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Register a new userDigital Signal Processing using Stream High Performance Computing: A 512-input Broadband Correlator for Radio Astronomy
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A large-N correlator that makes use of Field Programmable Gate Arrays and Graphics Processing Units has been deployed as the digital signal processing system for the Long Wavelength Array station at Owens Valley Radio Observatory (LWA-OV), to enable the Large Aperture Experiment to Detect the Dark Ages (LEDA). The system samples a ~100MHz baseband and processes signals from 512 antennas (256 dual polarization) over a ~58MHz instantaneous sub-band, achieving 16.8Tops/s and 0.236 Tbit/s throughput in a 9kW envelope and single rack footprint. The output data rate is 260MB/s for 9 second time averaging of cross-power and 1 second averaging of total-power data. At deployment, the LWA-OV correlator was the largest in production in terms of N and is the third largest in terms of complex multiply accumulations, after the Very Large Array and Atacama Large Millimeter Array. The correlators comparatively fast development time and low cost establish a practical foundation for the scalability of a modular, heterogeneous, computing architecture.
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A major challenge in modern radio astronomy is dealing with the massive data volumes generated by wide-bandwidth receivers. Such massive data rates are often too great for a single device to cope, and so processing must be split across multiple devices working in parallel. These devices must work in unison to process incoming data in real time, reduce the data volume to a manageable size, and output a science-ready data product. The aim of this chapter is to give a broad overview of how digital systems for radio telescopes are commonly implemented, with a focus on real-time stream processing over multiple compute devices.
Advances in astronomy are intimately linked to advances in digital signal processing (DSP). This special issue is focused upon advances in DSP within radio astronomy. The trend within that community is to use off-the-shelf digital hardware where possible and leverage advances in high performance computing. In particular, graphics processing units (GPUs) and field programmable gate arrays (FPGAs) are being used in place of application-specific circuits (ASICs); high-speed Ethernet and Infiniband are being used for interconnect in place of custom backplanes. Further, to lower hurdles in digital engineering, communities have designed and released general-purpose FPGA-based DSP systems, such as the CASPER ROACH board, ASTRON Uniboard and CSIRO Redback board. In this introductory article, we give a brief historical overview, a summary of recent trends, and provide an outlook on future directions.
Radio astronomy observatories with high throughput back end instruments require real-time data processing. While computing hardware continues to advance rapidly, development of real-time processing pipelines remains difficult and time-consuming, which can limit scientific productivity. Motivated by this, we have developed Bifrost: an open-source software framework for rapid pipeline development. Bifrost combines a high-level Python interface with highly efficient reconfigurable data transport and a library of computing blocks for CPU and GPU processing. The framework is generalizable, but initially it emphasizes the needs of high-throughput radio astronomy pipelines, such as the ability to process data buffers as if they were continuous streams, the capacity to partition processing into distinct data sequences (e.g., separate observations), and the ability to extract specific intervals from buffered data. Computing blocks in the library are designed for applications such as interferometry, pulsar dedispersion and timing, and transient search pipelines. We describe the design and implementation of the Bifrost framework and demonstrate its use as the backbone in the correlation and beamforming back end of the Long Wavelength Array station in the Sevilleta National Wildlife Refuge, NM.
We present a procedure for efficiently compressing astronomical radio data for high performance applications. Integrated, post-correlation data are first passed through a nearly lossless rounding step which compares the precision of the data to a generalized and calibration-independent form of the radiometer equation. This allows the precision of the data to be reduced in a way that has an insignificant impact on the data. The newly developed Bitshuffle lossless compression algorithm is subsequently applied. When the algorithm is used in conjunction with the HDF5 library and data format, data produced by the CHIME Pathfinder telescope is compressed to 28% of its original size and decompression throughputs in excess of 1 GB/s are obtained on a single core.
Dual sideband (2SB) receivers are well suited for the spectral observation of complex astronomical signals over a wide frequency range. They are extensively used in radio astronomy, their main advantages being to avoid spectral confusion and to diminish effective system temperature by a factor two with respect to double sideband (DSB) receivers. Using available millimeter-wave analog technology, wideband 2SB receivers generally obtain sideband rejections ratios (SRR) of 10-15dB, insufficient for a number of astronomical applications. We report here the design and implementation of an FPGA-based sideband separating FFT spectrometer. A 4GHz analog front end was built to test the design and measure sideband rejection. The setup uses a 2SB front end architecture, except that the mixer outputs are directly digitized before the IF hybrid, using two 8bits ADCs sampling at 1GSPS. The IF hybrid is implemented on the FPGA together with a set of calibration vectors that, properly chosen, compensate for the analog front end amplitude and phase imbalances. The calibrated receiver exhibits a sideband rejection ratio in excess of 40dB for the entire 2GHz RF bandwidth.
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