Abstract

Correlators are key components of radio telescopes as they combine the data from all receivers. They are characterized by high data rates, impressive compute loads, and the necessity to process data in real time. Often, these instruments use graphics processing units (GPUs) to correlate the incoming data streams as GPUs are fast, energy efficient, flexible, and programmable with a reasonable programming effort. Recent GPUs are equipped with a new technology, called “tensor cores”, to perform specific (typically artificial intelligence) workloads an order of magnitude more efficiently than regular GPU cores. This paper introduces the Tensor-Core Correlator, a GPU library that exploits this technology for signal processing and allows a GPU to correlate signals five to ten times faster and more energy efficiently than traditional state-of-the-art GPU correlators. The library hides the complexity of the use of tensor cores and can be easily integrated into the GPU pipelines of existing and future instruments, leading to a significant reduction in costs and energy consumption.

Full Text
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