Extending Amdahl's Law for Heterogeneous Computing

Energy will be a major limiting factor in future multi-core architectures, so optimizing performance per watt should be a key driver for next generation massive-core architectures. Recent studies show that heterogeneous chips integrating different core architectures, such as CPU and GPU, on a single die is the most promising solution. We investigated how energy efficiency and scalability are affected by the power constraints imposed on contemporary hybrid CPU-GPU processors. Analytical models were developed to extend Amdahl's Law by accounting for energy limitations before examining the three processing modes available to heterogeneous processors, i.e., symmetric, asymmetric, and simultaneous asymmetric. The analysis shows clearly that greater parallelism is the most important factor affecting power consumption.