A. Teymouri - Nano-Electronics Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
H. Dorosti - Department of Computer Systems Architecture, Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
M. Ersali Salehi Nasab - Nano-Electronics Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
S.M. Fakhraie - Nano-Electronics Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.

kground and Objectives: The future demands of multimedia and signal processing applications forced the IC designers to utilize efficient high performance techniques in more complex SoCs to achieve higher computing throughput besides energy/power efficiency improvement. In recent technologies, variation effects and leakage power highly affect the design specifications and designers need to consider these parameters in design time. Considering both challenges as well as boosting the computation throughput makes the design more difficult.Methods: In this article, we propose a simple serial core for higher energy/power efficiency and also utilize data level parallel structures to achieve required computation throughput.Results: Using the proposed core we have ۳۵% (۷۵%) energy (power) improvement and also using parallel structure results in ۸x higher throughput. The proposed architecture is able to provide ۷۶ MIPS computation throughput by consuming only ۲.۷ pj per instruction. The outstanding feature of this processor is its resiliency against the variation effects.Conclusion: Simple serial architecture reduces the effect of variations on design paths, furthermore, the effect of process variation on throughput loss and energy dissipation is negligible and almost zero. Proposed processor architecture is proper for energy/power constrained applications such as internet of things (IoT) and mobile devices to enable easy energy harvesting for longer lifetime.

Massive Parallel Processing, SSTA, ultra-low-energy, Variation-aware, High-throughput