Abstract
Conceptual modeling is drawing more attention among researchers from many organizations and different disciplines including high-performance low-power multicore systems. As the popularity and demand grow, more processing power is required by the mission critical systems. Several chip vendors have developed teraflop computing systems (like Intel 80-Core Research chip). Even though IBM offers the Roadrunner supercomputer, NSF and other research organization are looking for more powerful petascale computer system. In a petascale computer system, thousands to millions of processing cores are expected to work together using petabytes of memory to produce the expected performance. A high performance system like Roadrunner requires a very sophisticated power management system. No wonder, such a gigantic system costs millions of dollars. Conceptual modeling offers the opportunity to conduct research on complex and expensive systems in an inexpensive way. In this work, we address some key conceptual modeling issues and discuss a methodology to develop conceptual models of petascale computer systems. Important features of this methodology include data acquisition to improve accuracy by capturing the important details about the system under consideration and (system-to-) model abstraction to make the modeling manageable without eliminating any significant characteristics of the target system. We believe our findings help develop sound conceptual models of complex high performance petascale computer systems.