Nvidia 699-2G500-0200-500 HBM2 Passive CUDA 16GB GPU Accelerator Card

699-2G500-0200-500 Nvidia Tesla CUDA 16GB GPU Accelerator Card

The 699-2G500-0200-500 Nvidia Tesla V100 GPU Accelerator represents a pinnacle in high-performance computing, designed for demanding applications like deep learning, scientific simulations, and AI workloads. Built with cutting-edge Volta architecture and featuring HBM2 memory, this card provides exceptional performance and efficiency for a wide array of use cases.

Advanced Volta Architecture

The Nvidia Tesla V100 is powered by Volta, a revolutionary GPU architecture that delivers groundbreaking performance improvements. This design integrates Tensor Cores to accelerate AI computations and floating-point arithmetic, enabling up to 125 teraflops of deep learning performance. This architecture is optimized for both single-precision (FP32) and double-precision (FP64) workloads, making it suitable for data-intensive scientific and AI applications.

Enhanced CUDA Core Efficiency

The Tesla V100 features 5,120 CUDA cores, delivering unparalleled parallel processing capabilities. These cores significantly boost performance for compute-heavy tasks, such as simulations, ray tracing, and molecular modeling. The CUDA cores are designed to run multiple tasks simultaneously, reducing latency and increasing throughput for data-intensive workflows.

Tensor Core Technology

Tensor Cores are a defining feature of the Tesla V100, enabling specialized operations for AI and machine learning. These cores accelerate matrix multiplications, a fundamental operation in neural networks, making this GPU ideal for training and inference tasks. The Tensor Core technology also enhances mixed-precision computing, which balances precision and computational speed, further optimizing performance.

High-Bandwidth HBM2 Memory

With 16GB of HBM2 (High-Bandwidth Memory 2), the Tesla V100 achieves unparalleled memory performance. The HBM2 memory architecture offers bandwidth up to 900 GB/s, ensuring faster data transfer and lower latency. This is particularly critical for large-scale simulations, rendering, and real-time analytics, where memory bottlenecks can hinder performance.

Memory Optimization for Complex Workloads

The 16GB of HBM2 memory is designed for workloads requiring extensive memory access. Whether you're working on genomics research, seismic imaging, or deep neural network training, the high memory bandwidth allows for seamless data processing. Its stacked memory configuration ensures faster data availability compared to traditional GDDR memory solutions.

Passive Cooling Design

The Tesla V100 employs a passive cooling design, making it ideal for data center deployments. Passive cooling reduces noise and ensures compatibility with server chassis cooling solutions. This design minimizes maintenance while delivering consistent performance even under prolonged operation, making it perfect for 24/7 environments.

Energy Efficiency and Thermal Management

Despite its high computational power, the Tesla V100 is energy-efficient, consuming less power per operation than previous-generation GPUs. This efficiency reduces operational costs for data centers and ensures lower heat output, enhancing overall system stability and reliability.

Applications and Use Cases

The Nvidia Tesla V100 excels in diverse industries, including scientific research, financial modeling, and artificial intelligence. Its versatile design supports multiple frameworks and APIs, such as TensorFlow, PyTorch, and CUDA, ensuring compatibility with existing and emerging technologies.

Deep Learning and AI

The Tesla V100 is a cornerstone for AI development, supporting both training and inference workloads. With its Tensor Core technology and optimized memory architecture, it accelerates neural network computations, enabling faster model training and deployment. This makes it a preferred choice for AI researchers and organizations scaling their AI capabilities.

High-Performance Computing (HPC)

The Tesla V100's exceptional parallel processing capabilities make it a standout in HPC environments. It is used in fields such as aerospace, automotive design, and energy exploration to run simulations and analyses that would otherwise require weeks of CPU-based computation.

Integration and Compatibility

The 699-2G500-0200-500 Nvidia Tesla V100 is designed for seamless integration into existing data center infrastructures. Its form factor and power requirements align with industry standards, simplifying deployment. It supports leading virtualization platforms and GPU clustering solutions, making it an adaptable choice for diverse computing environments.

Multi-GPU Scalability

The Tesla V100 supports multi-GPU configurations, allowing organizations to scale performance to meet their computational needs. Whether it's a single workstation or a supercomputing cluster, the V100 delivers consistent and scalable performance, ensuring flexibility for future upgrades.

Software Ecosystem

Nvidia provides an extensive software suite to complement the Tesla V100, including the CUDA toolkit, cuDNN, and TensorRT. These tools enhance development workflows, optimize GPU performance, and simplify the implementation of AI models. This ecosystem ensures developers can maximize the Tesla V100's capabilities with minimal overhead.

Durability and Reliability

The Tesla V100 is engineered for durability, capable of withstanding the demands of enterprise-grade applications. Nvidia's rigorous testing standards ensure that each GPU delivers consistent performance under varying conditions, making it a reliable choice for mission-critical operations.

Data Integrity

ECC (Error-Correcting Code) memory is integrated into the Tesla V100, safeguarding against data corruption during computations. This feature is essential for scientific and financial applications where data accuracy is paramount.