John Romein from ASTRON gave this talk at the GPU Technology Conference. “We’ll discuss how FPGAs are changing as a result of new technology such as the Open CL high-level programming language, hard floating-point units, and tight integration with CPU cores. Traditionally energy-efficient FPGAs were considered notoriously difficult to program and unsuitable for complex HPC applications. We’ll compare the latest FPGAs to GPUs, examining the architecture, programming models, programming effort, performance, and energy efficiency by considering some real applications.”
Consumer GPUs Power 2 Petaflop Deep Learning Cluster at ASTRON
January 21, 2018 by
Today ClusterVision announced the successful deployment of a new high performance computing GPU cluster system for the Netherlands Institute for Radio Astronomy (ASTRON). “By utilizing the deep learning capabilities of the GPU cluster, the telescopes will be able to detect pulsar flashes with much greater accuracy through self-learning. In the past, ASTRON scientists had to manually detect and input pulsar patterns. With deep learning, ARTS does it for them.”
Petaflop Radio Astronomy Signal Processing and the CASPER Collaboration
May 7, 2014 by
In this video from the OpenFabrics International Developer Workshop 2014, SETI@home co-founder Dan Werthimer presents: Petaflop Radio Astronomy Signal Processing and the CASPER Collaboration. As a bellwether for exascale, radio astronomy projects like CASPER and the SKA telescope are pushing the limits of high performance computing.
Extreme Signal-Processing Meets HPC with Petascale Cross-Correlation
May 4, 2014 by
“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.”
