Hello Universe: NASA’s Next-Gen Space Processor Undergoes Testing

NASA’s High Performance Spaceflight Computing project aims to dramatically improve the computing power of spacecraft. Missions need processors that can withstand the harsh space environment, so they use chips developed years ago that are. The institutional report frames the development in practical terms and ties it to the broader mission or observing effort.

It is relevant because Earth science becomes stronger when local observations can be placed inside a broader physical pattern that spans time and geography. The planet operates as a coupled system in which atmospheric, oceanic, cryospheric and solid-Earth processes interact across timescales from days to millions of years. A measurement that captures one variable at one location and one moment has limited interpretive value until it is embedded in the longer series and wider spatial coverage that allow natural variability to be separated from forced change. 4 min read Preparations for Next Moonwalk Simulations Underway (and Underwater) Small enough to fit in the palm of a hand, NASA’s High Performance Spaceflight Computing processor. Washington 321-432-4624 jasmine. s. hopkins@nasa. gov 2026-031 Share Details Last Updated May 12.

But upgraded chips are needed to enable the development of autonomous spacecraft, accelerate the rate of scientific discovery through faster data analysis, and support astronauts. Building on the legacy of previous space processors, this new multicore system is fault-tolerant, flexible, and extremely high-performing,” said Eugene Schwanbeck, program element.

We are putting these new chips through the wringer by carrying out radiation, thermal, and shock tests while also evaluating their performance through a rigorous functional test. To simulate real-world performance, we are using high-fidelity landing scenarios from real NASA missions that would typically require power-intensive hardware to process huge.

The processor is working as designed and indications show it operating at 500 times the performance of the radiation-hardened chips currently in use. But only the SoCs JPL is testing are built to survive for years, millions (or even billions) of miles from the nearest repair technician, enduring conditions that even the.

The broader interest lies in linking the observation to climatic, geophysical or environmental dynamics that extend well beyond the immediate event or location. Earth science is unusual in that its most important questions operate on timescales that no single research career can observe directly, making the archival record, whether in ice, sediment, rock or satellite data, as important as any new measurement. Results that can be embedded in that record, and that either confirm or challenge the patterns it reveals, carry disproportionate scientific weight.

The project is managed by the Space Technology Mission Directorate’s Game Changing Development (GCD) program based at NASA Langley. The GCD program and JPL, a division of Caltech in Pasadena, California, led the end-to-end maturation of the High Performance Spaceflight Computing technology by developing.

Because the account originates with NASA News Releases, it functions best as a primary institutional report that is close to the data and operations, not as independent scientific validation. Institutional communications are produced by organizations with legitimate interests in presenting their work in a favorable light, which does not make them unreliable but does make them partial. Details that complicate the narrative, including instrument limitations, unexpected failures and results below projections, tend to be minimized relative to progress messages. Technical documentation and peer-reviewed publications, where they exist, provide the complementary layer that institutional releases cannot substitute.

The next step is to place the result inside longer time series and to compare it with independent instruments and independent sites. Earth system observations gain most of their interpretive power from network density and temporal depth, not from any single measurement however precise. Model simulations that assimilate the new data will help clarify whether the observation fits comfortably within known natural variability or represents a shift that existing models do not reproduce.

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