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NVIDIA Tesla K80 2 x Kepler GK210 900-22080-0000-000 24GB (12GB per GPU) 384-bit GDDR5 PCI Express 3.0 x16 GPU Accelerators for Servers
- TESLA K80
- 4992 CUDA Cores
- 24GB GDDR5
- PCI Express 3.0 x16
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Learn more about the NVIDIA 900-22080-0000-000
| Brand | NVIDIA |
|---|---|
| Series | Tesla K80 |
| Model | 900-22080-0000-000 |
| Interface | PCI Express 3.0 x16 |
|---|
| Chipset Manufacturer | NVIDIA |
|---|---|
| GPU | 2 x Kepler GK210 |
| Core Clock | 560MHz Core - Boostable to 876MHz |
| CUDA Cores | 4992 (2496 per GPU) |
| Memory Clock | 10 GHz |
|---|---|
| Memory Size | 24GB (12GB per GPU) |
| Memory Interface | 384-bit |
| Memory Type | GDDR5 |
| Cooler | Passive Heatsink Cooling |
|---|
| Features | Accelerate your most demanding data analytics and scientific computing applications with NVIDIA Tesla GPU Accelerators. Based on the NVIDIA Kepler Architecture, Tesla accelerators are designed to deliver faster, more efficient compute performance. From energy exploration to machine learning, data scientists can crunch through petabytes of data with Tesla accelerators, up to 10x faster than with CPUs. For computational scientists, Tesla accelerators deliver the horsepower needed to run bigger simulations faster than ever. Tesla K80 GPU Accelerator A dual GPU board that combines 24 GB of memory with blazing fast memory bandwidth and up to 2.91 Tflops double precision performance with NVIDIA GPU Boost, the Tesla K80 GPU is designed for the most demanding computational tasks. It's ideal for single and double precision workloads that not only require leading compute performance but also demands high data throughput. Peak double precision floating point performance: 2.91 Tflops (GPU Boost Clocks) 1.87 Tflops (Base Clocks) Peak single precision floating point performance: 8.74 Tflops (GPU Boost Clocks) 5.6 Tflops (Base Clocks) Memory bandwidth (ECC off)**: 480 GB/sec (240 GB/sec per GPU) **With ECC on, 6.25% of the GPU memory is used for ECC bits. For example, 6 GB total memory yields 5.25 GB of user available memory with ECC on. |
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| Date First Available | October 06, 2021 |
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