AI Training—Up to 3X higher throughput than v100 and 6X higher than T4

BERT Large Pre-Training (Normalized)

Training AI models for next-level challenges such as conversational AI requires massive compute power and scalability.

NVIDIA A30 Tensor Cores with Tensor Float (TF32) provide up to 10X higher performance over the NVIDIA T4 with zero code changes and an additional 2X boost with automatic mixed precision and FP16, delivering a combined 20X throughput increase. When combined with NVIDIA® NVLink®, PCIe Gen4, NVIDIA networking, and the NVIDIA Magnum IO™ SDK, it’s possible to scale to thousands of GPUs.

Tensor Cores and MIG enable A30 to be used for workloads dynamically throughout the day. It can be used for production inference at peak demand, and part of the GPU can be repurposed to rapidly re-train those very same models during off-peak hours.

NVIDIA set multiple performance records in MLPerf, the industry-wide benchmark for AI training.

AI Inference—Up To 3X higher throughput than V100 at real-time conversational AI

BERT Large Inference (Normalized)
Throughput for <10ms Latency

AI Inference—Over 3X higher throughput than T4 at real-time image classification

RN50 v1.5 Inference (Normalized)
Throughput for <7ms Latency

HPC—Up to 1.1X higher throughput than V100 and 8X higher than T4

LAMMPS (Normalized)

To unlock next-generation discoveries, scientists use simulations to better understand the world around us.

NVIDIA A30 features FP64 NVIDIA Ampere architecture Tensor Cores that deliver the biggest leap in HPC performance since the introduction of GPUs. Combined with 24 gigabytes (GB) of GPU memory with a bandwidth of 933 gigabytes per second (GB/s), researchers can rapidly solve double-precision calculations. HPC applications can also leverage TF32 to achieve higher throughput for single-precision, dense matrix-multiply operations.

The combination of FP64 Tensor Cores and MIG empowers research institutions to securely partition the GPU to allow multiple researchers access to compute resources with guaranteed QoS and maximum GPU utilization. Enterprises deploying AI can use A30’s inference capabilities during peak demand periods and then repurpose the same compute servers for HPC and AI training workloads during off-peak periods.

Deep Learning Inference

The NVIDIA A30 graphics processor is specifically optimized for deep learning, meeting the demanding computational needs of AI deployments in data centers. Built on the powerful Ampere architecture, the A30 is equipped with a large number of CUDA Cores and Tensor Cores, enabling exceptional speed and accuracy in processing neural networks.
This graphics processor excels at large-scale inference workloads across various industries, from natural language processing and image recognition to recommendation systems and autonomous vehicles. The A30’s support for mixed precision computing enhances performance by balancing computational accuracy with efficiency, delivering fast inference results without compromising model precision.
Integration with NVIDIA’s TensorRT inference optimization toolkit further streamlines deployment and maximizes throughput, allowing businesses to scale their AI applications effectively. Overall, the NVIDIA A30 graphics processor is a robust solution for enterprises looking to accelerate their deep learning inference capabilities, providing outstanding performance and scalability in AI-based environments.

Data analysis

The NVIDIA A30 graphics processor is set to revolutionize high-performance data analysis with its robust capabilities and efficient Ampere architecture. Tailored for demanding applications that require large amounts of data, the A30 is equipped with a wealth of CUDA Cores and Tensor Cores that excel in accelerating complex analytical tasks such as large-scale data processing, machine learning, and predictive analytics.
Its high memory bandwidth and support for NVIDIA NVLink technology provide fast access to vast datasets and enable their processing, allowing organizations to quickly extract insights and make informed decisions. The versatility of the A30 includes support for mixed precision computing, optimizing computational performance without sacrificing accuracy, which is critical for effectively handling diverse workloads.
Integrated with NVIDIA’s software toolkits, such as RAPIDS for GPU-accelerated data analysis processes and CUDA-X libraries, the A30 simplifies the deployment and scaling of data analysis solutions in hybrid cloud and on-premises environments. Ultimately, the NVIDIA A30 graphics processor sets a new standard for high-performance data analysis, empowering businesses to extract valuable insights faster and more effectively than ever before.

High-Performance Computing (HPC)

The NVIDIA A30 graphics processor represents a significant advancement in high-performance computing (HPC), designed to deliver unparalleled computational power and efficiency across a wide range of computational tasks. Built on the efficient Ampere architecture, the A30 features a substantial number of CUDA Cores and Tensor Cores optimized to handle complex scientific simulations, numerical analysis, and data-intensive computations with remarkable speed and accuracy.
Its high memory bandwidth and support for NVIDIA NVLink technology facilitate seamless communication between GPUs and other system components, enhancing overall system performance and scalability. The robust computational capabilities of the A30 make it ideal for accelerating applications in fields such as physics, chemistry, weather forecasting, and molecular dynamics, where rapid data processing and simulation are critical.
Integration with NVIDIA’s parallel computing platform and CUDA libraries ensures compatibility and simplifies the development of optimized software solutions, enabling researchers and engineers to effectively tackle larger and more complex problems. In summary, the NVIDIA A30 graphics processor is a powerful solution for HPC environments, offering unmatched performance and reliability to drive innovation and scientific discoveries.

AI Training

The NVIDIA A10 graphics processor is a versatile powerhouse designed to elevate the mainstream of enterprise computing, providing unmatched performance across a variety of workloads. Leveraging the advanced Ampere architecture, the A10 features a significant boost in computational performance, making it ideal for data analytics, Virtual Desktop Infrastructure (VDI), and cloud computing environments.
With its rich set of CUDA Cores and Tensor Cores, the A10 enables accelerated processing of complex computations, facilitating faster insights from large datasets and enhancing machine learning model efficiency. The wide memory bandwidth of the A10 ensures smooth management of data-intensive tasks, while NVIDIA’s virtualization technology allows multiple users to access the GPU’s capabilities concurrently, optimizing resource utilization and reducing operational costs.
Moreover, the A10 seamlessly integrates with NVIDIA’s comprehensive software ecosystem, including CUDA, cuDNN, and TensorRT, ensuring compatibility and ease of deployment within existing IT infrastructures. These features position the NVIDIA A10 as a key asset for enterprises aiming to enhance computational power, streamline operations, and drive innovation.