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Podcast: Memory-Driven Computing

Kimberly Keeton from HPE Labs

In this podcast, HPE Distinguished Technologist Kim Keeton describes the concept of Memory-Driven Computing and how it relates to traditional high performance computing. In terms of application areas, Kim also explains her perspective on blockchain and self-driving cars.

Memory-Driven Computing sets itself apart by giving every processor in a system access to a giant shared pool of memory – a sharp departure from today’s systems where relatively small amounts of memory are tethered to each processor. The resulting inefficiencies limit performance.

Changing gears, Kim explains the importance of volunteering and collaboration across academia, government and industry. Known for her professional visibility (ACM Fellow, chair of many important conferences) she goes on to make the case for diversity in our profession.

Kim Keeton is an American computer scientist specializing in databases and computer data storage. She works at HP Labs as a Distinguished Technologist, and was one of the designers of the Express Query metadata database used by Hewlett-Packard as part of their StoreAll large-scale data storage systems.

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