870917-001 HPE Nvidia 8GB GDDR5 Tesla P4 GPU

HPE 870917-001 Nvidia 8GB GDDR5 Tesla P4 Computational Accelerator Overview

The HPE 870917-001 Nvidia 8GB GDDR5 Tesla P4 Computational Accelerator is a highly efficient, low-profile GPU designed to bring powerful inference acceleration to a wide range of data center and enterprise workloads. Built on Nvidia’s Pascal architecture, the Tesla P4 delivers exceptional energy efficiency, scalability, and performance for deep learning inference, video transcoding, and high-performance computing (HPC) applications. This GPU is optimized for rack servers and cloud-based systems, allowing organizations to achieve remarkable AI and video performance within compact form factors. With 8GB of GDDR5 memory and an efficient 50-75W power envelope, the HPE 870917-001 is ideal for large-scale deployment and edge data centers where space and power are limited.

GPU Architecture and Core Design

Nvidia Pascal Architecture

The Tesla P4 is powered by the Pascal architecture, a major leap in performance and efficiency over previous generations. This architecture incorporates enhanced CUDA cores, improved instruction scheduling, and advanced streaming multiprocessor (SM) design, all contributing to faster computation and superior energy efficiency. The Pascal architecture was engineered to deliver exceptional throughput for parallel workloads, making it ideal for AI inference, real-time analytics, and machine learning applications.

CUDA Core and Tensor Performance

Equipped with 2560 CUDA cores, the Tesla P4 GPU provides the parallel processing capabilities necessary to accelerate deep neural network (DNN) inference. The GPU efficiently handles matrix operations, which are fundamental in AI computation, making it a top choice for real-time inference at scale. This architecture enables data centers to perform high-throughput, low-latency AI services, such as image recognition, natural language processing, and recommendation engines.

Optimized for Inference Acceleration

Unlike GPUs designed for training, the Tesla P4 is optimized specifically for inference tasks. Its Pascal-based architecture supports INT8 precision computing, enabling high-performance inference workloads while maintaining low power consumption. This makes it particularly suitable for applications such as real-time video analytics, search personalization, and voice recognition systems.

Memory and Bandwidth

8GB GDDR5 Memory

The HPE 870917-001 features 8GB of high-bandwidth GDDR5 memory, providing the capacity and speed required to process large neural network models and handle continuous data streaming. The GDDR5 memory enables fast data access, ensuring smooth execution of AI inference and video decoding workloads without bottlenecks.

High Memory Bandwidth

With a memory bandwidth of up to 192 GB/s, the Tesla P4 ensures efficient data transfer between the GPU cores and the memory modules. This high bandwidth supports sustained compute operations for deep learning frameworks such as TensorFlow, PyTorch, and Caffe, enhancing overall processing efficiency.

ECC Memory

The inclusion of Error Correction Code (ECC) memory ensures computational accuracy and reliability. ECC automatically detects and corrects memory errors, preventing data corruption and ensuring the integrity of AI model inference results — an essential feature in mission-critical enterprise deployments.

Power and Thermal Design

One of the most notable features of the HPE 870917-001 Tesla P4 is its exceptional energy efficiency. Operating within a 50-75W power envelope, it delivers outstanding performance-per-watt ratios. This low-power design enables large-scale GPU deployments without the need for costly power or cooling infrastructure upgrades, making it ideal for hyperscale data centers and edge computing environments.

Passive Cooling for Data Centers

The Tesla P4 uses a passive cooling mechanism that relies on system airflow, allowing for quiet and efficient heat dissipation. This design ensures that multiple GPUs can be densely packed in 1U or 2U servers without thermal issues. The passive cooling solution is robust, supporting continuous, high-load operations within professional-grade server enclosures.

Scalable Power Consumption

Organizations can choose between 50W and 75W configurations, depending on performance needs and thermal limitations. This scalability allows flexibility for system architects who need to balance power constraints with compute requirements in diverse deployment environments.

Connectivity and Interface

PCI Express 3.0 x16 Interface

The Tesla P4 connects through a PCI Express 3.0 x16 interface, offering high-speed communication between the GPU and host system. This interface ensures minimal latency and maximum data throughput, allowing the GPU to efficiently process and exchange data with CPUs, storage, and network components in real time.

Compact Form Factor

The Tesla P4 features a low-profile, single-slot form factor, making it perfectly suited for compact servers and high-density configurations. Its small size allows it to fit into a variety of systems, from standard rack-mounted servers to edge computing devices, without compromising on performance or power efficiency.

Multi-GPU

For organizations requiring higher throughput, multiple Tesla P4 GPUs can be deployed in parallel. This scalability enables enterprises to accelerate vast numbers of concurrent inference requests or large-scale video processing tasks while maintaining consistent performance and energy efficiency.

Low Latency for Real-Time Inference

The GPU is optimized for latency-sensitive tasks, enabling real-time predictions and AI services. Whether powering autonomous vehicle perception systems or powering real-time recommendation engines, the Tesla P4 ensures instant response with minimal latency, providing smooth and efficient inference operations.

TensorRT and DeepStream SDK

By supporting Nvidia TensorRT and DeepStream SDK, the Tesla P4 simplifies deployment of AI-powered applications. TensorRT optimizes trained models for inference, improving throughput and reducing response times, while DeepStream SDK provides the necessary tools for video analytics and intelligent video surveillance solutions.

Video Processing and Transcoding Capabilities

Hardware-Accelerated Video Decoding

The HPE 870917-001 features Nvidia’s NVDEC engine, capable of decoding multiple HD and 4K video streams simultaneously. This makes it ideal for video delivery networks, streaming services, and surveillance systems that require efficient video decoding and analytics capabilities.

High-Quality Video Encoding

In addition to decoding, the GPU supports Nvidia NVENC hardware encoding, enabling fast and efficient video compression. This reduces CPU load and allows real-time video transcoding for content distribution, streaming optimization, and live broadcast applications.

Scalable Video Workloads

Data centers can deploy multiple Tesla P4 accelerators to scale their video processing capacity across hundreds or thousands of concurrent streams. This scalability makes the GPU an attractive solution for cloud video platforms, social media companies, and enterprise security applications.

Software Compatibility and Ecosystem

Comprehensive Framework Support

The Tesla P4 supports major AI and HPC frameworks, including TensorFlow, PyTorch, MXNet, Caffe2, and CNTK. It is also compatible with Nvidia CUDA and cuDNN libraries, ensuring optimized performance and easy integration with existing deep learning pipelines.

Nvidia GPU Cloud (NGC) Support

Developers and data scientists can leverage Nvidia GPU Cloud to access pre-trained models, optimized containers, and deployment resources. This ecosystem accelerates the time-to-deployment for AI applications and simplifies the management of GPU-accelerated workflows.

Cloud Integration

The Tesla P4 supports Nvidia GRID and virtual GPU (vGPU) technologies, enabling GPU acceleration in virtualized environments. This capability allows cloud service providers to deliver GPU-powered inference and AI services to multiple virtual machines simultaneously.

Use Cases and Industry Applications

Data Center Inference

The Tesla P4 is ideal for hyperscale data centers that deliver large-scale AI inference services such as voice assistants, recommendation engines, and fraud detection. Its high efficiency allows deployment across thousands of servers to handle millions of real-time queries daily.

Edge Smart Infrastructure

Due to its compact and energy-efficient design, the P4 is perfect for edge AI solutions deployed in smart cities, manufacturing plants, and autonomous systems. It enables intelligent decision-making closer to the data source, reducing latency and bandwidth requirements.

Video Analytics and Surveillance

Enterprises in security and surveillance benefit from the P4’s video decoding and AI inference capabilities. The GPU can analyze multiple camera feeds in real time, performing facial recognition, motion detection, and anomaly detection efficiently.

Healthcare and Medical Imaging

In healthcare, the Tesla P4 accelerates image recognition tasks such as MRI and CT scan analysis. Its computational accuracy and reliability make it an excellent choice for research labs and diagnostic systems that rely on machine learning for medical imaging.

Cloud Services and Content Delivery

Cloud providers use the P4 for scalable inference and video streaming workloads. The GPU’s low-power operation and performance density make it a key enabler of AI-as-a-service (AIaaS) and real-time video delivery networks across the globe.

Integration with HPE Systems

HPE Certified Performance

The HPE 870917-001 Tesla P4 is certified for use in HPE ProLiant and Apollo series servers. This certification ensures optimal compatibility, cooling, and stability when deployed in enterprise-grade infrastructure. HPE’s integration guarantees seamless installation, management, and scaling of GPU resources within data centers.

Optimized for Rack-Scale Deployment

Its low-profile design and passive cooling solution make the Tesla P4 a perfect fit for dense HPE rack-mounted systems. Enterprises can maximize compute capacity per rack while minimizing power and cooling costs, achieving optimal total cost of ownership (TCO).

Performance Advantages

High Performance per Watt

The Tesla P4 delivers outstanding performance-per-watt efficiency, making it one of the most energy-efficient AI accelerators in its class. This advantage allows enterprises to deploy hundreds of GPUs across server racks without exceeding power constraints.

Scalable AI Inference Throughput

By leveraging multiple Tesla P4 GPUs, data centers can handle thousands of simultaneous inference requests with low latency. The scalability of this architecture ensures consistent response times even during peak workloads, supporting real-time services at scale.

Enhanced Reliability and Uptime

With ECC protection and enterprise-grade design, the Tesla P4 maintains long-term stability and reliability in 24/7 operational environments. This reduces downtime and ensures consistent inference accuracy for mission-critical AI workloads.