876340-001 HPE Nvidia 16GB HBM2 PCIe Tesla V100 GPU

HPE 876340-001 Nvidia 16GB HBM2 PCIe Tesla V100 Computational Accelerator Overview

The HPE 876340-001 Nvidia 16GB HBM2 PCIe Tesla V100 Computational Accelerator is a high-performance GPU built for deep learning, high-performance computing (HPC), and AI workloads in enterprise and data center environments. Leveraging Nvidia's Volta architecture, the Tesla V100 delivers exceptional performance, energy efficiency, and scalability for complex computational tasks. With 16GB of high-speed HBM2 memory, 5120 CUDA cores, and advanced tensor processing capabilities, this accelerator is engineered to handle demanding AI inference, model training, and scientific simulations efficiently and reliably.

Volta GPU Architecture

Advanced Parallel Processing

The Tesla V100 is built on Nvidia's Volta GPU architecture, which provides cutting-edge performance for AI and HPC workloads. The architecture incorporates thousands of CUDA cores optimized for floating-point and integer operations, allowing simultaneous execution of multiple instructions. This parallelism ensures high throughput across compute-intensive tasks such as matrix multiplications, deep learning model training, and scientific simulations.

Tensor Core Integration

The Volta architecture introduces Tensor Cores, specialized processing units designed to accelerate mixed-precision matrix computations. With 640 Tensor Cores in the Tesla V100, AI training and inference tasks are significantly accelerated, delivering up to 125 teraflops of deep learning performance for FP16 operations. This enables rapid experimentation and deployment of complex neural networks across industries.

Enhanced Instruction

Each CUDA core and Tensor Core in the Tesla V100 is designed for maximal instruction throughput, reducing latency and increasing computational efficiency. This allows AI models to execute faster, improving time-to-insight for analytics and scientific research applications.

Scalable Multi-GPU Deployment

The V100 is engineered for multi-GPU setups, enabling scalable deployments in rack-mounted servers and HPC clusters. Multiple Tesla V100 GPUs can work in concert using Nvidia NVLink interconnects, delivering linear performance scaling for large AI and HPC workloads.

Memory Architecture and Bandwidth

16GB HBM2 High-Speed Memory

The HPE 876340-001 features 16GB of HBM2 memory, providing a high-capacity memory buffer for large datasets and deep neural networks. This ensures that models with billions of parameters can fit entirely within GPU memory, reducing the need for frequent data transfer between system memory and GPU memory.

High Bandwidth for Data-Intensive Workloads

With a memory bandwidth exceeding 900 GB/s through a 4096-bit memory interface, the Tesla V100 delivers rapid data movement to and from GPU cores. This high bandwidth is critical for machine learning, deep learning, and scientific computing workloads that require continuous access to large datasets.

Memory and Error Protection

The Tesla V100 supports error-correcting code (ECC) memory, ensuring data integrity in mission-critical applications. ECC protects against memory corruption and maintains reliability during extensive training or inference tasks, making the V100 suitable for enterprise and HPC environments.

Computational Performance

High-Performance AI Training

The Tesla V100 delivers exceptional AI training performance, capable of processing billions of operations per second. Its 5120 CUDA cores, combined with Tensor Cores and high-bandwidth memory, allow it to accelerate the training of deep learning models across image recognition, natural language processing, autonomous vehicles, and scientific simulations.

Scientific and HPC Workloads

In addition to AI, the V100 is optimized for HPC tasks such as molecular dynamics, weather modeling, computational fluid dynamics, and financial simulations. The GPU provides double-precision (FP64) performance up to 7.8 teraflops, ensuring high accuracy for scientific computations.

Mixed Precision Performance

Tensor Cores enable mixed-precision computing, which combines FP16 and FP32 operations to maximize throughput without sacrificing accuracy. This allows researchers and engineers to achieve faster results for deep learning models and HPC applications.

Energy Efficiency

Despite its high computational capability, the Tesla V100 is energy-efficient, consuming approximately 250W TDP. Its passive and active cooling options allow deployment in dense server racks without compromising thermal stability, enabling data centers to scale AI and HPC workloads sustainably.

Deep Learning Framework

The Tesla V100 supports all major deep learning frameworks including TensorFlow, PyTorch, MXNet, Caffe, and Theano. Pre-optimized libraries such as cuDNN and TensorRT allow seamless deployment of AI models, significantly reducing training time and improving inference efficiency.

Real-Time Inference Acceleration

The V100 excels in low-latency AI inference, processing large volumes of queries in real-time. This is critical for applications such as voice recognition, recommendation engines, video analytics, and autonomous systems where rapid decision-making is required.

TensorRT Optimization

Using Nvidia TensorRT, AI developers can optimize models for inference on the V100, achieving up to 8x faster inference compared to CPU-only solutions. This enables enterprises to deploy highly efficient AI solutions at scale.

Video Processing and Graphics Capabilities

High-Density Video Encoding and Decoding

The Tesla V100 is equipped with NVENC and NVDEC engines, enabling simultaneous encoding and decoding of multiple 4K or 8K video streams. This is particularly useful for cloud gaming, live streaming, and media analytics applications where high throughput and low latency are critical.

Scalable Video Transcoding

Multiple V100 GPUs can be deployed in tandem to transcode high volumes of video streams for media platforms, ensuring efficient processing without compromising quality or introducing latency.

Integration with HPE Servers

HPE Compatibility and Optimization

The HPE 876340-001 Tesla V100 is fully certified for HPE ProLiant and Apollo servers, ensuring seamless installation, compatibility, and performance. Its PCIe interface allows it to fit in standard server slots, supporting both single and multi-GPU configurations for high-density AI and HPC deployments.

Scalable Multi-GPU Configurations

Enterprises can deploy multiple Tesla V100 GPUs in a single server to handle parallel workloads, delivering linear performance scaling for deep learning, HPC, and video analytics tasks. NVLink connectivity allows for rapid inter-GPU communication, further enhancing performance.

Enterprise-Grade Reliability

HPE-certified servers provide thermal management, power monitoring, and firmware compatibility for the Tesla V100, ensuring stable operation under continuous workloads. This guarantees maximum uptime for mission-critical applications.

Deployment Flexibility

Whether for cloud AI platforms, HPC clusters, or edge inference servers, the Tesla V100’s form factor and HPE optimization make it suitable for a wide range of deployment scenarios, allowing organizations to scale computational capacity efficiently.

Software Ecosystem and Development Tools

CUDA, cuDNN, and TensorRT

The Tesla V100 integrates seamlessly with Nvidia's CUDA toolkit, cuDNN libraries, and TensorRT for AI deployment. This ecosystem enables developers to optimize AI models for training and inference, ensuring maximum throughput and low latency.

Framework Compatibility

Supports all major AI and HPC frameworks including TensorFlow, PyTorch, MXNet, Caffe, and Theano. Pre-optimized libraries provide acceleration for both training and inference workloads.

Use Cases and Industry Applications

High-Performance Computing

Scientific simulations, weather modeling, molecular dynamics, and computational fluid dynamics benefit from the Tesla V100’s FP64 performance and massive parallel processing capabilities, delivering accurate and accelerated results.

Video Analytics and Media Processing

With advanced NVENC/NVDEC video engines, the Tesla V100 accelerates video decoding, encoding, and AI-driven analytics for smart city applications, live streaming platforms, and surveillance systems.

Enterprise and Cloud Deployment

Enterprises can deploy Tesla V100 GPUs in HPE servers for private cloud AI platforms, high-density data centers, and virtualized environments, maximizing performance-per-watt and ensuring reliable service delivery.