Division of Computing and Communication Foundations
Exploiting Parallelism and Scalability (XPS)CONTACTS
|Anindya Banerjeeemail@example.com||(703) 292-7885|
|Tracy Kimbrelfirstname.lastname@example.org||(703) 292-7924|
|Tao Liemail@example.com||(703) 292-8238|
|Amy Aponfirstname.lastname@example.org||(703) 292-7939|
|Mimi McClureemail@example.com||(703) 292-5197|
|Rajiv Ramnathfirstname.lastname@example.org||(703) 292-4776|
|Aidong Zhangemail@example.com||(703) 292-5311|
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 17-1), is effective for proposals submitted, or due, on or after January 30, 2017. Please be advised that, depending on the specified due date, the guidelines contained in NSF 17-1 may apply to proposals submitted in response to this funding opportunity.
Computing systems have undergone a fundamental transformation from the single-core processor-devices of the turn of the century to today's ubiquitous and networked-devices with multicore/many-core processors along with warehouse-scale computing via the cloud. At the same time, semiconductor technology is facing fundamental physical limits and single-processor performance has plateaued. This means that the ability to achieve predictable performance improvements through improved processor technologies alone has ended. Thus, parallelism has become critically important.
The Exploiting Parallelism and Scalability (XPS) program aims to support groundbreaking research leading to a new era of parallel computing. Achieving the needed breakthroughs will require a collaborative effort among researchers representing all areas -- from services and applications down to the micro-architecture -- and will be built on new concepts, theories, and foundational principles. New approaches to achieving scalable performance and usability need new abstract models and algorithms, new programming models and languages, and new hardware architectures, compilers, operating systems and run-time systems, and must exploit domain and application-specific knowledge. Research is also needed on energy efficiency, communication efficiency, and on enabling the division of effort between edge devices and clouds.< /p>