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- In Stock: 154
- Manufacturer: HP
- Model or Part: 747401-001
- Condition: Refurbished
- Weight: 3.00lb
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Item Condition
New - Sealed or Open Box ConditionExcellent - Almost-New, Missing Original Packaging
Refurbished - Seller Refurbished, Good Condition, Previously Used Item
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Overview
The HP NVIDIA Tesla K40 12GB PCIe 3.0 GPU is a high-performance accelerator designed for demanding scientific, engineering and data-intensive workloads. Built on the Kepler architecture, this board delivers massive parallel processing power while maintaining energy efficiency in server and workstation environments.
Key Features
- 12 GB of GDDR5 memory with 288 bit wide bus for high bandwidth data access
- 2880 CUDA cores enable fast execution of parallel algorithms
- PCIe 3.0 x16 interface provides up to 16 GT/s throughput per lane
- Double precision performance of 1.43 TFLOPS for accurate numeric simulations
- Supports NVIDIA GRID and Virtual GPU technologies for shared resource environments
- Thermal design power (TDP) of 235 watts, optimized cooling for dense deployments
Technical Specifications
- Model/Part Number: 747401-001
- GPU Architecture: Kepler GK110B
- Core Clock: 745 MHz (base) / 875 MHz (boost)
- Memory Capacity: 12 GB GDDR5
- Memory Speed: 6.0 Gbps
- Memory Bandwidth: 288 GB/s
- CUDA Cores: 2880
- PCI Express Interface: PCIe Gen3 x16
- Maximum Power Consumption: 235 W
- Form Factor: Full height, full length card with dual slot cooling
Applications
- High performance computing (HPC) simulations such as fluid dynamics and molecular modeling
- Deep learning training and inference for neural networks
- Large scale data analytics and machine learning pipelines
- Computer aided engineering (CAE) tasks including finite element analysis
- Scientific research requiring double precision calculations
- Virtual desktop infrastructure (VDI) and GPU sharing in cloud environments
This NVIDIA Tesla K40 GPU provides the compute density and reliability needed to accelerate complex workloads, making it an ideal choice for researchers, engineers and data scientists seeking to push the limits of their applications.