Standard benchmarking provides the run times for given programs on given machines, but fails to provide insight as to why those results were obtained (either in terms of machine or program characteristics), and fails to provide run times for that program on some other machine, or some other programs on that machine. We have developed a machineindependent model of program execution to characterize both machine performance and program execution. By merging these machine and program characterizations, we can estimate execution time for arbitrary machine/program combinations. Our technique allows us to identify those operations, either on the machine or in the programs, which dominate the benchmark results. This information helps designers in improving the performance of future machines, and users in tuning their applications to better utilize the performance of existing machines. Here we apply our methodology to characterize benchmarks and predict their execution times. We present extensi...

In previous research, we have developed and presented a model for measuring machines and analyzing programs, and for accurately predicting the running time of any analyzed program on any measured machine. That work is extended here by: (a) developing a high level program to measure the design and performance of the cache and TLB for any machine; (b) using those measurements, along with published miss ratio data, to improve the accuracy of our run time predictions; (c) using our analysis tools and measurements to study and compare the design of several machines, with particular reference to their cache and TLB performance. As part of this work, we describe the design and performance of the cache and TLB for ten machines. The work presented in this paper extends a powerful technique for the evaluation and analysis of both computer systems and their workloads; this methodology is valuable both to computer users and computer system designers. 1. Introduction The performance of a computer ...