Collaborative Research: Software Infrastructure for Accelerating Grand Challenge Science with Future Computing Platforms
Collaborative Research: Software Infrastructure for Accelerating Grand Challenge Science with Future Computing Platforms
批准号:
1216696
负责人:
Manish Parashar
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-10-01 至 2014-09-30
中文摘要
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英文摘要
Solving scientific grand challenges requires effective use of cyber infrastructure. Future computing platforms, including Field Programmable Gate Arrays (FPGAs), General Purpose Graphics Processing Units (GPGPUs), multi-core and multi-threaded processors, and Cloud computing platforms, can dramatically accelerate innovation to solve complex problems of societal importance when supported by a critical mass of sustainable software.This project will organize scientific communities to help leverage the disruptive potential of future computing platforms through sustainable software. Grand challenge problems in biological science, social science, and security domains will be targeted based on their under-served needs and demonstrated possibilities. Users will be engaged through interdisciplinary workshops that bring together domain experts with software technologists with the goals of identifying core opportunity areas, determining critical software infrastructure, and discovering software sustainability challenges. The outcome will be an in-depth conceptual design for a Center for Sustainable Software on Future Computing Platforms, as part of the Software Infrastructure for Sustained Innovation (SI2) program. The design, scoped toward grand challenge problems, will identify common and specialized software infrastructure, research, development and outreach priorities, and coordination with the SSE and SSI components of the SI2 program. The interactions will offer a comprehensive understanding of grand challenges that best map to future computing platforms and the software infrastructure to best support scientists' needs. The workshops will enhance understanding of future platforms' potential for transformative research and lead to key insights into cross-cutting problems in leveraging their potential. Published results will help guide future research and reduce barriers to entry for under-represented groups.
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