明星力量: 为什么世界上最大的望远镜依赖 GPUs
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The universe’s oldest, most distant galaxies may hold clues about the future of our own. But even with the world’s largest telescope, scientists won’t be able to see those galaxies clearly without our GPUs.
这 European-Extremely Large Telescope, or E-ELT, will capture images 15 times sharper than the dazzling shots the Hubble telescope has beamed to Earth for the past three decades. Set to begin operations in 2024 on a Chilean mountaintop, it will gather more than 200 times more light than the Hubble, lighting the way for scientists to peer into galaxies far, far away and study the universe in unprecedented detail.
“It could tell us about the origins of the universe, understand how galaxies evolve and even predict what will happen to our galaxy over time,” said Damien Gratadour, a professor at Université Paris Diderot and research scientist at LESIA, Observatoire de Paris, in a talk at the GPU 技术会议this week.
Focusing in on Outer Space
The E-ELT is the first telescope that incorporates what’s known as adaptive optics to reduce the effects of turbulence on the beam of light and provide increased and uniform image quality. In the same way a road seems to shimmer on a hot day, that turbulence prevents scientists from capturing clear, sharp images of the cosmos.
“Deploying extremely large telescopes without adaptive optics is like acquiring a fast sport car and driving it only in first gear,” said Hatem Ltaief, a senior research scientist at King Abdullah University of Science and Technology, who works with Gratadour on E-ELT.
That’s where GPUs are critical, said Ltaief.
The scientists, who met a few years ago at GTC, are running GPU-powered simulations to predict how different configurations of E-ELT will affect image quality. Changes to the angle of the telescope’s mirrors, different numbers of cameras and other factors could improve image quality.
“We’re looking for the best tradeoff between scientific output and price,” Gratadour said.
Simulated Galaxies Observations in Seconds
“Using the DGX-1, it takes only a few seconds to simulate the observation of several galaxies,” said Ltaief. “A few years ago it would take days to do that.”
The pair next plan to use deep learning to more accurately predict what configuration changes will most effectively improve images. But they declined to discuss their plans in more detail because, Ltaief said, “we really want to come back to GTC next year and talk about it then.”
The main image in this story is an illustration of the E-ELT, courtesy of ESO, King Abdullah University of Science and Technology (KAUST) and Observatoire de Paris.