Built on Google’s Infrastructure
Access some of the same hardware that Google uses to develop high performance machine learning products. GPUs give you the power that you need to process massive datasets. The hardware is passed through directly to the virtual machine to provide bare metal performance.
- Several GPU types available
- NVIDIA® Tesla® K80 GPUs are available today and soon you will be able to select the AMD FirePro S9300 x2 and the NVIDIA® Tesla® P100, depending on your compute and remote visualization needs.
- Bare metal Performance
- GPUs are offered in passthrough mode, directly attached to the virtual machine to provide maximum performance.
- All the Benefits of the Google Cloud
- Run GPU workloads on Google Cloud Platform where you have access to industry-leading storage, networking, and data analytics technologies.
- Fast Video Transcoding
- Experience faster than real-time digital video file conversion on GPUs for GCE.
- Attach GPUs To Any Machine Type
- Optimally balance the processor, memory, high performance disk and GPU power for your individual workload.
- Flexible GPU Counts Per Instance
- Attach up to 8 GPUs to your instance to get the power that you need for your applications.
- GPU Application Frameworks
- Whether your applications require OpenCL, CUDA, Vulkan or OpenGL Compute Engine provides the hardware that you need to accelerate your workloads.
- Per-Minute Billing
- Get the same per-minute billing for GPUs that you do for the rest of Google Cloud Platform's resources. Pay only for what you need while you are using it.
“These new instances of GPUs in the Google Cloud offer extraordinary performance advantages over comparable CPU-based systems and underscore the inflection point we are seeing in computing today. Using standard analytical queries on the 1.2 billion row NYC taxi dataset, we found that a single Google n1-highmem-32 instance with 8 attached K80 GPUs is on average 85 times faster than Impala running on a cluster of 6 nodes each with 32 vCPUs. Further, the innovative SSD storage configuration via NVME further reduced cold load times by a factor of five. This performance offers tremendous flexibility for enterprises interested in millisecond speed at over billions of rows.”— Todd Mostak Founder and CEO , MapD
|SKU||On Demand Price GPU / Hour (USD)|