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并行性的提高，许多小任务将在几台大机器上共存。没有一个单一的计算任务可以完全利用机器的资源，但是当机器通电时，所有这些资源都是可用的。这种不匹配导致了众所周知的能源不均衡问题，即服务器未得到充分利用，其固定电力成本在很少的工作中摊销。管理任务托管以确保性能、提高能效并激励战略用户的期望行为需要新的视角。计算资源越来越多地落入经济学家之手？公地的定义。公地是由一组智能体联合使用的技术，公地的问题是组织对这项技术的联合开发。通过将共享硬件体系结构映射到这个问题表述中，调查人员调整了系统管理机制，以适应战略用户行为。这种微观经济观点促使用户采用云计算，以获得更高的性能和效率。研究人员致力于将研究和教育结合起来。成功的课程包括对节能计算课程进行强有力的教学评估，以及为计算机基础背景较弱的硕士学生迅速做好准备的课程。成功还包括培养本科生和代表性不足的少数群体参与研究。研究人员研究了用于共同分配任务和缓解共享高性能硬件架构的战略用户之间的争用的博弈论机制。首先，这些机制通过推断用户引起的争用惩罚的统计模型来估计性能？行为组合。然后，这些机制通过联盟博弈理论将惩罚归因于任务，以确定每个任务对系统争用的贡献程度。最后，这些机制优化了战略用户的软件协同配置，并确保了共享激励和公平等博弈论期望。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在一起。这项研究借鉴了严格的分析框架，以推断用户在共享系统中的交互及其对整体系统结果的贡献。此外，这项研究还将严谨转化为系统管理和任务协同分配的操作机制。

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.