Wednesday, 24.4.2013, 11:30
Real-time compression for primary storage is quickly becoming widespread as data continues to grow exponentially, but adding compression on the data path consumes scarce CPU and memory resources on the storage system. In this talk I'll present different approaches to efficient estimation of the potential compression ratio of data and how these methods can be applied in advanced storage systems. Our work targets two granularities: the macro scale estimation which is backed up by analytical proofs of accuracy, and the micro scale which is heuristic.
Based on joint work with Oded Margalit, Ronen Kat, Dmitry Sotnikov and Avishay Traeger, from IBM Research - Haifa. This work has recently appeared in FAST 2013.
Bio: Danny is a researcher at the storage systems group at IBM Haifa Research Labs. He completed his PhD at the Weizmann Institute (2006) and before joining IBM spent two years as a Postdoc at the Technion and UCLA/IPAM. His main research interests are storage systems, data compression, security and cryptography.