep learning inference, and machine learning pipelines. Tensor cores support mixed-precision computations including FP32, FP16, BF16, and INT8, delivering higher performance per watt compared to traditional GPU designs and enabling efficient processing of large-scale AI models in virtualized and multi-tenant environments.

Multi-Precision Compute for Diverse Workloads

The Tesla A16 Tensor cores enable precision versatility, allowing workloads that require INT8 or FP16 inference to be executed efficiently, while also supporting FP32 operations for high-fidelity scientific simulations. This flexibility ensures the GPU can handle a wide variety of enterprise tasks without compromising performance or accuracy.

64GB GDDR6 Memory for High-Density Workloads

With 64GB of GDDR6 memory, the Tesla A16 provides substantial capacity for processing large datasets, multiple VDI sessions, AI model deployments, and high-resolution video streams. Its memory architecture ensures consistent performance when managing simultaneous workloads across virtualized and containerized enterprise environments.

High Bandwidth Memory Interface

The Tesla A16’s GDDR6 memory utilizes a wide memory interface, delivering high data throughput for large-scale processing and real-time applications. This bandwidth ensures rapid access to data, reducing bottlenecks for AI inferencing, video processing, and graphics-intensive virtualization tasks.

Memory for Multi-Instance GPU (MIG)

Nvidia’s Multi-Instance GPU (MIG) capability allows the Tesla A16 to be partitioned into multiple isolated GPU instances, each with dedicated memory and compute resources. This enables multiple users or applications to share a single GPU securely, providing consistent performance and scalability for cloud, VDI, and enterprise AI deployments.

Passive Cooling for Data Center Deployment

The Tesla A16 employs a passive cooling design optimized for server rack environments. By utilizing airflow from the data center or workstation chassis, the GPU maintains stable temperatures under continuous load while reducing mechanical failure risks associated with active fan systems. Passive cooling is particularly advantageous for high-density server deployments where multiple GPUs operate simultaneously.

Scalability in Multi-GPU Racks

The dual-slot passive design allows multiple Tesla A16 GPUs to be deployed in a single server or rack, enabling scalable performance for enterprise workloads. Multi-GPU configurations maximize throughput for AI, VDI, and HPC tasks, ensuring optimal resource utilization and reliability in high-density environments.

PCIe Connectivity for Enterprise Servers

The Tesla A16 uses a PCIe interface to communicate with host systems, supporting stable high-speed data transfers and ensuring efficient interaction with CPUs, memory, and storage. PCIe connectivity is essential for enterprise servers requiring low-latency, high-throughput performance for virtualized and cloud workloads.

High-Throughput Enterprise Integration

PCIe connectivity ensures seamless integration into leading server platforms from Dell, HPE, Lenovo, and Supermicro. The GPU maintains consistent performance in high-density data centers, supporting AI workloads, virtual desktops, and enterprise video processing pipelines.

Multi-GPU Deployment

The PCIe interface allows multiple Tesla A16 GPUs to be installed in a single chassis, supporting scalable parallel processing for AI, deep learning, HPC, and virtualization workloads. Multi-GPU deployments optimize resource allocation and maximize overall system performance in enterprise clusters.

Flexible Legacy

While optimized for modern PCIe servers, the Tesla A16 maintains backward compatibility with older PCIe configurations, providing enterprise flexibility and cost-effective upgrade options without the need for extensive infrastructure replacements.

Cloud-Ready Capabilities

The Tesla A16 is designed for enterprise virtualization and cloud applications. With Nvidia’s Multi-Instance GPU (MIG) and vGPU technologies, this GPU can partition resources to serve multiple virtual machines or containerized workloads simultaneously, ensuring predictable performance and secure multi-tenant operation.

Nvidia vGPU and Multi-Instance GPU (MIG)

vGPU and MIG technologies allow the Tesla A16 to run multiple isolated GPU instances, each dedicated to a virtual desktop, AI model, or containerized application. This enables high-density GPU virtualization and efficient resource allocation in enterprise and cloud data centers.

Cloud Deployment and Multi-Tenant

The Tesla A16 is ideal for cloud service providers and enterprise IT, delivering scalable GPU resources across multiple tenants or users. Its memory capacity and passive design ensure reliable performance for AI inference, video processing, and VDI workloads in shared environments.

High-Throughput Inference

With dedicated Tensor cores, the GPU delivers high throughput for AI inference workloads. This ensures that AI applications can process large volumes of data with minimal latency, supporting real-time AI-driven insights, predictions, and automation.

Neural Network Training

The Tesla A16 supports both AI training and inference, enabling enterprises to develop, test, and deploy models on a single platform. Its large memory and parallel processing architecture allow handling of high-resolution datasets and complex neural network architectures without memory limitations.

Enterprise Reliability

The Tesla A16 provides enterprise-grade reliability, availability, and serviceability (RAS) features. ECC memory, secure firmware, and continuous monitoring ensure robust operation for mission-critical workloads. These features make it suitable for high-density server environments, scientific computing, and AI-driven enterprises.

Secure Firmware and Boot Mechanisms

Advanced firmware security ensures that the GPU operates in a protected and validated environment. Secure boot and firmware validation prevent unauthorized modifications, enhancing system integrity and compliance with enterprise security policies.

Scalable Multi-GPU Deployment for High-Density Computing

The Tesla A16 supports scalable multi-GPU configurations, enabling enterprises to build high-density compute clusters for AI, VDI, HPC, and virtualization workloads. Its passive design, high memory capacity, and CUDA cores provide predictable, scalable performance for data center and cloud deployments.

Parallel Workload

Multiple Tesla A16 GPUs can be deployed together to execute parallel workloads efficiently. Each GPU can process distinct workloads or work collaboratively on large tasks, maximizing throughput for enterprise applications, simulations, and AI pipelines.

Integration with HPC and Cloud Environments

The Tesla A16 can be integrated into high-performance computing clusters and enterprise cloud environments. Its compatibility with containerized workflows, virtualization, and orchestration frameworks enables scalable, flexible deployment for AI, graphics, and compute-intensive workloads.

Resource Utilization

Scalable GPU deployments allow organizations to maximize resource utilization, allocating compute, memory, and bandwidth efficiently across multiple virtualized workloads. The Tesla A16’s architecture ensures linear performance scaling and high reliability in high-density enterprise systems.

Enterprise and Cloud Applications

The Nvidia 900-2G171-0100-130 Tesla A16 64GB GDDR6 Passive CUDA GPU Accelerator is suitable for a wide range of enterprise, AI, and cloud applications. Its combination of high memory capacity, passive thermal design, CUDA acceleration, and AI optimization makes it ideal for virtual desktops, AI inference, HPC, and professional cloud-based workloads.

High-Density Enterprise Server Deployments

With its passive cooling and dual-slot design, the Tesla A16 is suitable for dense server installations. Multiple GPUs can be deployed within a single chassis to maximize computational density while minimizing power consumption and thermal constraints, making it ideal for large-scale enterprise, cloud, and data center environments.