Proactive temperature management in MPSoCs

Preventing thermal hot spots and large temperature variations on the die is critical for addressing the challenges in system reliability, performance, cooling cost and leakage power. Reactive thermal management methods, which take action after temperature reaches a given threshold, maintain the temperature below a critical level at the cost of performance, and do not address the temperature variations. In this work, we propose a proactive thermal management approach, which estimates the future temperature using regression, and allocates workload on a multicore system to reduce and balance the temperature to avoid temperature induced problems. Our technique reduces the hot spots and temperature variations significantly in comparison to reactive strategies.