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HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed) in Saudi Arabia

HPE NVIDIA Tesla V100 32GB HBM2 PCIe 3.0 x16 Passive GPU Computational Accelerator for AI Machine Learning HPC Deep Learning 699-2G500-0216-400 (Renewed)

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Category
Graphic Cards
Weight
477 g
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Special Features

  • NVIDIA Volta GV100 Architecture — 5,120 CUDA Cores, 640 1st-Gen Tensor Cores delivering 14 TFLOPS FP32 and 112 TFLOPS deep learning performance for AI training, inference, HPC, and scientific computing workloads
  • 32GB HBM2 ECC Memory — 900 GB/s Bandwidth — High-bandwidth memory on a 4096-bit bus with ECC error correction provides the memory capacity and throughput required for the largest AI models, simulations, and datasets
  • PCIe 3.0 x16 Interface — 250W TDP — Standard PCIe Gen3 connectivity with passive cooling designed for enterprise rack server deployment in HPE ProLiant, Dell PowerEdge, and Supermicro platforms with adequate chassis airflow
  • NVLink — Scale to 96GB Unified Memory — Connect two V100 GPUs via NVLink at 300 GB/s bi-directional bandwidth to scale GPU memory from 32GB to 96GB for larger AI training and HPC workloads
  • Multi-Precision Computing — Supports FP64 (7 TFLOPS), FP32 (14 TFLOPS), FP16 (112 TFLOPS) and INT8 precision modes for flexible deployment across training, inference, and scientific simulation workloads
  • HPE OEM Validated — P44861-001 — Also known as HPE Part No P44861-001 (Spare No P44899-001), validated for deployment in HPE ProLiant servers including DL380 Gen10, DL360 Gen10, and other PCIe Gen3 x16 compatible platforms

Description

The HPE NVIDIA Tesla V100 PCIe 32GB is an enterprise-grade computational accelerator purpose-built for artificial intelligence, machine learning, deep learning, and high-performance computing workloads. Powered by NVIDIA's Volta GV100 architecture with 5,120 CUDA cores and 640 first-generation Tensor Cores, the V100 delivers 14 TFLOPS of FP32 performance and 112 TFLOPS of deep learning performance — making it one of the most capable data center GPUs available for AI training and inference. Equipped with 32GB of high-bandwidth HBM2 memory on a 4096-bit bus delivering 900 GB/s of memory bandwidth, the V100 handles the largest AI models and datasets with ease. The PCIe 3.0 x16 interface and passive cooling design make it compatible with a wide range of enterprise rack servers including HPE ProLiant, Dell PowerEdge, and Supermicro platforms. NVLink support enables two V100 GPUs to be connected for 96GB of unified memory at 300 GB/s bi-directional bandwidth for even larger workloads. Backed by NVIDIA's proven Volta architecture and HPE enterprise validation for mission-critical data center deployments requiring maximum AI compute density and reliability.

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