Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA

Opportunities for hardware acceleration in data analytics

Kanu Gulati (Zetta Venture Partners)
11:00am–11:30am Tuesday, 03/29/2016
Emerging Technologies

Location: Hilton, Almaden Ballroom
Average rating: *....
(1.67, 6 ratings)

Prerequisite knowledge

Participants should be familiar with the basics of algorithm acceleration, parallel computing, and SQL querying.

Description

Hardware-accelerated solutions are ready to meet challenges in data analytics with regard to data I/O, computational capacity, and interactive visualization. Simply put, data analytics and HPC evolution must go hand in hand. The more data we collect, the more computational power we need to analyze the data. Big data platforms and supercomputing technologies such as high-speed interconnects and coprocessors are enabling the next major wave of analytics innovation. Just as custom ICs, FPGAs, and GPU technologies greatly assist technical computing solutions today, they are vastly improving complex queries and visualizations for the future. Kanu Gulati offers an overview of the advances in hardware acceleration and the landscape of solutions (academic-, startup-, and large corporation-based) that solve the challenges in enabling real-time data analytics.

Photo of Kanu Gulati

Kanu Gulati

Zetta Venture Partners

Kanu Gulati is a senior associate at Zetta Venture Partners. Kanu has over 10 years of operating experience as an engineer, scientist, and strategist. She owned Intel’s multicore CAD algorithms research roadmap, developed advanced parallel CAD solutions, and pioneered metrics-driven methodology improvements for design flows. In addition, Kanu led due diligence and provided deal support for early-stage investments at Intel Capital and Khosla Ventures. Kanu was the first business hire at MapD (hardware-accelerated data visualization) and held engineering roles at Nascentric (fast-circuit simulation tool, acquired by Cadence) and Atrenta (predictive analytics for design verification and optimization, acquired by Synopsys), among others.

Kanu has coauthored 3 books, a book chapter, 35+ peer-reviewed publications with 370+ citations, and 1 US patent on high-performance computing and hardware acceleration. She has a PhD and master’s degree from Texas A&M University and an undergraduate degree from Delhi College of Engineering. Kanu completed her MBA at Harvard Business School, where she was copresident of the annual Venture Capital and Private Equity Conference.