Nvidia 900-2G500-0140-030 Tesla V100S 32GB HBM2 GPU Accelerator Card

NVIDIA 900-2G500-0140-030 Tesla V100S 32GB HBM2 Passive GPU PCIe Accelerator Card Overview

The NVIDIA 900-2G500-0140-030 Tesla V100S 32GB HBM2 Passive GPU PCIe Accelerator Card represents one of the most advanced solutions in GPU acceleration technology. Built to deliver extreme parallel computing performance, the Tesla V100S is specifically designed for high-performance computing (HPC), deep learning, and artificial intelligence (AI) applications. This GPU card integrates Volta architecture and HBM2 memory to provide exceptional speed and efficiency for data centers and enterprise-level tasks.

Features and Technical Specifications of the Tesla V100S GPU

The Tesla V100S offers a range of innovative features and specifications that make it an essential part of any modern data center infrastructure:

• Memory Type: 32GB HBM2, delivering ultra-fast data transfer and handling complex workloads efficiently.
• Memory Bandwidth: Up to 1 TB/s, ensuring seamless data movement and reduced bottlenecks in high-throughput applications.
• Tensor Cores: Equipped with 640 Tensor Cores that accelerate AI training and inference tasks, boosting overall performance in deep learning models.
• CUDA Cores: 5,120 CUDA cores to handle parallel tasks, ensuring higher processing power for intensive computing tasks.
• Peak Single-Precision Performance: Up to 16.4 TFLOPS, which is ideal for tasks requiring massive computational throughput.

Deep Learning and AI Capabilities

With its groundbreaking architecture, the NVIDIA Tesla V100S excels in deep learning and AI applications. The 640 Tensor Cores embedded in the GPU enable deep neural networks to train faster and with higher precision. This performance advantage directly benefits industries such as healthcare for medical image analysis, autonomous driving technology, and financial services for predictive modeling.

Mixed Precision Computing for Maximum Efficiency

The Tesla V100S supports mixed-precision computing, allowing for the combination of FP32 (single-precision) and FP16 (half-precision) calculations. This leads to faster training times without sacrificing the accuracy of models. The seamless integration of mixed-precision training is vital for developing models that require extensive data processing capabilities.

Enhanced Data Center Efficiency

Designed for use in data centers, the Tesla V100S 32GB GPU boasts power efficiency while providing maximum computational output. The GPU is a passive card, relying on external cooling systems within server racks to maintain optimal performance. This design minimizes energy consumption and heat production, which is critical for maintaining the longevity and reliability of data center hardware.

Power Requirements and Cooling Solutions

Operating efficiently within a data center environment, the Tesla V100S uses a passive cooling solution. This approach requires a robust cooling infrastructure in server racks to manage heat dissipation effectively. The GPU’s power requirements are optimized to ensure consistent performance without excessive energy expenditure, making it a sustainable option for long-term use in enterprise-grade data centers.

Applications and Use Cases for the NVIDIA Tesla V100S

The versatile nature of the NVIDIA Tesla V100S GPU makes it applicable in various industries:

High-Performance Computing (HPC)

For scientific research and simulations, the Tesla V100S offers the computational power necessary for tasks such as climate modeling, molecular dynamics, and physics simulations. Its ability to process massive datasets efficiently makes it an indispensable tool for research institutions and universities conducting intensive data analysis.

Climate and Environmental Modeling

The GPU's computational capabilities allow researchers to model complex climate systems, improving the accuracy and speed of predictions. Such enhanced computational throughput supports governments and organizations in making informed decisions based on high-fidelity simulations.

Deep Learning and AI Research

Deep learning researchers benefit from the Tesla V100S’s combination of high memory bandwidth and massive parallel processing power. Training complex neural networks becomes faster, which speeds up the development of new machine learning algorithms and applications. This GPU is particularly suited for tasks involving natural language processing, computer vision, and generative AI models.

Training Large Language Models (LLMs)

Language models with billions of parameters, like those used in NLP, can leverage the Tesla V100S for efficient training cycles. The GPU’s high Tensor Core count enhances the parallel execution of matrix operations, making it ideal for processing and training transformer-based models.

Enterprise Data Analytics

Enterprises that rely on big data analysis can utilize the NVIDIA Tesla V100S to speed up data processing and extract insights more rapidly. This allows for real-time business intelligence and decision-making processes that improve operational efficiency and strategic planning.

Why Choose the NVIDIA 900-2G500-0140-030 Tesla V100S?

The choice of the Tesla V100S as a GPU solution for data centers, research labs, and enterprises comes down to its unmatched performance and efficiency:

• Scalable Performance: The Tesla V100S can be integrated into multi-GPU servers, scaling up computing power for larger and more complex workloads.
• Future-Proof Technology: The use of HBM2 memory and Volta architecture ensures that this GPU remains relevant as software and algorithmic requirements evolve.
• Industry-Leading Support: NVIDIA provides comprehensive driver and software support to maintain compatibility with the latest deep learning frameworks and high-performance computing applications.

Compatibility and Integration

The Tesla V100S PCIe Accelerator Card is compatible with most modern server configurations. Its integration into systems with PCIe slots ensures flexibility, allowing it to be part of mixed-GPU or hybrid CPU-GPU environments. This makes it a versatile addition for IT administrators looking to upgrade or expand their data center's capabilities.

Multi-GPU Configurations

Utilizing the Tesla V100S in a multi-GPU setup can amplify the performance of applications that benefit from distributed parallel processing. This approach can significantly reduce the time required for processing complex computations, making it an essential strategy for handling expansive datasets and simulations.

Conclusion

The NVIDIA 900-2G500-0140-030 Tesla V100S 32GB HBM2 Passive GPU PCIe Accelerator Card is engineered to meet the demands of data-intensive operations. From AI model training to high-performance computing, this GPU ensures optimal performance and efficiency across a variety of applications. Its combination of HBM2 memory, Tensor Cores, and CUDA Cores positions it as a leading choice for enterprises and researchers aiming for cutting-edge computational power.