Intel has been selected by DARPA, a U.S. Department of Defense agency, to collaborate on the development of a powerful new data-handling and computing platform that will leverage machine learning and other artificial intelligence (AI) techniques.
The notion of Big Data emerges from the observation that 90 percent of the data available today has been created in just the past two years. From devices at the edge to large data centers crunching everything from corporate clouds to future energy technology simulations, the world is awash in data – being stored, indexed and accessed.
DARPA’s Microsystems Technology Office created the Hierarchical Identify Verify & Exploit (HIVE) program to develop new technologies to realize 1,000x performance-per-watt gains in the ability to handle graph analytics.
Unlike traditional analytics that are tools to study “one to one” or “one to many” relationships, graph analytics can use algorithms to construct and process the world’s data organized in a “many to many” relationship – moving from immediate connections to multiple layers of indirect relationships. While some graphs are small and easy to visualize – such as a family tree – many graphs are vast and constantly changing, and they represent significant complex semantics – such as the evolving search list of every user on the planet for Amazon sales or Apple iTunes.
Intel’s Data Center Group (DCG), Platform Engineering Group (PEG) and Intel Labs will work as one of the hardware architecture research performers for DARPA HIVE, with a joint research program between Intel and DARPA valued at more than $100 million during a 4½-year effort.
“By mid-2021, the goal of HIVE is to provide a 16-node demonstration platform showcasing 1,000x performance-per-watt improvement over today’s best-in-class hardware and software for graph analytics workloads,” said Dhiraj Mallick, vice president of the Data Center Group and general manager of the Innovation Pathfinding and Architecture Group at Intel. “Intel’s interest and focus in the area may lead to earlier commercial products featuring components of this pathfinding technology much sooner.”