GPU compute for AI, machine learning and more
On-demand GPUs for parallel processing workloads such as machine learning, scientific computing, and video processing.
GPU
Scientists, artists, and engineers need access to significant parallel computational power. Linode offers GPU-optimized virtual machines accelerated by the NVIDIA Quadro RTX 6000, harnessing the power of CUDA, Tensor, and RT cores to execute complex processing, deep learning, and ray tracing workloads.
On-demand GPU
Between purchasing, installing, and maintaining GPUs, the cost of ownership is often high. Linode GPUs allow you to leverage the power of GPUs while benefiting from the main value proposition of cloud: turning a capital expense into an operating expense.
Market Leading Hardware
Linode GPUs are NVIDIA Quadro RTX 6000 units, currently considered one of the best in market GPUs. With CUDA, Tensor, and RT cores in each unit, these GPUs support any use cases associated with parallel processing, deep learning, or ray tracing.
Simplifying Complex Use Cases
You focus on your core competencies, we’ll worry about the hardware that makes them possible. Linode GPUs remove the barrier of entry for complex use cases such as machine learning, AI, and video streaming.
Multiple Plan Types
One GPU card isn’t enough for your projected workloads? Not a problem. Linode GPU plans offer up to four cards per instance, depending on how much horsepower you need.
Quadro RTX 6000 Specs
| CUDA Cores (Parallel-Processing) | 4,608 |
|---|---|
| Tensor Cores (Machine & Deep Learning) | 576 |
| RT Cores (Ray Tracing) | 72 |
| GPU Memory | 24 GB GDDR6 |
| RTX-OPS | 84T |
| Rays Cast | 10 Giga Rays / Sec |
| FP32 Performance | 16.3 TFLOPS |
Select the Dedicated + RTX6000 GPU plan for your most specialized workloads
GPU Price-Performance Benchmarking
Also recommended: Infographic: The Business Case for GPUs in the Cloud
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