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The forthcoming Extremely Large Telescopes all require adaptive optics systems for their successful operation. The real-time control for these systems becomes computationally challenging, in part limited by the memory bandwidths required for wavefront reconstruction. We investigate new POWER8 processor technologies applied to the problem of real-time control for adaptive optics. These processors have a large memory bandwidth, and we show that they are suitable for operation of first-light ELT instrumentation, and propose some potential real-time control system designs. A CPU-based real-time control system significantly reduces complexity, improves maintainability, and leads to increased longevity for the real-time control system.
The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an Adaptive Optics (
We demonstrate a novel architecture for Adaptive Optics (AO) control based on FPGAs (Field Programmable Gate Arrays), making active use of their configurable parallel processing capability. SPARCs unique capabilities are demonstrated through an imple
We propose a solution to the increased computational demands of Extremely Large Telescope (ELT) scale adaptive optics (AO) real-time control with the Intel Xeon Phi Knights Landing (KNL) Many Integrated Core (MIC) Architecture. The computational dema
The next generation of Adaptive Optics (AO) systems on large telescopes will require immense computation performance and memory bandwidth, both of which are challenging with the technology available today. The objective of this work is to create a fu
For ExAO instruments for the Giant Segmented Mirror Telescopes (GSMTs), alternative architectures of WFS are under consideration because there is a tradeoff between detector size, speed, and noise that reduces the performance of GSMT-ExAO wavefront c