NVIDIA DGX A100 2NVMe
- Condition
- New
- Manufacturer
- NVIDIA
- CPU
- 2x AMD EPYC 7742 (64c/128t, 2.25GHz-3.4GHz, 225W)
- RAM
- 2000GB (DDR4 ECC REG)
- NIC card
- 8x ConnectX-6 VPI + 1x dual-port ConnectX-6 VPI
- GPU
- 8 x NVIDIA A100
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Submit a requestNVIDIA DGX A100 is an integrated accelerated computing system designed for enterprise artificial intelligence, machine learning, analytics, and high-performance computing (HPC) workloads. Built around eight NVIDIA A100 Tensor Core GPUs, the platform provides a unified architecture for AI training, inference, and large-scale data processing in modern data centers.
Unlike a traditional GPU server assembled from individual components, NVIDIA DGX A100 combines GPU acceleration, high-speed interconnects, storage, networking, and a validated NVIDIA software stack in a single enterprise-ready platform. It can operate as a standalone AI compute node or serve as a building block for scalable DGX-based clusters.
GPU architecture for AI training and inference
NVIDIA DGX A100 is equipped with eight NVIDIA A100 Tensor Core GPUs based on the NVIDIA Ampere architecture. The system is available in 640GB and 320GB configurations, with eight GPUs in both versions. The DGX A100 640GB model provides 640GB of total GPU memory, while the DGX A100 320GB model provides 320GB of total GPU memory.
The NVIDIA A100 Tensor Core GPU is designed for a wide range of AI workloads, including deep learning training, inference, analytics, and HPC applications. Tensor Cores with support for mixed-precision computing enable acceleration of neural network operations while maintaining the accuracy required for production workloads.
The eight GPUs are connected through third-generation NVIDIA NVLink and six second-generation NVIDIA NVSwitch devices, creating a high-bandwidth GPU communication fabric. This architecture provides up to 600GB/s of GPU-to-GPU bandwidth and allows multiple accelerators to efficiently operate together as a single computing domain for demanding distributed workloads.
The system is powered by two AMD EPYC 7742 processors with 64 cores each, providing 128 CPU cores in total. The factory configuration supports up to 2TB of system memory, enabling efficient data preparation, containerized workloads, and CPU-side processing tasks required by AI pipelines.
Primary use cases
- AI model training and fine-tuning. DGX A100 accelerates development and optimization of deep learning models, including computer vision, natural language processing, recommendation systems, and enterprise AI applications.
- Large-scale inference workloads. The platform is designed for deploying production AI services, intelligent applications, automated decision systems, and real-time model execution.
- Data analytics and accelerated computing. DGX A100 supports GPU-accelerated analytics, scientific computing, simulations, and workloads that combine traditional HPC methods with machine learning.
- Multi-user AI environments. NVIDIA Multi-Instance GPU (MIG) technology allows each A100 GPU to be partitioned into up to seven isolated GPU instances with dedicated memory and compute resources, improving resource utilization for multiple teams and applications.
- Enterprise AI infrastructure. DGX A100 provides a standardized foundation for organizations building internal AI platforms, research environments, and scalable machine learning operations.
NVIDIA DGX A100 in enterprise infrastructure
NVIDIA DGX A100 is designed for organizations that require dedicated AI computing resources for continuous development, testing, and production deployment. The platform enables data science teams, AI engineers, and enterprise developers to work within a consistent hardware and software environment instead of managing separate accelerator servers and integration layers.
The system can be deployed as an individual AI node or integrated into larger NVIDIA-based environments. When planning an enterprise deployment, organizations should evaluate not only GPU performance but also network architecture, external storage requirements, workload distribution, and data center readiness.
With its integrated hardware design, NVIDIA software ecosystem, and support for scalable AI deployments, DGX A100 helps enterprises shorten the path from AI experimentation to production use. The platform provides a reliable foundation for organizations developing machine learning services, analytics platforms, and HPC applications that require predictable performance and simplified infrastructure management.
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