HPE NVIDIA Tesla V100 SXM2 16GB HBM2 GPU Accelerator Module

• AI model development and training infrastructure
• Deep learning research environments
• High performance computing clusters
• Scientific and engineering simulations
• GPU accelerated data analytics
• Enterprise machine learning workloads
• Research and academic computing platforms
• HPE GPU server replacement programs
• Accelerator capacity expansion in supported server configurations
• Legacy AI and HPC infrastructure modernization

• NVIDIA Tesla V100 computational accelerator
• NVIDIA Volta architecture
• 16GB HBM2 high bandwidth memory
• 5120 NVIDIA CUDA cores
• 640 Tensor Cores
• Up to 900GB/s memory bandwidth
• NVLink high-speed GPU interconnect
• SXM2 server module form factor
• Designed for AI and deep learning workloads
• Suitable for high performance computing
• Supports parallel GPU computing workloads
• HPE server integration for supported configurations
• Designed for data center computational environments
• Supports GPU-accelerated scientific and engineering applications
• Provides a different deployment path from PCIe V100 accelerators through its SXM2 architecture

• Brand: HPE
• Part Number: Q2N66A
• GPU: NVIDIA Tesla V100
• Architecture: NVIDIA Volta
• Module Type: SXM2
• GPU Memory: 16GB HBM2
• CUDA Cores: 5120
• Tensor Cores: 640
• Memory Bandwidth: Up to 900GB/s
• Interconnect: NVLink
• Double Precision Performance: Up to 7.8 TFLOPS
• Single Precision Performance: Up to 15.7 TFLOPS
• Half Precision Performance: Up to 125 TFLOPS
• Maximum Power Consumption: 300W
• Thermal Solution: Passive

WHY CHOOSE THIS PRODUCT?

• Organizations choose Q2N66A when their HPE compute platform specifically requires an SXM2 V100 accelerator rather than a PCIe GPU. The combination of 16GB HBM2, 5120 CUDA cores, 640 Tensor Cores and NVLink makes it materially different from the PCIe V100 family members, while the SXM2 architecture is particularly relevant to supported GPU-optimized server designs. For replacement, expansion or lifecycle extension projects, it can preserve an existing V100-based AI or HPC environment without changing the accelerator architecture, provided the target HPE server configuration explicitly supports Q2N66A.