Multi-Objective Optimization for Floating Point Mix-Precision Tuning

This paper proposes a multi-objective optimization method for mixed-precision computation. Unlike previous studies that often take mantissa length reduction as the only optimization target, our work models the actual performance and power consumption of mixed precision programs on the corresponding hardware platforms, and based on this model searches for the pareto optimal set of all precision configurations. Experiments show that this tool can obtain performance improvements of 15% - 71 % on floating-point benchmarks while satisfying accuracy requirements. Compared to some typical counterpart-work, an average 21 % improvement can be obtained in SIMD scenarios.