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相关概念视频

Temperature and Thermal Equilibrium01:11

Temperature and Thermal Equilibrium

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Heat and temperature are essential concepts for everyone every day. The study of heat and temperature is part of an area of physics known as thermodynamics. It is not always easy to distinguish heat and temperature.
The concept of temperature has evolved from the common concepts of hot and cold. The scientific definition of temperature explains more than just our sense of hot and cold. Temperature is operationally defined as the quantity measured with a thermometer. Furthermore, temperature is...
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Thermal Stress01:09

Thermal Stress

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If the temperature of an object is changed while it is prevented from expanding or contracting, the object is subjected to stress. The stress is compressive if the object expands in the absence of constraint and tensile if it contracts. This stress resulting from temperature change is known as thermal stress. It can be quite large and can cause damage. To avoid this stress, engineers may design components so they can expand and contract freely. For instance, on highways, gaps are deliberately...
2.5K
Mechanisms of Heat Transfer II01:20

Mechanisms of Heat Transfer II

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In convection, thermal energy is carried by the large-scale flow of matter. Ocean currents and large-scale atmospheric circulation, which result from the buoyancy of warm air and water, transfer hot air from the tropics toward the poles and cold air from the poles toward the tropics. The Earth’s rotation interacts with those flows, causing the observed eastward flow of air in the temperate zones. Convection dominates heat transfer by air, and the amount of available space for the airflow...
4.5K
Thermal expansion and Thermal stress: Problem Solving01:27

Thermal expansion and Thermal stress: Problem Solving

2.2K
San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55...
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Temperature Dependent Deformation01:12

Temperature Dependent Deformation

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In a nonhomogeneous rod made up of steel and brass, restrained at both ends and subjected to a temperature change, several steps are involved in calculating the stress and compressive load. Due to the problem's static indeterminacy, one end support is disconnected, allowing the rod to experience the temperature change freely. Next, an unknown force is applied at the free end, triggering deformations in the rod's steel and brass portions. These deformations are then calculated and added...
743
Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

636
Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
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相关实验视频

Updated: May 6, 2026

Esophageal Heat Transfer for Patient Temperature Control and Targeted Temperature Management
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强化学习驱动的任务迁移用于3D noc系统中有效的温度管理.

Jingyi Tang1, Jun Hong2

  • 1Department of Information Engineering, Shanxi Institute of Mechanical and Electrical Engineering, Changzhi, 046011, Shanxi, China. sophia2020@163.com.

Scientific reports
|April 8, 2025
PubMed
概括

本研究介绍了一种基于强化学习的任务迁移算法,用于管理多核系统中的热问题. 该策略有效地将峰值芯片温度降低高达31%,性能影响最小.

关键词:
在芯片上的3D网络.强化学习是一种强化学习.任务迁移任务的迁移温度管理是指温度的管理.

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科学领域:

  • 计算机工程 计算机工程
  • 可靠性工程可靠性工程
  • 热管理 热管理

背景情况:

  • 多核系统由于功率密度和热点的增加而面临可靠性和性能挑战.
  • 3D堆叠通过增加芯片温度加剧了这些问题,要求先进的热管理解决方案.
  • 现有的热控制策略往往缺乏可扩展性和长期可靠性考虑.

研究的目的:

  • 为多核系统开发有效的热管理算法,专注于提高系统可靠性.
  • 为了应对热核任务迁移的挑战,使用启发式方法解决一个完整的NP问题.
  • 为了最大限度地降低芯片温度,并减轻高级计算架构中的性能退化.

主要方法:

  • 基于任务迁移的新型算法被提议用于热管理.
  • 强化学习 (RL) 被用作一种启发式方法来解决任务迁移目的地问题.
  • 该算法在选择迁移位置时考虑了核心温度和迁移开销.

主要成果:

  • 拟议的策略显著降低了芯片的最大温度,在任务负载最高的核心中降低了多达31%.
  • 任务迁移策略对系统性能的影响很小.
  • 该方法在管理高密度计算环境中的热挑战方面表现出有效性.

结论:

  • 基于强化学习的任务迁移是多核系统中热管理的可行和有效策略.
  • 该算法成功地平衡了热减少与性能保存.
  • 这种方法提供了一个可扩展的解决方案,以提高现代高性能计算系统的可靠性.