Adaptive Optics Real-time Control Research Articles

A many-core CPU prototype of an MCAO and LTAO RTC for ELT-scale instruments

We propose a many-core CPU architecture for Extremely Large Telescope (ELT) scale adaptive optics (AO) real-time control (RTC) for the multi-conjugate AO (MCAO) and laser-tomographic AO (LTAO) modes. MCAO and LTAO differ from the more conventional single-conjugate (SCAO) mode by requiring more wavefront sensor (WFS) measurements and more deformable mirrors to achieve a wider field of correction, further increasing the computational requirements of ELT-scale AO. We demonstrate results of our CPU based AO RTC operating firstly in SCAO mode, using either Shack-Hartmann or Pyramid style WFS processing, and then in MCAO mode and in LTAO mode using the specifications of the proposed ELT instruments, MAORY and HARMONI. All results are gathered using a CPU based camera simulator utilising UDP packets to better demonstrate the pixel streaming and pipe-lining of the RTC software. We demonstrate the effects of switching parameters, streaming telemetry and implicit pseudo open-loop control (POLC) computation on the MCAO and LTAO modes. We achieve results of < 600$\mu$s latency with an ELT scale SCAO setup using Shack-Hartman processing and < 800$\mu$s latency with SCAO Pyramid WFS processing. We show that our MCAO and LTAO many core CPU architecture can achieve full system latencies of < 1000$\mu$s with jitters < 40$\mu$s RMS. We find that a CPU based AO RTC architecture has a good combination of performance, flexibility and maintainability for ELT-scale AO systems.

Scalable platform for adaptive optics real-time control, part 1: concept, architecture, and validation

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. SPARC's unique capabilities are demonstrated through an implementation on an off-the-shelf inexpensive Xilinx VC-709 development board. The architecture makes SPARC a generic and powerful Real-time Control (RTC) kernel for a broad spectrum of AO scenarios. SPARC is scalable across different numbers of subapertures and pixels per subaperture. The overall concept, objectives, architecture, validation and results from simulation as well as hardware tests are presented here. For Shack-Hartmann wavefront sensors, the total AO reconstruction time ranges from a median of 39.4us (11x11 subapertures) to 1.283 ms (50x50 subapertures) on the development board. For large wavefront sensors, the latency is dominated by access time (~1 ms) of the standard DDR memory available on the board. This paper is divided into two parts. Part 1 is targeted at astronomers interested in the capability of the current hardware. Part 2 explains the FPGA implementation of the wavefront processing unit, the reconstruction algorithm and the hardware interfaces of the platform. Part 2 mainly targets the embedded developers interested in the hardware implementation of SPARC.

Scalable platform for adaptive optics real-time control, part 2: field programmable gate array implementation and performance

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 future-proof adaptive optics platform on an FPGA architecture, which scales with the number of subapertures, pixels per subaperture and external memory. We have created a scalable adaptive optics platform with an off-the-shelf FPGA development board, which provides an AO reconstruction time only limited by the external memory bandwidth. SPARC uses the same logic resources irrespective of the number of subapertures in the AO system. This paper is aimed at embedded developers who are interested in the FPGA design and the accompanying hardware interfaces. The central theme of this paper is to show how scalability is incorporated at different levels of the FPGA implementation. This work is a continuation of Part 1 of the paper which explains the concept, objectives, control scheme and method of validation used for testing the platform.

ELT-scale adaptive optics real-time control with the Intel Xeon Phi Many Integrated Core Architecture

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 demands of an AO real-time controller (RTC) scale with the fourth power of telescope diameter and so the next generation ELTs require orders of magnitude more processing power for the RTC pipeline than existing systems. The Xeon Phi contains a large number (> 64) of low power x86 CPU cores and high bandwidth memory integrated into a single socketed server CPU package. The increased parallelism and memory bandwidth are crucial to providing the performance for reconstructing wavefronts with the required precision for ELT scale AO. Here, we demonstrate that the Xeon Phi KNL is capable of performing ELT scale single conjugate AO real-time control computation at over 1.0 kHz with less than 20 {\mu}s RMS jitter. We have also shown that with a wavefront sensor camera attached the KNL can process the real-time control loop at up to 966 Hz, the maximum frame-rate of the camera, with jitter remaining below 20 {\mu}s RMS. Future studies will involve exploring the use of a cluster of Xeon Phis for the real-time control of the MCAO and MOAO regimes of AO. We find that the Xeon Phi is highly suitable for ELT AO real time control.

Investigation of POWER8 processors for astronomical adaptive optics real-time control

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.

A real-time simulation facility for astronomical adaptive optics

In this paper we introduce the concept of real-time hardware-in-the-loop simulation for astronomical adaptive optics, and present the case for the requirement for such a facility. This real-time simulation, when linked with an adaptive optics real-time control system, provides an essential tool for the validation, verification and integration of the Extremely Large Telescope real-time control systems prior to commissioning at the telescope. We demonstrate that such a facility is crucial for the success of the future extremely large telescopes.

The Durham adaptive optics real-time controller: capability and Extremely Large Telescope suitability

The Durham adaptive optics real-time controller is a generic, high performance real-time control system for astronomical adaptive optics systems. It has recently had new features added as well as performance improvements, and here we give details of these, as well as ways in which optimisations can be made for specific adaptive optics systems and hardware implementations. We also present new measurements that show how this real-time control system could be used with any existing adaptive optics system, and also show that when used with modern hardware, it has high enough performance to be used with most Extremely Large Telescope adaptive optics systems.

Durham adaptive optics real-time controller

The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems.