CLOUD VS. ON-PREMISE — Total Cost of Ownership Analysis

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Deep learning applications require powerful multi-GPU systems for development and operation, which can be very expensive to rent in the cloud for long-term operations. The question arises: Which infrastructure offers the best compromise between time-to-solution, cost-to-solution and availability of resources?

To illustrate the benefits of an on-premise solution, let‘s compare the acquisition and operating costs of a 4-GPU system with a comparable cloud-based GPU server, the AWS p3.8xlarge instance from Amazon.

Comparing the Costs: Total Cost of Ownership (TCO)

To be able to present a direct price comparison, we are assuming a 1-year contract for the use of an AWS EC2 P3 instance „p3.8xlarge“ in the region „EU (Frankfurt)“. The lowest rate AWS offers for guaranteed uptime is categorized as Reserved Instance, All Upfront, to be paid 100% in advance. …


Henri Hagenow

UX/UI Expert, Interactive Design & Development, Machine Learning, Digital Consultant, CoFounder of AIME and Sid | | |

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