Google takes a slightly different approach to the HPC market than other cloud vendors . In addition to supporting IaaS capabilities for compute resources , they provide advanced machine learning capabilities they often also refer to as HPC . This is uncommon in the marketplace , as machine learning applies to a different set of domains than HPC . We will discuss Google capabilities in both areas for comparison .
While some customers do run HPC workloads on Google , for jobs like product design , rendering , special effects and other modeling of the physical world , Google does not offer the same breadth of capabilities as other providers . Google has a set of IaaS capabilities , including high CPU count instances , that can be used for HPC workloads .
Google ’ s differentiation lies in the advanced computing capabilities it provides around Machine Learning . Machine learning is commonly leveraged by applications involved in analyzing human interactions , including social media , image analysis and social influences . Google speaks to machine learning capabilities as HPC because of the highly scalable nature of their machine learning implementations and the specialized hardware they leverage to provide high levels of performance . Out of the advanced work Google is doing for machine learning , two unique sets of technology are at the core :
• TensorFlow - TensorFlow is an open source set of libraries for analyzing data flow graphs .
Google Genomics supports genomics analysis workloads , a very common application for HPC , with significantly less upfront configuration and setup than traditional tools .
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