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Energy-Efficient Computing for Extreme-Scale Science
November 2009 (vol. 42 no. 11)
pp. 62-71
David Donofrio, Lawrence Berkeley National Laboratory
Leonid Oliker, Lawrence Berkeley National Laboratory
John Shalf, Lawrence Berkeley National Laboratory
Michael F. Wehner, Lawrence Berkeley National Laboratory
Chris Rowen, Tensilica
Jens Krueger, Fraunhofer Institute, Germany
Shoaib Kamil, University of California, Berkeley
Marghoob Mohiyuddin, University of California, Berkeley
A many-core processor design for high-performance systems draws from embedded computing's low-power architectures and design processes, providing a radical alternative to cluster solutions.

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6. Research Accelerator for Multiple Processors (RAMP); http:/ramp.eecs.berkeley.edu.
7. D. Burke et al., "RAMP Blue: Implementation of a Manycore 1008 Processor FPGA System," Proc. Reconfigurable Systems Summer Institute 2008 (RSSI 08), July 2008; www.rssi2008.org/proceedings/papers/presentations 19_Burke.pdf.
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9. Nvidia Inc.; www.nvidia.com/objectcuda_home.html.
10. AMD/ATI Inc., "ATI Stream Software Development Kit;" http://developer.amd.com/gpuATIStreamSDK .

Index Terms:
Extreme-scale computing, Chip architectures, Green Flash, Application-driven design, Climate modeling, Embedded systems
Citation:
David Donofrio, Leonid Oliker, John Shalf, Michael F. Wehner, Chris Rowen, Jens Krueger, Shoaib Kamil, Marghoob Mohiyuddin, "Energy-Efficient Computing for Extreme-Scale Science," Computer, vol. 42, no. 11, pp. 62-71, Nov. 2009, doi:10.1109/MC.2009.353
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