Abstract:

Of the many ways one could gauge the complexity-effectiveness of a design or design element, one candidate approach is to consider a design's power/performance tradeoffs. This paper describes our early-stage results in a broad effort to evaluate the power-performance tradeoffs of a range of benchmarks and microarchitectures. In particular, this paper presents power data collected on-the-fly on real x86 machines as they execute carefully-constructed microbenchmarks. The microbenchmarks exercise aspects of the system such as data cache and branch predictor. They are parametrically-variable to consider how load dependence, cache miss rate, branch mispredict rate, and branch distance all impact the power and performance of a CPU. For example, from these experiments, we learn that CPU performance increases essentially monotonically with cache hit rate, while CPU power encounters a maximum at roughly 80-90% cache hit rates. Likewise, we show results demonstrating that performance-neutral issues such as bit populations in the data cache values can display interesting power trends. While the experimental results are preliminary, we feel that the techniques described in this paper will o er a useful foundation for a broad range of power/performance tradeoffs.