Nvidia A30 Tensor Core GPU Accelerator for Compute GPU, AI Interface and Enterprise Servers

NVIDIA A30 Tensor Core GPU stands out as the most versatile mainstream compute GPU, ideal for AI inference and enterprise workloads.  Leveraging the NVIDIA Ampere architecture Tensor Core technology, it supports various mathematical precisions, providing a single accelerator to boost performance across various tasks. Designed for large-scale AI inference, the A30 facilitates rapid AI model retraining with TF32 and accelerates high-performance computing (HPC) applications using FP64 Tensor Cores. This PCIe card is optimized for mainstream servers, featuring Multi-Instance GPU (MIG) and FP64 Tensor Cores, along with a high-speed 933 GB/s memory bandwidth within a low 165W power envelope.

Combination of third-generation Tensor Cores and MIG ensures secure quality of service across diverse workloads, creating a versatile GPU that enables an elastic data center. The A30’s comprehensive computing capabilities cater to large and small workloads, providing maximum value for mainstream enterprises. It is part of NVIDIA's complete data center solution, which integrates hardware, networking, software, libraries, and optimized AI models and applications from NGC. Representing the most powerful end-to-end AI and HPC platform for data centers allows researchers to achieve real-world results and deploy solutions at scale.

SYSTEM SPECIFICATION

NVIDIA Ampere Architecture

Whether using MIG to partition an A30 GPU into smaller instances or NVIDIA NVLink to connect multiple GPUs for larger workloads, the A30 easily handles various acceleration needs. Its versatility allows IT managers to maximize GPU utility in their data centers continuously.

Third-Generation Tensor Cores

NVIDIA A30 delivers 165 teraFLOPS (TFLOPS) of TF32 deep learning performance, 20 times the AI training throughput and over five times the inference performance of the NVIDIA T4 Tensor Core GPU. The A30 offers 10.3 TFLOPS of performance for HPC, nearly 30 percent more than the NVIDIA V100 Tensor Core GPU.

Next-Generation NVLink

NVIDIA NVLink in the A30 provides twice the throughput of the previous generation. Connecting two A30 PCIe GPUs via an NVLink Bridge yields 330 TFLOPs of deep learning performance.

Multi-Instance GPU (MIG)

A30 GPU divided into up to four fully isolated instances, each with its high-bandwidth memory, cache, and compute cores. MIG allows developers to access breakthrough acceleration for their applications. Simultaneously, IT administrators allocate appropriately sized GPU acceleration for each task, optimizing utilization and broadening access for all users and applications.

HBM2

Equipped with up to 24GB of high-bandwidth memory (HBM2), the A30 delivers 933GB/s of GPU memory bandwidth, making it ideal for diverse AI and HPC workloads in mainstream servers.

Structural Sparsity

AI networks often contain millions to billions of parameters, many of which are unnecessary for accurate predictions and can be zeroed out, making the models "sparse" without compromising accuracy. The A30's Tensor Cores can offer up to 2X higher performance for sparse models, benefiting AI inference and improving model training performance.

End-to-End Solution for Enterprises

NVIDIA A30 Tensor Core GPU, powered by the NVIDIA Ampere architecture, is central to the modern data center. It is integral to NVIDIA’s data center platform, designed for deep learning, HPC, and data analytics, accelerating over 2,000 applications, including all major deep learning frameworks. NVIDIA AI Enterprise, a cloud-native suite of AI and data analytics software, is certified to run on the A30 within VMware vSphere-based virtual infrastructures. This allows for managing and scaling AI workloads in a hybrid cloud environment. The complete NVIDIA platform is available from data center to edge, delivering significant performance gains and cost-saving opportunities.

Order Information

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