Nvidia 900-2G500-0110-030 Tesla V100 32GB HBM2 CUDA PCIe GPU Accelerator Card.

Nvidia 900-2G500-0110-030 Tesla V100 32GB HBM2 CUDA PCI Express 3.0 x16 GPU Accelerator Card Overview

The Nvidia 900-2G500-0110-030 Tesla V100 32GB HBM2 CUDA PCI Express 3.0 x16 GPU Accelerator Card is a powerful graphics processing unit designed to meet the demanding requirements of AI, deep learning, and high-performance computing (HPC) applications. Known for its exceptional performance, this accelerator card leverages Nvidia's Volta architecture to deliver significant gains in processing power and memory bandwidth, providing users with the tools necessary for running complex workloads in data centers and research environments.

Key Features of the Nvidia Tesla V100 GPU Accelerator

The Nvidia 900-2G500-0110-030 Tesla V100 GPU Accelerator Card is packed with high-end features, making it ideal for a range of computational tasks. Below are some key aspects that distinguish this card from other GPUs in the market:

• CUDA Cores: The Tesla V100 comes with over 5,000 CUDA cores, providing immense parallel processing power for a variety of applications from scientific research to machine learning and simulation.
• 32GB HBM2 Memory: With 32GB of high-bandwidth memory (HBM2), the Tesla V100 offers more memory capacity and bandwidth than most GPUs in its class, enabling users to process larger datasets without bottlenecks.
• Volta Architecture: Built on Nvidia’s Volta architecture, the Tesla V100 provides up to 12 times higher performance than previous generations in AI and deep learning applications.
• PCI Express 3.0 x16: The card is equipped with PCIe 3.0 x16 interface, ensuring fast communication between the GPU and the system’s CPU, which is essential for workloads requiring high data throughput.
• Tensor Cores: The inclusion of Tensor Cores optimizes matrix operations, providing significant speedups in deep learning, training, and inference tasks.

Designed for Advanced Applications

Targeted primarily at AI researchers, data scientists, and professionals involved in large-scale simulations, the Nvidia Tesla V100 32GB HBM2 card delivers groundbreaking performance across several advanced use cases, including:

• Deep Learning: Train and deploy large-scale deep learning models efficiently with the Tesla V100's Tensor Cores and massive memory bandwidth.
• High-Performance Computing (HPC): Run complex simulations, computations, and analyses that require massive parallel processing power.
• Data Analytics: Analyze vast amounts of data quickly by leveraging the Tesla V100's incredible processing capabilities, making it perfect for big data applications.
• Scientific Computing: Speed up simulations and computations for scientific research in physics, chemistry, biology, and more.

Unparalleled Performance in AI and Machine Learning

The Nvidia Tesla V100 32GB HBM2 GPU is specifically optimized for artificial intelligence and machine learning tasks, making it the ideal choice for enterprises and researchers working with large datasets. With the power of the Volta architecture and dedicated Tensor Cores, this accelerator card is able to drastically reduce the time it takes to train complex models.

AI Training and Inference

AI training requires immense computational power, as neural networks are complex structures that process large amounts of data to learn patterns and make predictions. The Tesla V100 excels at this task thanks to its high processing throughput and efficient Tensor Cores that accelerate deep learning tasks.

Faster Neural Network Training

With the Tesla V100, users can dramatically reduce the time required to train large-scale neural networks. The card’s 32GB of HBM2 memory ensures that it can handle massive datasets, and its Tensor Cores are optimized for matrix operations, which are essential in neural network training. As a result, researchers can iterate faster, getting closer to their goals in less time.

Optimized for Deep Learning Frameworks

The Tesla V100 is fully supported by popular deep learning frameworks such as TensorFlow, PyTorch, and Caffe. These frameworks take advantage of the V100’s unique architecture, ensuring that deep learning workloads can be processed efficiently, whether it’s training models for computer vision, natural language processing, or reinforcement learning.

High-Performance Computing with Tesla V100

In high-performance computing (HPC) environments, the Tesla V100 GPU accelerator provides unparalleled processing capabilities for a wide range of scientific, engineering, and computational workloads. Its immense parallel processing ability enables the rapid execution of complex calculations, simulations, and data analysis tasks that require high throughput and low latency.

Simulations and Modeling

In scientific fields such as physics and chemistry, researchers rely on simulations to model complex systems. The Tesla V100’s computational power allows users to simulate molecular structures, chemical reactions, and other phenomena that would otherwise take days or weeks to compute on traditional processors.

Real-Time Processing

For researchers and engineers working with real-time data, such as weather forecasting or environmental monitoring, the Tesla V100’s high throughput ensures that simulations can be processed quickly and in real-time, improving both speed and accuracy in time-sensitive applications.

Faster Time-to-Insight

The Tesla V100's ability to handle large-scale data analysis and modeling significantly reduces time-to-insight for scientists and engineers. This is especially beneficial in areas like medical research, where fast processing can mean quicker advancements in diagnostics and treatment solutions.

Data Center Applications

The Nvidia Tesla V100 is designed with data center use in mind, providing an ideal solution for organizations that need powerful computational resources in a highly scalable and energy-efficient form. Whether you're running on-premise servers or in a cloud infrastructure, the Tesla V100 can seamlessly integrate into your data center architecture.

Scalable and Energy Efficient

When deploying the Tesla V100 in a data center, scalability is critical. The card supports Nvidia’s NVLink technology, allowing for the connection of multiple GPUs to scale performance even further. Moreover, the Tesla V100 is designed for maximum energy efficiency, ensuring that organizations can achieve exceptional performance without excessive power consumption.

Multi-GPU Setup

In a multi-GPU setup, the Tesla V100 GPUs can work together to provide unprecedented levels of parallel computing power. This is especially useful for large-scale computations that require the combined processing capabilities of multiple GPUs, such as deep learning model training on massive datasets or high-performance simulations for scientific research.

Why Choose the Nvidia Tesla V100?

The Nvidia 900-2G500-0110-030 Tesla V100 32GB HBM2 CUDA PCI Express 3.0 x16 GPU Accelerator Card is a powerhouse that delivers on multiple fronts—performance, scalability, and reliability. Whether you're looking to accelerate AI model training, run HPC simulations, or scale up your data center operations, the Tesla V100 is the ideal solution. Here are some reasons why it stands out:

• Performance: The Tesla V100’s massive core count, combined with Tensor Cores and high-bandwidth memory, ensures that users can tackle the most demanding workloads without compromising on speed.
• Future-Proof Technology: With support for Nvidia's NVLink, high-bandwidth memory, and cutting-edge Volta architecture, the Tesla V100 is built to handle the workloads of tomorrow, making it a future-proof investment for your infrastructure.
• Efficient Power Usage: Despite its power, the Tesla V100 is designed with energy efficiency in mind, making it suitable for both large-scale data centers and more constrained environments where energy consumption matters.

Compatibility and Integration

Integrating the Nvidia 900-2G500-0110-030 Tesla V100 into your computing environment is simple. With its PCIe 3.0 x16 interface, it can be seamlessly installed in compatible server systems and workstations, ensuring that you get the full performance benefits of the accelerator card. Additionally, its compatibility with popular deep learning frameworks and HPC applications ensures that you can quickly get started with your workload.

System Requirements

To ensure optimal performance, it is recommended to pair the Tesla V100 GPU with a compatible CPU and server infrastructure. While the card works with any system that supports PCIe 3.0 x16 slots, Nvidia recommends using the Tesla V100 in systems that have sufficient power supply and cooling to handle the card’s requirements.

Optimal Cooling Solutions

The Tesla V100 is a high-performance card, and as such, it generates considerable heat during operation. Ensuring proper cooling within the server or workstation is critical for maintaining the stability and performance of the GPU. Nvidia provides a variety of cooling solutions to suit different server configurations, helping users optimize their setups for efficiency and longevity.