Optimized parallel distribution load flow solver on commodity multi-core CPU

Solving a large number of load flow problems quickly is required for Monte Carlo analysis and various power system problems, including long term steady state simulation, system benchmarking, among others. Due to the computational burden, such applications are considered to be time-consuming, and infeasible for online or realtime application. In this work we developed a high performance framework for high throughput distribution load flow computation, taking advantage of performance-enhancing features of multi-core CPUs and various code optimization techniques. We optimized data structures to better fit the memory hierarchy. We use the SPIRAL code generator to exploit inherent patterns of the load flow model through code specizlization. We use SIMD instructions and multithreading to parallelize our solver. Finally, we designed a Monte Carlo thread scheduling infrastructure to enable real time operation. The optimized solver is able to achieve more than 50% of peak performance on a Intel Core i7 CPU, which translates to solving millions of load flow problems within a second for IEEE 37 test feeder.