Astronomical real-time streaming signal processing on a Blue Gene/L supercomputer
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
ZOID: I/O-forwarding infrastructure for petascale architectures
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
Overview of the IBM Blue Gene/P project
IBM Journal of Research and Development
Using many-core hardware to correlate radio astronomy signals
Proceedings of the 23rd international conference on Supercomputing
Vectorization techniques for the Blue Gene/L double FPU
IBM Journal of Research and Development
Performance and Scalability Evaluation of 'Big Memory' on Blue Gene Linux
International Journal of High Performance Computing Applications
Achieving a single compute device image in OpenCL for multiple GPUs
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming
Performance and Scalability Evaluation of 'Big Memory' on Blue Gene Linux
International Journal of High Performance Computing Applications
The LOFAR beam former: implementation and performance analysis
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part II
ExaScale high performance computing in the square kilometer array
Proceedings of the 2012 workshop on High-Performance Computing for Astronomy Date
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LOFAR is the first of a new generation of radio telescopes.Rather than using expensive dishes, it forms a distributed sensor network that combines the signals from many thousands of simple antennas. Its revolutionary design allows observations in a frequency range that has hardly been studied before. Another novel feature of LOFAR is the elaborate use of software to process data, where traditional telescopes use customized hardware. This dramatically increases flexibility and substantially reduces costs, but the high processing and bandwidth requirements compel the use of a supercomputer. The antenna signals are centrally combined, filtered, optionally beam-formed, and correlated by an IBM Blue Gene/P. This paper describes the implementation of the so-called correlator. To meet the real-time requirements, the application is highly optimized, and reaches exceptionally high computational and I/O efficiencies. Additionally, we study the scalability of the system, and show that it scales well beyond the requirements. The optimizations allows us to use only half the planned amount of resources, and process 50% more telescope data, significantly improving the effectiveness of the entire telescope.