Presented By O'Reilly and Cloudera
Make Data Work
31 May–1 June 2016: Training
1 June–3 June 2016: Conference
London, UK

Opportunities for hardware acceleration in big data analytics

Kanu Gulati (Zetta Venture Partners)
16:35–17:15 Friday, 3/06/2016
Visualization & user experience
Location: Capital Suite 14 Level: Non-technical

The more data we collect, the more computational power we need to analyze the data. Hardware-accelerated approaches are ready to meet challenges in data analytics with regard to data I/O, computational capacity, interactive visualization, etc. Simply stated, data analytics and high-performance computing (HPC) evolution must go hand in hand.

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 provides an overview of the advances in hardware acceleration and the landscape of solutions built using custom ICs, FPGAs, and GPUs 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.