Grand Challenges

Grand Challenges are difficult but important problems set by various institutions or professions to encourage solutions or advocate for the application of government or philanthropic funds especially in the most highly developed economies and 
Grand challenges are more than ordinary research questions or priorities, they are end results or outcomes that are global in scale; very difficult to accomplish, yet offer hope of being ultimately tractable; demand an extensive number of research projects across many technical and non-technical disciplines and accompanied by well-defined metrics. Lastly, Grand challenges "require coordinated, collaborative, and collective efforts" and must capture "the popular imagination, and thus political support." 
U.S. national computing research.
1980s.
The presidential Office of Science and Technology Policy in the United States set a first list of grand challenges in the late 1980s, to direct research funding for high-performance computing. A grand challenge is a fundamental problem in science or engineering, with broad applications, whose solution would be enabled by the application of high performance computing resources that could become available in the near future. Examples of these grand challenges were said to be:
This was partially in response to the Japanese 5th Generation (or Next Generation) 10-year project.
The list envisioned using high-performance computing to improve understanding and solve problems in:
2000s.
The National Science Foundation updated its list of grand challenges, removing largely completed challenges such as the Human Genome Project, and adding new challenges such as better prediction of climate change, carbon dioxide sequestration, tree of life genetics, understanding biological systems, virtual product design, cancer detection and therapy, and modeling of hazards (such as hurricanes, tornadoes, earthquakes, wildfires, and chemical accidents), and gamma ray bursts. In addition to funding high-performance computing hardware, the NSF proposed to fund research on computational algorithms and methods, software development methods, data visualization, education, and workforce development.