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The processing pipeline to create useful astronomical data will require hundreds of peta-operations per second, at a very limited power budget. We analyze the compute, memory and bandwidth requirements for the key algorithms used in the SKA. By studying their implementation on existing platforms, we show that most algorithms have properties that map inefficiently on current hardware, such as a low compute\u2013bandwidth ratio and complex arithmetic. In addition, we estimate the power breakdown on CPUs and GPUs, analyze the cache behavior on CPUs, and discuss possible improvements. This work is complemented with an analysis of supercomputer trends, which demonstrates that current efforts to use commercial off-the-shelf accelerators results in a two to three times smaller improvement in compute capabilities and power efficiency than custom built machines. We conclude that waiting for new technology to arrive will not give us the instruments currently planned in 2018: one or two orders of magnitude better power efficiency and compute capabilities are required. Novel hardware and system architectures, to match the needs and features of this unique project, must be developed.<\/jats:p>","DOI":"10.1177\/1094342014549059","type":"journal-article","created":{"date-parts":[[2014,9,16]],"date-time":"2014-09-16T02:18:57Z","timestamp":1410833937000},"page":"37-50","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":16,"title":["Challenges in exascale radio astronomy: Can the SKA ride the technology wave?"],"prefix":"10.1177","volume":"29","author":[{"given":"Erik","family":"Vermij","sequence":"first","affiliation":[{"name":"IBM Research, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leandro","family":"Fiorin","sequence":"additional","affiliation":[{"name":"IBM Research, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rik","family":"Jongerius","sequence":"additional","affiliation":[{"name":"IBM Research, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Hagleitner","sequence":"additional","affiliation":[{"name":"IBM Research, Zurich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koen","family":"Bertels","sequence":"additional","affiliation":[{"name":"Delft University of Technology, Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2014,9,15]]},"reference":[{"key":"bibr1-1094342014549059","unstructured":"ARM (n.d.) big.LITTLE processing. 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