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Heterogeneous multi-processors platforms are an interesting option to satisfy the computational performance of dynamic multi-media applications at a reasonable energy cost. Today, almost no support exists to energy-efficiently manage the data of a multi-threaded application on these platforms. In this paper we show that the assignment of data of dynamically created/deleted tasks to the shared memory has a large impact on the energy consumption. We present two dynamic memory allocators which solve the bank assignment problem for shared multi-banked SDRAM memories. Both allocators assign the tasks' data to the available SDRAM banks such that the number of page-misses is reduced. We have measured large energy savings with these allocators compared to existing dynamic memory allocators for several task-sets based on MediaBench [5].

Current main memory organizations in embedded and mobile application systems are DRAM dominated. The everincreasing gap between today's processor and memory speeds makes the DRAM subsystem design a major aspect of computer system design. However, the limitations to DRAM scaling and other challenges like refresh provide undesired trade-offs between performance, energy and area to be made by architecture designers. Several emerging NVM options are being explored to at least partly remedy this but today it is very hard to assess the viability of these proposals because the simulations are not fully based on realistic assumptions on the NVM memory technologies and on the system architecture level. In this paper, we propose to use realistic, calibrated STT-MRAM models and a well calibrated cross-layer simulation and exploration framework, named SEAT, to better consider technologies aspects and architecture constraints. We will focus on general purpose/mobile SoC multicore architectures. We will highlight results for a number of relevant benchmarks, representatives of numerous applications based on actual system architecture. The most energy efficient STT-MRAM based main memory proposal provides an average energy consumption reduction of 27% at the cost of 2x the area and the least energy efficient STT-MRAM based main memory proposal provides an average energy consumption reduction of 8% at the around the same area or lesser when compared to DRAM.