September 26-27, 2016
New York, NY

Intel's new processors: A machine-learning perspective

Amitai Armon (Intel)
1:30pm–2:10pm Tuesday, 09/27/2016
Implementing AI
Location: 3D09 Level: Beginner

Prerequisite knowledge

  • A basic familiarity with machine learning
  • What you'll learn

  • Learn how to choose the right hardware for your computations, based on acquaintance with the characteristics of the available hardware and software
  • Description

    Intel has recently released new server processors for the Xeon and Xeon Phi product lines. Amitai Armon discusses how these processors are used for machine-learning tasks and offers data on their performance for several types of algorithms in both single-node and multinode settings.

    Amitai provides performance results for a variety of common machine-learning tasks, demonstrating the relevant capabilities of each processor and what can be achieved through parallelization. In addition, Amitai offers an overview of the relevant software stack available for each processor and explores its deployment and usability.

    Photo of Amitai Armon

    Amitai Armon


    Amitai Armon is the chief data scientist for Intel’s Advanced Analytics group, which provides solutions for the company’s challenges in diverse domains ranging from design and manufacturing to sales and marketing, using machine learning and big data techniques. Previously, Amitai was the cofounder and director of research at TaKaDu, a provider of water-network analytics software to detect hidden underground leaks and network inefficiencies. The company received several international awards, including the World Economic Forum Technology Pioneers award. Amitai has about 15 years of experience in performing and leading data science work. He holds a PhD in computer science from the Tel Aviv University in Israel, where he previously completed his BSc (cum laude, at the age of 18).