Name: PCI-e NVIDIA TESLA P100 16GB COMPUTATIONAL ACCEL
Brand: HP
Price: 215.95 USD
Availability: InStock

HP 868585-001 PCI-e NVIDIA TESLA P100 16GB COMPUTATIONAL ACCEL

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$215.95

In Stock: 2
Manufacturer: HP
Model or Part: 868585-001
Condition: Refurbished
Weight: 3.00lb

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Item Condition

New - Sealed or Open Box Condition
Excellent - Almost-New, Missing Original Packaging
Refurbished - Seller Refurbished, Good Condition, Previously Used Item

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Description

Overview

The HP PCI-e NVIDIA TESLA P100 16GB Computational Accelerator (part number 868585-001) delivers massive parallel processing power for demanding scientific, engineering and AI workloads. Designed to fit into standard server chassis, this accelerator leverages the Pascal architecture to provide high throughput, low latency and energy efficient performance in a single PCI Express slot.

Key Features

16 GB of HBM2 memory with 720 GB/s bandwidth for large data sets
Peak double precision (FP64) performance of 5.3 TFLOPS and single precision (FP32) performance of 10.6 TFLOPS
PCIe Gen3 x16 interface ensures fast data transfer between host and accelerator
NVLink compatible for multi-GPU scaling in supported systems
Optimized drivers and libraries from NVIDIA for deep learning, HPC and analytics

Technical Specifications

Model / Part Number: 868585-001
Form Factor: PCIe full height, full length card
Memory Type: HBM2
Total Memory Capacity: 16 GB
Memory Bandwidth: 720 GB per second
CUDA Cores: 3584
Power Consumption: Typical 250 W
Operating Temperature Range: 0 deg to 85 deg C
Supported OS: Linux, Windows Server (64 bit)

Applications

High performance computing simulations such as fluid dynamics and molecular modeling
Deep learning training and inference for neural networks
Big data analytics and real time processing of large data streams
Scientific research requiring double precision calculations
Financial modelling, risk analysis and quantitative trading algorithms

This HP NVIDIA TESLA P100 accelerator provides the raw compute power needed to accelerate complex workloads while maintaining compatibility with existing server infrastructure.