Algorithms for Optimally Arranging Multicore Memory Structures
As more processing cores are added to embedded systems processors, the relationships between cores and memories have more influence on the energy consumption of the processor. In this paper, the authors conduct fundamental research to explore the effects of memory sharing on energy in a multicore processor. They study the Memory Arrangement (MA) Problem. They prove that the general case of MA is NP-complete. They present an optimal algorithm for solving linear MA and optimal and heuristic algorithms for solving rectangular MA. On average, they can produce arrangements that consume 49% less energy than an all shared memory arrangement and 14% less energy than an all private memory arrangement for randomly generated instances.