699-2G500-0200-310 Nvidia Tesla V100 16GB HBM2 PCIe GPU.

Nvidia Tesla Tesla V100 16GB HBM2 PCIe GPU Overview

The Nvidia 699-2G500-0200-310 Tesla V100 16GB HBM2 PCIe 3.0 X16 250W Passive CUDA GPU Accelerator Card represents a pinnacle in high-performance computing (HPC) solutions. Designed to deliver extreme computational power for artificial intelligence, deep learning, and scientific simulations, this GPU card leverages the groundbreaking Volta architecture to provide unmatched performance and energy efficiency for enterprise-grade workloads.

Volta Architecture and CUDA Cores

The Tesla V100 is built on Nvidia's Volta architecture, which incorporates 5,120 CUDA cores that deliver unparalleled parallel processing capabilities. This architecture significantly improves single-precision and double-precision floating-point performance, making it ideal for HPC, AI model training, and inference tasks. The architecture also introduces Tensor Cores, designed to accelerate matrix operations commonly used in deep learning, providing a transformative boost to AI workloads compared to previous GPU generations.

High-Bandwidth Memory (HBM2) Technology

Equipped with 16GB of HBM2 memory, the Tesla V100 ensures high-speed data transfer with a memory bandwidth of up to 900 GB/s. This advanced memory configuration allows large datasets and complex models to be processed without bottlenecks, enabling seamless performance for tasks such as neural network training, financial simulations, and large-scale scientific computations. HBM2 technology not only improves throughput but also optimizes energy efficiency, making the Tesla V100 a highly efficient solution for data centers and HPC clusters.

PCIe 3.0 X16 Interface and Passive Cooling

The Nvidia Tesla V100 PCIe variant supports a 3.0 x16 interface, ensuring high-speed connectivity with compatible motherboards and servers. Its 250W passive thermal design allows for flexible deployment in densely packed server racks and GPU clusters. Passive cooling enables integration with data center airflow management systems without requiring additional active cooling mechanisms on the card itself, reducing noise and maintenance requirements.

Scientific Computing and Simulation

High-performance computing is not limited to AI; scientific simulations also demand exceptional GPU performance. The Tesla V100 excels in computational fluid dynamics, molecular modeling, climate simulations, and physics-based computations. Its high double-precision performance ensures accurate calculations, which are critical for scientific accuracy and predictive modeling. Researchers rely on this GPU accelerator to reduce simulation times from weeks to days, significantly improving productivity and research outcomes.

Enterprise and Data Center Integration

The Tesla V100 is optimized for data center and enterprise-level deployments. With support for Nvidia NVLink and seamless integration into GPU clusters, this GPU accelerator enables multi-GPU scaling for workloads that require massive computational resources. IT administrators benefit from its low-maintenance passive cooling and high energy efficiency, which reduce operational costs while maintaining peak performance for AI, HPC, and analytics applications.

Performance Metrics and Benchmarking

Performance benchmarking highlights the Tesla V100's superiority over traditional GPU solutions. With a peak single-precision performance exceeding 14 teraflops and double-precision performance of 7 teraflops, this GPU card enables faster model training, reduced time-to-insight, and improved throughput for complex workloads. Tensor Core operations can reach up to 112 teraflops, providing exponential acceleration for AI-specific matrix calculations. These metrics make the Tesla V100 one of the most powerful GPU accelerators available for demanding computational tasks.

Thermal and Power Management

Despite its high computational output, the Tesla V100 maintains efficient thermal performance through advanced passive cooling design. The 250W power envelope ensures predictable energy consumption, making it suitable for multi-GPU configurations without exceeding data center power limits. Its thermal design aligns with modern server cooling strategies, allowing seamless integration in high-density deployments while maintaining operational stability.

Data Center Optimization and Scalability

The Tesla V100’s passive cooling design and PCIe 3.0 interface make it ideal for dense GPU clusters, allowing multiple units to operate efficiently in shared airflow environments. Data centers can scale workloads dynamically, leveraging Tesla V100 GPUs to accelerate analytics, AI inference, and scientific computation. Its combination of high bandwidth memory, CUDA acceleration, and efficient power consumption supports continuous, large-scale computational operations without compromising reliability.

Security and Reliability Features

Enterprise deployments demand not only performance but also security and reliability. The Tesla V100 includes ECC memory support, ensuring error correction during critical computations. This feature prevents data corruption in sensitive calculations, a necessity for financial modeling, scientific research, and AI workloads. Its long lifecycle and compatibility with enterprise-grade servers ensure consistent uptime and dependable performance across a wide range of applications.

Future-Proofing and Longevity

Designed with forward-looking technologies, the Tesla V100 accommodates the growth of AI and HPC workloads over time. With support for the latest deep learning optimizations, multi-GPU scalability, and high-bandwidth memory architecture, it remains relevant for evolving computational requirements. Organizations can rely on the Tesla V100 for sustained performance in AI research, cloud computing, and scientific simulations for years to come.

Comparative Advantage Over Previous GPU Generations

Compared to Pascal and Maxwell-based GPU accelerators, the Tesla V100 offers substantial improvements in throughput, energy efficiency, and AI performance. Tensor Core technology and HBM2 memory provide significant acceleration in matrix computations and data-heavy operations, making it a preferred choice for enterprises seeking next-level performance. Its passive cooling design, PCIe 3.0 compatibility, and robust software ecosystem ensure seamless integration into modern data center infrastructures, solidifying its position as a leading GPU accelerator for demanding workloads.

Target Markets and Industries

The Tesla V100 serves diverse industries, including high-performance computing, AI research, healthcare analytics, automotive simulation, financial modeling, and scientific research. Its versatility, computational power, and efficiency make it suitable for both small-scale AI projects and large-scale HPC clusters. Organizations benefit from accelerated workflows, reduced computation times, and scalable GPU resources that meet complex business and research objectives.

Academic and Research Applications

Academic institutions leverage Tesla V100 GPUs for machine learning courses, AI research, and scientific simulations. Its compatibility with leading frameworks and libraries provides students and researchers access to high-performance computing environments that facilitate faster experimentation, model testing, and data analysis.

Energy Efficiency and Operational Costs

Despite its high computational power, the Tesla V100 maintains energy-efficient operation. Passive cooling and optimized power consumption reduce electricity costs while maintaining peak performance. Enterprises benefit from lower operational costs and increased reliability, making this GPU accelerator a cost-effective solution for long-term deployment in data centers and research facilities.