Distributed Resource Reservation in Massively Parallel Processor Arrays

This paper proposes a methodology for applications to automatically claim linear arrays of processing elements within massively parallel processor arrays at run-time depending on the available degree of parallelism or dynamic computing requirements. Using this methodology, parallel programs running on individual processing elements gain the capability of autonomously managing the available processing resources in their neighborhood. We present different protocols and architectural support for gathering and transporting the result of a resource exploration for informing a configuration loader about the number and location of the claimed resources. Timing and data overhead cost of four different approaches are mathematically evaluated. In order to verify and compare these decentralized algorithms, a simulation platform has been developed to compare the data overhead and scalability of each approach for different sizes of processor arrays.