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Comparing the Power and Performance of Intel’s SCC to State-of-the-Art CPUs and GPUs

Ehsan Totoni, Babak Behzad, Swapnil Ghike, Josep Torrellas
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
International Symposium on Performance Analysis of Systems and Software (ISPASS), 2012

@article{totoni2012comparing,

   title={Comparing the Power and Performance of Intel’s SCC to State-of-the-Art CPUs and GPUs},

   author={Totoni, E. and Behzad, B. and Ghike, S. and Torrellas, J.},

   year={2012}

}

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Power dissipation and energy consumption are becoming increasingly important architectural design constraints in different types of computers, from embedded systems to largescale supercomputers. To continue the scaling of performance, it is essential that we build parallel processor chips that make the best use of exponentially increasing numbers of transistors within the power and energy budgets. Intel SCC is an appealing option for future many-core architectures. In this paper, we use various scalable applications to quantitatively compare and analyze the performance, power consumption and energy efficiency of different cutting-edge platforms that differ in architectural build. These platforms include the Intel Single-Chip Cloud Computer (SCC) many-core, the Intel Core i7 general-purpose multi-core, the Intel Atom low-power processor, and the Nvidia ION2 GPGPU. Our results show that the GPGPU has outstanding results in performance, power consumption and energy efficiency for many applications, but it requires significant programming effort and is not general enough to show the same level of efficiency for all the applications. The "light-weight" many-core presents an opportunity for better performance per watt over the "heavy-weight" multi-core, although the multi-core is still very effective for some sophisticated applications. In addition, the low-power processor is not necessarily energy-efficient, since the runtime delay effect can be greater than the power savings.
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