AGILE: The Future of Data Centric Computing
DescriptionToday’s era of explosive data growth poses serious challenges for society in transforming massive, random, heterogeneous data streams and structures into useful knowledge, applicable to every aspect of modern life, including national security, economic productivity, scientific discovery, medical breakthroughs, and social interactions. The burgeoning data, which is increasing exponentially not only in volume, but in velocity, variety, and complexity, already far outpaces the abilities of current computing systems to execute the complex data analytics needed to extract meaningful insights in a timely manner.
The key problem with today’s computers is that they were designed to address yesterday’s compute-intensive problems rather than today’s data-intensive problems. Transforming massive data streams and structures into actionable knowledge and meaningful results in near real-time requires a complete rethinking of computing architectures and technologies – one that places the primary focus on data access and data movement rather than on faster compute power. The data of interest today and in the future is typically sparse, random, and heterogeneous, with minimal locality (it is randomly distributed across the computer), and characterized by poor data re-use, streaming updates flowing into the system, and fine-grain data movement and parallelism. The computations to be performed are determined by the data, and multiple applications might need simultaneous access to the same data. These are very different conditions than those characteristic of yesterday’s compute-intensive applications.
IARPA’s new AGILE Program aims to provide data-analytic results in time for appropriate response, e.g., to predict impending adversarial events rather than forensically analyzing them after the fact. It will accomplish this goal by developing new system-level intelligent mechanisms for moving, accessing, and storing large, random, time-varying data streams and structures that allow for the scalable and efficient execution of dynamic graph analytic applications. The program solicited system designs that emphasize optimizing the fully integrated system, not independent optimization of individual functionalities. AGILE aims to develop scalable, energy-efficient computing system designs that enable solutions to data-intensive problems as well as traditional compute-intensive problems. These designs will be cost-effective and realizable in silicon prior to the year 2030.
The key problem with today’s computers is that they were designed to address yesterday’s compute-intensive problems rather than today’s data-intensive problems. Transforming massive data streams and structures into actionable knowledge and meaningful results in near real-time requires a complete rethinking of computing architectures and technologies – one that places the primary focus on data access and data movement rather than on faster compute power. The data of interest today and in the future is typically sparse, random, and heterogeneous, with minimal locality (it is randomly distributed across the computer), and characterized by poor data re-use, streaming updates flowing into the system, and fine-grain data movement and parallelism. The computations to be performed are determined by the data, and multiple applications might need simultaneous access to the same data. These are very different conditions than those characteristic of yesterday’s compute-intensive applications.
IARPA’s new AGILE Program aims to provide data-analytic results in time for appropriate response, e.g., to predict impending adversarial events rather than forensically analyzing them after the fact. It will accomplish this goal by developing new system-level intelligent mechanisms for moving, accessing, and storing large, random, time-varying data streams and structures that allow for the scalable and efficient execution of dynamic graph analytic applications. The program solicited system designs that emphasize optimizing the fully integrated system, not independent optimization of individual functionalities. AGILE aims to develop scalable, energy-efficient computing system designs that enable solutions to data-intensive problems as well as traditional compute-intensive problems. These designs will be cost-effective and realizable in silicon prior to the year 2030.
Event Type
Invited Talk
TimeTuesday, 15 November 202210:30am - 11:15am CST
LocationDallas Ballroom/Omni Hotel
TP
XO/EX
Recorded
