In this video from the GPU Technology Conference 2014, Ben Barsdell from Harvard University presents: Petascale Cross-Correlation: Extreme Signal-Processing Meets HPC.
How do you cross-correlate 10,000 signals 100 million times per second? This is an example of the type of compute-bound problem facing modern radio astronomy, which, paralleling the paradigm shift in computing architectures, has transitioned from monolithic single-dish telescopes to massive arrays of smaller antennas. In this session we will describe how general-purpose HPC installations can be used to achieve scaling of a cross-correlation pipeline to petascale with all the flexibility of a purely-software implementation. Optimizations we will discuss include tuning of the GPU cross-correlation kernel, maximizing concurrency between compute and network operations, and minimizing bandwidth bottlenecks in a streaming application. GPUs are already powering the world’s biggest radio telescope arrays, and this work paves the way for entirely off-the-shelf correlators for the future exascale-generation of instruments.