Core mapping, in which a core graph is mapped to a network graph to minimize communication, is a common design problem for Systems-on-Chip interconnected by a Network-on-Chip. In conventional multiprocessors, this mapping is area-agnostic as the cores in the core graph are uniform and therefore iso-area. This changes for Systems-on-Chip because tasks are mapped to specific blocks and not general-purpose cores. Thus, the area of these specific cores is varying. This requires novel mapping methods. In this paper, we propose a an area-aware cost function for simulated annealing; Furthermore, we advocate the use of nonlinear models as the area is nonlinear: A semi-definite program (SDP) can be used as it is sufficiently fast and shows 20% better area than conventional linear models. Our cost function allows for up to 16.4% better area, 2% better communication (bandwidth times hop distance) and 13.8% better total bandwidth in the network in comparison to the standard approach that accounts for both the network communication and uses cores with varying areas as well.
Spin Torque Transfer Magnetic RAM (STT-MRAM) is a promising Non-Volatile Memory (NVM) technology achieving high density, low leakage power, and relatively small read/write delays. It provides a solution to improve the performance and to mitigate the leakage power consumption compared to SRAM-based processors. However, the process heterogeneity and the sophisticated back-end-of-line (BEOL) structure make it difficult to integrate the STT-MRAM in two-dimensional integrated circuits (2D ICs). In this paper, we implement a RISC-V-based processor with STT-MRAM using a heterogeneous 3D integration methodology. Compared with the SRAM-based 2D counterpart, the MRAM-based 3D IC provides up to 17.55% silicon area saving, together with either 34.74% performance gain or 13.90% energy reduction.
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