A Simulation Methodology for Reliability Analysis in Multi-Core SoCs

Reliability has become a significant challenge for system design in new process technologies. Higher integration levels dramatically increase power densities, which leads to higher temperature and adverse effects on reliability. In this paper, we introduce a simulation methodology to analyze reliability of multi-core SoCs. The proposed simulator is the first to provide system-on-chip level fine-grained reliability analysis. We use our simulation methodology to study the reliability effects of design choices such as thermal packaging and placement, as well as runtime events such as power management policies and workload distributions

Proactive temperature balancing for low cost thermal management in MPSoCs

Abstract — Designing thermal management strategies that reduce the impact of hot spots and on-die temperature variations at low performance cost is a very significant challenge for multiprocessor system-on-chips (MPSoCs). In this work, we present a proactive MPSoC thermal man-agement approach, which predicts the future temperature and adjusts the job allocation on the MPSoC to minimize the impact of thermal hot spots and temperature variations without degrading performance. In addition, we implement and compare several reactive and proactive management strategies, and demonstrate that our proactive temperature-aware MPSoC job allocation technique is able to dramatically reduce the adverse effects of temperature at very low performance cost. We show experimental results using a simulator as well as an implementation on an UltraSPARC T1 system. I

Power-aware scheduling and dynamic voltage setting for tasks running on a hard real-time system

Abstract- This paper addresses the problem of minimizing energy consumption of a computer system performing periodic hard real-time tasks with precedence constraints. In the proposed approach, dynamic power management and voltage scaling techniques are combined to reduce the energy consumption of the CPU and devices. The optimization problem is first formulated as an integer programming problem. Next, a three-phase solution framework, which integrates power management scheduling and task voltage assignment, is proposed. Experimental results show that the proposed approach outperforms existing methods by an average of 18 % in terms of the system-wide energy savings. I