SHF: Small: Coalitional Game Theory for Co-Locating Software on Shared Hardware

随着计算能力的增长和计算任务的并行化，许多小型任务将在几台大型机器上共同定位。没有一个单一的计算任务可以完全利用机器的资源，但是当机器上电时，所有这些资源都可用。这种不匹配导致了众所周知的能量不成比例问题，当服务器未充分利用时，其固定的电力成本被分摊到很少的工作上。管理任务协同定位以确保性能、提高电源效率和激励战略用户的期望行为需要新的视角。计算资源越来越落入经济学家手中？公地的定义。公共资源是由一组主体共同使用的技术，公共资源的问题是组织对该技术的共同利用。通过将共享硬件架构映射到这个问题表述中，研究人员调整系统管理机制以适应战略性用户行为。这种微观经济的观点导致了鼓励用户采用云计算以获得更高性能和效率的激励。研究人员致力于将研究和教育结合起来。成功之处包括对节能计算课程进行强有力的教学评估，以及让计算机基础基础较弱的硕士学生迅速做好准备的课程。成功之处还包括促进本科生和未被充分代表的少数族裔参与研究。研究人员研究了共享高性能硬件架构的战略用户之间共同定位任务和缓解竞争的博弈论机制。首先，这些机制通过推断由用户产生的争用惩罚的统计模型来估计性能。行为的组合。然后，这些机制通过使用联合博弈论来确定每个任务对系统争用的贡献程度，从而将惩罚归因于任务。最后，这些机制优化了战略用户的软件共置，并确保了博弈论的期望，如共享激励和公平。该项目是跨学科的，将以前在计算机体系结构、资源管理和算法经济学方面的不同研究联系起来。该研究利用严格的分析框架来推理共享系统中的用户交互及其对整体系统结果的贡献。此外，该研究将严谨性转化为系统管理和任务协同定位的操作机制。

As computing capability grows and computation becomes increasingly task parallel, many small tasks will co-locate on a few big machines. No single computational task can utilize a machine's resources completely, yet all of these resources become available when a machine is powered up. This mismatch leads to the well-known problem of energy disproportionality, when a server is under-utilized and its fixed power costs are amortized over little work. Managing task co-location to ensure performance, to improve power efficiency, and to incentivize desired behavior from strategic users requires new perspectives. Computing resources increasingly fall into economists? definition of a commons. A commons is a technology used jointly by a set of agents and the problem of the commons is to organize the joint exploitation of this technology. By mapping shared hardware architectures into this problem formulation, the investigators adapt systems management mechanisms to accommodate strategic user behavior. This microeconomic perspective leads to incentives that encourage users to adopt cloud computing for greater performance and efficiency.The investigators are committed to integrating research and education. Successes include strong teaching evaluations for classes in energy-efficient computing and classes that rapidly prepare Masters students with weaker backgrounds in computing fundamentals. Successes also include fostering research participation from undergraduates and under-represented minorities. The investigators study game-theoretic mechanisms for co-locating tasks and mitigating contention between strategic users who share high-performance hardware architectures. First, these mechanisms estimate performance by inferring statistical models for contention penalties that arise from users? behavior combinations. Then, these mechanisms attribute penalties to tasks by using coalitional game theory to determine the extent that each task contributes to system contention. Finally, these mechanisms optimize software co-location for strategic users and ensure game-theoretic desiderata, such as sharing incentives and fairness. The project is interdisciplinary, linking previously disparate studies in computer architecture, resource management, and algorithmic economics. The research draws on rigorous, analytical frameworks to reason about users' interactions within shared systems and their contributions to overall system outcomes. Moreover, the research translates rigor into operational mechanisms for systems management and task co-location.