Title :
Comparing the power and performance of Intel´s SCC to state-of-the-art CPUs and GPUs
Author :
Totoni, Ehsan ; Behzad, Babak ; Ghike, Swapnil ; Torrellas, Josep
Author_Institution :
Dept. of Comput. Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
Power dissipation and energy consumption are becoming increasingly important architectural design constraints in different types of computers, from embedded systems to large-scale 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.
Keywords :
computer architecture; energy conservation; energy consumption; graphics processing units; multiprocessing systems; performance evaluation; CPU; Intel SCC; Intel atom low-power processor; Intel core i7 general-purpose multicore; Intel single-chip cloud computer many-core; Nvidia ION2 GPGPU; architectural design constraint; embedded systems; energy consumption; energy efficiency; large-scale supercomputers; many-core architecture; parallel processor chips; power dissipation; scalable application; Computer architecture; Energy consumption; Graphics processing unit; Jacobian matrices; Power demand; Tiles; Transistors;
Conference_Titel :
Performance Analysis of Systems and Software (ISPASS), 2012 IEEE International Symposium on
Conference_Location :
New Brunswick, NJ
Print_ISBN :
978-1-4673-1143-4
Electronic_ISBN :
978-1-4673-1145-8
DOI :
10.1109/ISPASS.2012.6189208