3D stacking of integrated circuits (ICs) provides significant advantages in saving device footprints, improving power management, and continuing performance enhancement, particularly for many-core systems. However, the stacked structure makes the heat dissipation a challenging issue. While Thermal Through Silicon Via (TTSV) is a promising way of lowering the thermal resistance of dies, past research has either overestimated or underestimated the effects of TTSVs as a consequence of the lack of detailed 3D IC models or system-level simulations. Here, we propose a simulation flow to accurately simulate TTSV effects on 3D ICs. We adopt benchmarks from Splash-2 running on a full-system mode of the gem5 simulator, which generates all the system component activities. McPAT is used to generate the corresponding power consumption and the power traces are fed to HotSpot for thermal simulation. The temperature profiles of 2D and 3D Nehalem-like ×86 processors are compared. TTSVs are later placed close to hotspot regions to facilitate heat dissipation; the peak temperature of 3D Nehalem is reduced by 5--25% with a small area overhead of 6%. By using a detailed 3D thermal model, full-system simulation, and a validated thermal simulator, our results show accurate thermal analysis of 3D ICs.

The movement toward 3D fabrication coupled with Network-on-Chip (NoC) aims to improve area, performance, power, and scalability of many-core systems. However, reliability issue as a perpetual challenge in advanced silicon technology imperils it. Aging is an emerging reliability concern, which degrades the system's performance and causes timing failure eventually. Bias-Temperature-Instability (BTI) and Hot-Carrier-Injection (HCI) are the dominant aging mechanisms, which escalate in high temperature and stress (i.e., usage). In addition to the intra-layer temperature variations, 3D NoCs experience inter-layer temperature variations, which demand necessary investigations for aging as compared to 2D NoC. In this paper, we propose AROMa, an aging-aware deadlock-free adaptive routing algorithm integrated with a novel online aging monitoring system for 3D NoCs. The monitoring system in AROMa exploits Distributed-Centralized-Aging-Table (D-CAT) to obtain routers' aging rates for each layer of 3D NoCs periodically. Consequently, AROMa swaps between different k-best source-destination shortest paths periodically to avoid highly aged routers, force them in recovery phase of BTI, and accordingly balance aging in the network. We prove that AROMa is deadlock free. Our extensive experimental analysis using gem5 full system mode for PARSEC and SPLASH-2 benchmark suites concludes that AROMa outperforms state-of-the-art works while improving age imbalance by 70 percent and maximum age by 35 percent in 3D NoC with negligible overheads.

Scalability of Network-on-Chip (NoC) as a promising solution for many-core systems can be jeopardized due to reliability challenges such as aging in advanced silicon technology. Previous mitigation techniques to protect NoC are either offline, while aging is strictly influenced by runtime operating conditions, or impose significant overheads to the system. This paper presents an online monitoring method through a Centralized Aging Table (CAT) for routers in NoCs. Router's capacity in flits, which are the main stimuli in routers, is predictable and limited for a given period of time. Consequently, stress rate and temperature, which are the major sources of aging mechanisms such as Bias Temperature Instability (BTI) and Hot Carrier Injection (HCI), will be in the predictable ranges, as well. Hence, our methodology uses CAT which is populated by values that represent aging degradation for each different pairs of stress and temperature ranges during a given period of time. Furthermore, utilizing CAT, we propose an online adaptive aging-aware routing algorithm in order to avoid highly aged routers which eventually leads to age balancing between routers. Additionally, our proposed routing algorithm reduces maximum age of routers by changing the shortest paths between source-destination pairs adaptively, considering routers' ages across them in each given period of time. Extensive experimental analysis using gem5 simulator demonstrates that our online routing algorithm and monitoring methodology, CAT, improves delay degradation of maximum aged router and aging imbalance on average by 39% and 52% compared to XY routing, respectively. The impact of our proposed methodology on network latency, Energy-Delay-Product (EDP) and link utilization is negligible.