Getting Rid of the Deep Learning Silo in the Data Center

With an electrical engineering education from Purdue University (PhD) and the Indian Institute of Technology Bombay (BS, MS), and nearly 25 years of experience in the semiconductor, systems, and hyperscale service provider industries, he has a broad perspective on hardware design and deployment. The elasticity of cloud infrastructure is a key enabler for enterprises and internet services, creating a shared pool of compute resources that various tenants can draw from as their workloads ebb and flow. Cloud tenants are spared the details of capacity and supply planning. This worked well because modern server systems are very efficient at a multitude of general computing tasks. Deep learning, however, creates new complexities for this model.