Paper Title: Machine Learning and Storage Applications

Paper Abstract: Today we are experiencing the intersection of multiple trends, each of which changes the storage and data landscape in powerful ways. Machines and applications generate massive quantities of new data whose value degrades over time unless it can be efficiently analyzed. Both new and long-existing machine learning and deep learning algorithms have shown promise at extracting insight from data for a wide range of usages. Hardware innovations in CPUs, DRAM, and persistent memory are now able to scale these analytic techniques. In addition, new architectures for data processing and storage have emerged, while existing architectures such as in-memory databases have also been extended to address these workloads. This talk will describe the intersections between machine learning and storage applications, covering the implications of machine learning and analytics as a new use case for storage, as well as how machine learning can be used within the storage infrastructure and applications.

Paper Author: Nisha Talagala, CTO, ParallelM

Author Bio: Nisha Talagala is Co-founder, CTO/VP of Engineering at ParallelM, a startup focused on Production Machine Learning. As Fellow at SanDisk and Fellow/Lead Architect at Fusion-io, she led advanced technology development in Non-Volatile Memory and applications. Nisha has more than 15 years of expertise in software, distributed systems, machine learning, persistent memory, and flash. Nisha was also technology lead for server flash at Intel - where she led persistent memory/flash technology and storage-memory convergence. Nisha was also the CTO of Gear6, where she designed clustered computing caches for HPC. Nisha also served at Sun Microsystems, where she developed I/O solutions and file system optimization. Nisha earned her PhD at UC Berkeley on distributed systems research. Nisha holds 56 patents in distributed systems, networking, storage, performance and non-volatile memory. Nisha is a frequent speaker at both industry and academic conferences and serves on multiple technical conference program committees.