This presentation addresses the following topic(s):
- Machine learning and HPC: Each worthy of its own investment, or better together? (Alternately: Marriage for the ages, or heading for divorce?)
The challenges of building successful AI and HPC programmes are different ones. In AI, the primary concerns are around finding and ingesting datasources, finding Data Scientists, and keeping them productive, gaining Efficiency from AI Frameworks and the GPU Infrastructures, and applying strong governance. For HPC, analogous concerns exist, but the priorities are very different and so is the impact on the storage environment. This presentation will dissect these challenges and outline the feature sets of Storage and Data Management Environments that can deliver performance, efficiency, security and ease of use to both paradigms. We show real customer examples to demonstrate how employing a Data centric approach to architecture can be the cornerstone of success for AI and HPC infrastructure.
