Scalable Parallelism in the Extreme

Funding Opportunity ID: 297629
Opportunity Number: 17-600
Opportunity Title: Scalable Parallelism in the Extreme
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Grant
Category of Funding Activity: Science and Technology and other Research and Development
Category Explanation:
CFDA Number(s): 47.070
Eligible Applicants: Others (see text field entitled “Additional Information on Eligibility” for clarification)
Additional Information on Eligibility: *Who May Submit Proposals: Proposals may only be submitted by the following: -Non-profit, non-academic organizations: Independent museums, observatories, research labs, professional societies and similar organizations in the U.S. associated with educational or research activities. -Universities and Colleges – Universities and two- and four-year colleges (including community colleges) accredited in, and having a campus located in, the US acting on behalf of their faculty members. Such organizations also are referred to as academic institutions. *Who May Serve as PI: Each proposal is required to have two or more PIs providing different and distinct expertise relevant to the program’s focus areas.
Agency Code: NSF
Agency Name: National Science Foundation
Posted Date: Sep 23, 2017
Close Date: Jan 09, 2018
Last Updated Date: Sep 23, 2017
Award Ceiling: $0
Award Floor: $0
Estimated Total Program Funding: $10,000,000
Expected Number of Awards: 25
Description: 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 performance improvements through improved processor technologies alone has ended.In recognition of this obstacle, the recent National Strategic Computing Initiative (NSCI) encourages collaborative efforts to develop, “over the next 15 years, a viable path forward for future high-performance computing (HPC) systems even after the limits of current semiconductor technology are reached (the ‘post-Moore’s Law era’).” Exploiting parallelism is one of the most promising directions to meet these performance demands. While parallelism has already been studied extensively and is a reality in today’s computing technology, the expected scale of future systems is unprecedented. At extreme scales, factors that have small impacts today can become highly significant. For example, even short serial program sections can prove destructive to performance. Heterogeneity of processing elements [Central Processing Units (CPUs), Graphics-Processing Units (GPUs), and accelerators] and their memory hierarchies pose significant management challenges. High system complexity may lead to unacceptable latencies and mean time between failures, even if built with highly reliable components. Furthermore, the interconnectedness of large-scale distributed architectures poses an enormous challenge of understanding and providing guarantees on performance behavior. These are just four of many issues arising in the new era of parallel computing that is upon us. The Scalable Parallelism in the Extreme (SPX) program aims to support research addressing the challenges of increasing performance in this modern era of parallel computing. This will require a collaborative effort among researchers in multiple areas, from services and applications down to micro-architecture. SPX encompasses all five NSCI Strategic Objectives, including supporting foundational research toward architecture and software approaches that drive performance improvements in the post-Moore’s Law era; development and deployment of programmable, scalable, and reusable platforms in the national HPC and scientific cyberinfrastructure ecosystem; increased coherence of data analytic computing and modeling and simulation; and capable extreme-scale computing. Coordination with industrial efforts that pursue related goals are encouraged.
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