Performance evaluation of concurrently executing parallel applications on multi-processor systems

Multiprocessors are increasingly being used in modern embedded systems for reasons of power and speed. These systems have to support a large number of applications and standards, in different combinations, called use-cases. The key challenges are designing efficient systems handling all these use-cases; this requires fast exploration of software and hardware alternatives with accurate performance evaluation. In this paper, we present a system level FPGA based simulation methodology for performance evaluation of applications on multiprocessor platforms. We observe that for multiple applications sharing an MPSoC platform, dynamic arbitration can cause deadlock in simulation. We use conservative parallel discrete event simulation (PDES) for simulation of these use-cases. We further note that conservative PDES is inefficient so we present a new PDES methodology that avoids causality errors by detecting them in advance. We call our new approach as smart conservative PDES. It is scalable in the number of use-cases and number of simulated processors and is 15% faster than conservative PDES. We further present results of a case-study of two real life applications. We used our simulation technique to do a design space exploration for optimal buffer space for JPEG and H263 decoders.