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The Case for Cross-Component Power Coordination on Power Bounded Systems

Modern computer systems are increasingly bounded by the available or permissible power at multiple layers from components to systems. To cope with this reality, it is necessary to understand how power bounds impact the design and performance of emergent computer systems. Prior work mainly focuses on power capping and budgeting on individual components without coordinating them to achieve the best possible performance. In this article, we study the problem of power bounded computing and power allocation across computer components on CPU and GPU-accelerated systems. We investigate the dynamics between cross-component power allocation and generalize the performance impacts, and propose lightweight heuristics to maximize performance. We draw multiple insights: (1) for a given application and power bound, there exists a maximum achievable performance which requires coordinated power allocation among components for balanced computation and memory access; (2) the max performance increases with the total power bound but only in a definite range specific to applications; (3) the dynamics of power allocations has categorical patterns with regard to performance trends and actual power use; and (4) the categorical patterns can be leveraged to design coordinated power allocations. These findings suggest the promises of cross-component coordination in forthcoming power bounded high performance computing.