Benchmarking Methodology for Real-Time Embedded Scalable High Performance Computing.

This application of scalable high performance computing to real time embedded systems is expanding. Traditional benchmarks and notions of scalability drawn from the scientific parallel computing community are of limited relevance when timing requirements must be met within strict size, weight, and power requirements. This paper proposes a bench marking methodology for real time embedded applications, including a relevant notion of scalability. The essential point is to give equal emphasis to timing and functional specifications. We use a test bench on the machine itself to realistically impulse the function or system under test. Metrics that measure the steady state performance account for limitations of non real time system software. The key metric is the minimum processor size required to meet the real time specifications for a given problem size. The scalability of the embedded processor can then be characterized in terms of the rate of increase of this minimum machine size as the problem and potentially the real time requirement is scaled.