Input

As computing systems become increasingly complex and concurrent, performance analysis becomes more important, especially when designing overall archi-tecture. Simple numerical approximations can of-ten yield bounds on performance. Queueing theory and Markovian analysis can provide insight into the steady-state performance of the system. Discrete-event simulation can provide a more detailed view of the system behavior. We used all of the above tech-niques in the performance study of a Fibre Channel switch. An approximate stochastic Petri net (SPN) model was employed, obtained by exploiting sym-metries in the system. The most challenging aspect was determining transition ring probabilities that accurately re ected the dynamic behavior of the ex-act SPN. This model was valided against a detailed simulation and found to be accurate within 3%. See [2] for details and references. 1 System description We consider a switch with N ports, numbered from 0 to N 1 (Fig. 1). The switch contains buer pools organized by input port, a router to transfer header information to output queues, and a scheduler to schedule the transfer of data from an input buer across the crossbar to an output port. When a mes-sage arrives at a port, it is read into a buer as soon as one is available. The router cyclically polls each port, bypassing ports without new messages. Dur-ing the poll of a particular port, the router reads the header information of the new message and inserts it into a scheduler table. This table is organized as N FIFO queues, one per output port. The router starts routing a message as soon as the header is i