Domain-specific machine learning (ML) accelerators such as Google's TPU and Apple's Neural Engine now dominate CPUs and GPUs for energy-efficient ML processing. However …
IG Thakkar, S Pasricha - IEEE Transactions on Multi-Scale …, 2018 - ieeexplore.ieee.org
Silicon nanophotonics technology is being considered for future networks-on-chip (NoCs) as it can enable high bandwidth density and lower latency with traversal of data at the speed of …
The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored …
Photonic networks-on-chip (PNoCs) enable high bandwidth on-chip data transfers by using photonic waveguides capable of dense-wave-length-division-multiplexing (DWDM) for …
Abstract Optical Network on Chip (ONoC) is now considered a promising alternative to traditional electrical interconnects. Meanwhile, several challenges such as temperature and …
The compact size and high wavelength-selectivity of microring resonators (MRs) enable photonic networks-on-chip (PNoCs) to utilize dense-wavelength-division-multiplexing …
The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored …
The performance of on-chip communication in the state-of-the-art multi-core processors that use the traditional electronic NoCs has already become severely energy-constrained. To …
In the wake of dwindling Moore's Law, to address the rapidly increasing complexity and cost of fabricating large-scale, monolithic systems-on-chip (SoCs), the industry has adopted dis …