NVDIA 900-2G500-0010-000 Tesla V100 32GB HBM2 CUDA PCI-E GPU Card.

Nvidia 900-2G500-0010-000 Tesla V100 32GB HBM2 CUDA PCI-E 3.0 X16 GPU Accelerator Card

The Nvidia 900-2G500-0010-000 Tesla V100 is a powerful GPU accelerator card designed for high-performance computing (HPC), deep learning, artificial intelligence (AI), and machine learning applications. With a robust 32GB of HBM2 memory and the cutting-edge CUDA architecture, this card is engineered to deliver unprecedented performance and scalability for data-intensive workloads.

As part of Nvidia's Tesla lineup, the Tesla V100 is optimized for data centers, supercomputers, and AI researchers who require immense processing power. Leveraging Nvidia's Volta architecture, the Tesla V100 is equipped with Tensor Cores, making it highly suitable for AI model training, inference, and high-end computational tasks.

Key Features of the Nvidia Tesla V100 32GB GPU Accelerator

The Nvidia Tesla V100 900-2G500-0010-000 GPU accelerator card boasts several industry-leading features that make it one of the most sought-after choices for professionals working in AI, HPC, and machine learning. Some of the standout features include:

High Bandwidth Memory (HBM2)

The 32GB of HBM2 memory ensures lightning-fast data access and exceptional memory bandwidth, crucial for handling complex computations required by AI, deep learning, and scientific simulations. HBM2 is designed to provide up to 900GB/s of memory bandwidth, allowing the Tesla V100 to easily process large datasets without any bottlenecks.

CUDA Architecture

The Tesla V100 is built on Nvidia's CUDA architecture, enabling massive parallel processing. With over 5000 CUDA cores, the V100 can handle tens of thousands of computational tasks simultaneously, making it ideal for workloads requiring high-performance computing capabilities. This architecture significantly accelerates the speed of AI and machine learning algorithms, offering substantial improvements over previous-generation GPUs.

Tensor Cores

One of the most innovative features of the Tesla V100 is its inclusion of Tensor Cores. These specialized cores are specifically designed to accelerate deep learning computations. They allow for faster matrix multiplications, which is essential in deep neural network training. This makes the Tesla V100 a must-have tool for AI researchers and developers who work with machine learning frameworks like TensorFlow, PyTorch, and Caffe.

PCI-E 3.0 X16 Interface

The PCI-E 3.0 x16 interface offers high-speed connectivity, ensuring that the Tesla V100 can transfer data to and from the CPU with minimal latency. This interface is critical for maximizing the performance of multi-GPU setups and ensuring that data flows efficiently between the CPU and the GPU during complex computational tasks.

Applications of Nvidia Tesla V100 32GB GPU Accelerator

The Nvidia Tesla V100 GPU accelerator is ideal for a wide range of applications, especially in fields where performance, scalability, and efficiency are critical. Here are some of the primary use cases:

Artificial Intelligence and Deep Learning

The Tesla V100 is a game-changer for AI and deep learning applications. Its Tensor Cores are optimized for training large deep learning models, significantly reducing training times compared to traditional CPUs or older GPUs. Researchers and data scientists can accelerate neural network training, enabling them to develop more sophisticated AI models faster.

High-Performance Computing (HPC)

In high-performance computing environments, the Tesla V100 excels at running simulations, processing large-scale datasets, and executing scientific computations. Its immense processing power allows researchers to tackle problems that were once impossible to solve on traditional systems. From molecular dynamics to climate modeling, the Tesla V100 delivers unparalleled performance.

Data Analytics and Machine Learning

With its large memory capacity and high throughput, the Tesla V100 accelerates big data analytics tasks. It significantly speeds up the training and deployment of machine learning models, especially those dealing with large volumes of data. Businesses can use Tesla V100 to process and analyze big data, offering quicker insights and facilitating decision-making processes.

Why Choose the Nvidia 900-2G500-0010-000 Tesla V100 32GB GPU Accelerator?

The Tesla V100 stands out in a crowded market of GPU accelerators, offering an unmatched combination of power, efficiency, and versatility. Below are a few reasons why professionals choose the Tesla V100 for their compute-heavy tasks:

Unmatched Performance

The Tesla V100 delivers performance that surpasses other GPU accelerators in its class. Whether you're training AI models, running simulations, or processing large datasets, the V100 provides the performance you need to complete tasks quickly and efficiently. The combination of 32GB of HBM2 memory and 5000+ CUDA cores ensures that no task is too large for the Tesla V100 to handle.

Energy Efficiency

Despite its immense computational power, the Tesla V100 is designed to be energy efficient. The Volta architecture is optimized for performance per watt, meaning that users can achieve high throughput while minimizing power consumption. This is crucial for large-scale deployments in data centers where energy costs can be a significant factor.

Scalability

The Tesla V100 is ideal for scalability, whether you're running a single machine or deploying multiple GPUs across a cluster. With its support for NVLink, the Tesla V100 can be linked with other Tesla V100 GPUs for enhanced scalability, making it a suitable option for large-scale AI and HPC workloads. This allows organizations to scale their GPU resources as their computing needs grow.

Easy Integration into Data Centers

Designed with data centers in mind, the Tesla V100 can easily integrate into existing infrastructure. The PCI-E 3.0 x16 interface ensures that it works with most modern servers and workstations, while the low-profile design allows it to fit into a wide range of server configurations. The Tesla V100 also supports a variety of cooling options, making it adaptable to various operating environments.

Specifications of the Nvidia 900-2G500-0010-000 Tesla V100 32GB HBM2 GPU

Technical Details

• GPU Architecture: Nvidia Volta
• CUDA Cores: 5120
• Memory: 32GB HBM2
• Memory Bandwidth: 900GB/s
• Interface: PCI-E 3.0 x16
• Tensor Cores: 640
• Peak Single Precision (FP32) Performance: 15.7 TFLOPS
• Peak Double Precision (FP64) Performance: 7.8 TFLOPS
• Peak Tensor Performance: 125 TFLOPS (FP16)

Power Requirements

The Tesla V100 has a typical power consumption of 250W and requires a system with sufficient power and cooling. It is essential to ensure that your server or workstation has the appropriate power supply and cooling capabilities to support the Tesla V100 GPU.

Conclusion

The Nvidia 900-2G500-0010-000 Tesla V100 32GB HBM2 CUDA PCI-E 3.0 X16 GPU Accelerator Card is one of the most advanced GPU solutions available today. Designed for the most demanding computing workloads, it offers unparalleled performance, efficiency, and scalability for AI, deep learning, machine learning, and high-performance computing tasks. Its combination of high bandwidth memory, CUDA cores, and Tensor Cores makes it an indispensable tool for researchers, developers, and data scientists looking to push the boundaries of what's possible in computational tasks.