1、Simulation results show that the algorithm can achieve more stable clustering accuracy on the benchmark data sets.
2、Your hardware vendor should have benchmark data stating the expected Memory, CPU (FLOPS), Disk, and Network performance.
3、The performance of multifrontal method is evaluated and compared with direct sparse factorization method through load flow calculation and transient stability simulation using IEEE benchmark data.
4、Although this is a sizing example, IBM sizing tools rely not only on the derived benchmark data, but also on analysis and feedback from both customer and internal production environments.
