Study on Thermally Constrained Task Scheduling in Homogeneous 3D Multi-Core Processors
|關鍵字:||三維多核心處理器;任務排程;熱點;動態電壓頻率調節;特徵選擇;支持向量機器學習;3D multi-core processors;task scheduling;hotspots;dynamic voltage and frequency scaling;feature selection;support-vector machine|
The implementation of chip designs in three dimensions (3D) offers several advantages over traditional two-dimensional chip implementation, such as shorter interconnect delays and better performance. 3D multi-core processors (3D-MCPs) have the potential to significantly improve system performance, but they are more likely to exhibit severe thermal problems due to their high power density and lack of heat dissipation paths. The thermal challenges in 3D-MCPs require a joint assessment of performance, energy, and temperature trade-offs. This thesis consisting of an off-line work and an on-line work focuses on optimizing the system performance, energy efficiency, and temperature of 3D-MCPs. The performance, power, and thermal behaviors of the 3D-MCPs are modeled to analyze how voltage-and-frequency assignments impact the thermal control. Moreover, novel OS-level task-scheduling algorithms for 3D-MCPs to optimize the performance and energy under thermal constraints are proposed. First, a novel architecture-level algorithm to control over-heating and large temperature variations while optimizing the system performance and minimizing energy consumption is proposed in the off-line work. A key challenge in 3D technology is that too much heat is generated from the internal active layers because the power density per unit volume is drastically increased in 3D-MCPs. Additionally, 3D-MCPs consume much more energy, which complicates low-power design implementations. To handle the severe thermal problem and energy consumption issue in 3D-MCPs, architecture-level solutions to optimize the system performance and minimize energy consumption in 3D-MCPs under thermal constraints are implemented. More specifically, the unique thermal behaviors in 3D-MCPs are studied and a novel layer-by-layer task-to-core mapping strategy to balance the temperatures among the cores in 3D-MCPs is developed. To further optimize the performance optimization and minimize the energy consumption, a thermal-and-energy-aware voltage scaling strategy is proposed to control thermal emergencies in 3D-MCPs. Second, our work is further implemented in on-line 3D-MCP systems by proposing an on-line task scheduler with a machine-learning model to dynamically assign operating voltages and frequencies to control temperature increase and improve system performance. Mitigation of the thermal issue by utilizing machine learning techniques to identify regions of temperature increase curves is developed in the on-line work. Two different thermal regions of 3D-MCPs are discovered and different key features of these regions are extracted. A machine-learning model with these key features to predict the thermal behavior and the best operation mode of 3D-MCPs is built. This work breaks away from the common assumption of initially static operation modes in 3D-MCP systems and to develop pre-emptively dynamic operation-mode assignment with machine-learning models to handle thermal issues and optimize system performance. Furthermore, a new vertical-grouping voltage scaling (VGVS) strategy that considers thermal correlation in 3D-MCPs is used to handle thermal emergencies. The experimental results demonstrated that the proposed on-line task scheduler reduced hotspot occurrences by over 50%, improved performance by 30% and saved energy by 40% in 3D-MCPs. The thesis focuses on the study to mitigate the thermal and energy issues associated with 3D-MCPs. The unique thermal behaviors of 3D-MCPs are extensively analyzed and both off-line and on-line architecture-level solutions to effectively control thermal issues while optimizing throughput and energy consumption are developed. This study increases the understanding of the thermal behaviors of 3D-MCPs under different operation modes, allowing increased control of thermal issues. As a result, the proposed design techniques successfully suppress hotspot occurrences, optimize system performance, and minimize energy consumption for 3D-MCPs under thermal constraints.
|Appears in Collections:||Thesis|