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

随着计算能力的增长和计算变得越来越任务并行，许多小任务将共同位于几台大机器上。没有一个计算任务可以完全利用机器的资源，但是当机器通电时，所有这些资源都变得可用。这种不匹配导致了众所周知的能源不稳定性问题，当服务器未得到充分利用时，其固定电力成本将在很少的工作中摊销。管理任务协同定位以确保性能，提高电源效率，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手中？公地的定义。一个公共空间是一个由一组代理共同使用的技术，公共空间的问题是组织共同开发这项技术。通过将共享的硬件架构映射到这个问题公式中，研究人员调整系统管理机制以适应战略用户行为。这种微观经济学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措施。研究人员致力于整合研究和教育。成功包括对节能计算课程的强有力的教学评估，以及快速培养计算基础知识背景较弱的硕士生的课程。成功还包括促进本科生和代表性不足的少数民族参与研究。研究人员研究了用于协同定位任务和减轻共享高性能硬件架构的战略用户之间的竞争的博弈论机制。首先，这些机制估计性能推断的统计模型引起的用户争用罚款？行为组合。然后，这些机制属性的惩罚任务，通过使用联盟博弈论，以确定每个任务的程度，有助于系统竞争。最后，这些机制优化了战略用户的软件协同定位，并确保博弈论的必要条件，如共享激励和公平性。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，该研究将严格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.