High performance computing systems for autonomous spaceborne missions

doi:10.1177/109434200101500306

High performance computing systems for autonomous spaceborne missions

2001-08-01

4

PRE

AI

DOI：10.1177/109434200101500306

原文链接

原文求助

摘要

En 中文

Future-generation space missions across the solar system to the planets, moons, asteroids, and comets may someday incorporate supercomputers both to expand the range of missions being conducted and to significantly reduce their cost. By performing science computation directly on the spacecraft itself, the amount of data required to be downlinked may be reduced by many orders of magnitude, thus greatly reducing the mass of the resources needed for communication while increasing the quality and quantity of the science achieved. By performing the mission planning in real time directly on the spacecraft, complex and highly responsive missions can be conducted out of range of direct human intervention, and the cost of mission management can be reduced. Through highly replicated computing structures, continued operation can be maintained in the presence of faults by means of graceful degradation. Two classes of systems, reflecting very different strategies of computer system architecture, are actively being pursued by the NASA Jet Propulsion Laboratory (JPL) to take advantage of the opportunity of embedded high performance computing on spacecraft for deep-space missions. Commodity off-the-shelf (COTS) clusters may permit the direct application of commercial computing hardware in loosely coupled ensembles to benefit from the enormous investment of industry in mass-market components. New processor-in-memory (PIM) architectures combine multiple nodes on a single chip of processor-memory pairs exposing the full memory bandwidth. This paper examines the driving issues motivating the use of supercomputing for future deep-space missions and describes two active research projects at NASA JPL that are pursuing both the COTS and PIM strategies for next-generation spaceborne computing.

High performance computing systems for autonomous spaceborne missions

摘要

AI总结

期刊

机构

引用论文