An integrated variation-aware mapping framework for FinFET based irregular 2D MPSoCs in the dark silicon era

Rajkrishna, Pramit, author
Pasricha, Sudeep, advisor
Jayasumana, Anura, committee member
Burns, Patrick, committee member
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In the deep submicron era, process variations and dark silicon considerations have become prominent focus areas for early stage networks-on-chip (NoC) design synthesis. Additionally, FinFETs have been implemented as promising alternatives to bulk CMOS implementations for 22nm and below technology nodes to mitigate leakage power. While overall system power in a dark silicon paradigm is governed by a limitation on active cores and inter-core communication patterns, it has also become imperative to consider process variations in a holistic context for irregular 2D NoCs. Additionally, manufacturing defects induce link failures, with resultant irregularity in the NoC topology and rendering conventional minimal routing schemes for regular topologies inoperable. In this thesis, we propose a holistic process variation aware design time synthesis framework (HERMES) that performs computation and communication mapping while minimizing energy consumption and maximizing Power Performance Yield (PPY). The framework targets a 22nm FinFET based homogenous NoC implementation with design time link failures in the NoC fabric, a dark silicon based power constraint and system bandwidth constraints for performance guarantees, while preserving connectivity and deadlock freedom in the NoC fabric. Our experimental results show that HERMES performs 1.32x better in energy, 1.29x better in simulation execution time and 58.44% better in PPY statistics, over other state-of-the-art proposed mapping techniques for various SPLASH2 and PARSEC parallel benchmarks.
2016 Spring.
Includes bibliographical references.
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networks on chip
genetic algorithm
dark silicon
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