ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chip

by   Febin Sunny, et al.

The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored to improve the energy-efficiency of silicon photonic networks-on-chip (PNoCs). Silicon photonic interconnects suffer from high power dissipation because of laser sources, which generate carrier wavelengths, and tuning power required for regulating photonic devices under different uncertainties. In this paper, we propose a framework called ARXON to reduce such power dissipation overhead by enabling intelligent and aggressive approximation during communication over silicon photonic links in PNoCs. Our framework reduces laser and tuning-power overhead while intelligently approximating communication, such that application output quality is not distorted beyond an acceptable limit. Simulation results show that our framework can achieve up to 56.4 better energy-efficiency than the best-known prior work on approximate communication with silicon photonic interconnects and for the same application output quality.



There are no comments yet.


page 3

page 5

page 9

page 11

page 12

page 14


LORAX: Loss-Aware Approximations for Energy-Efficient Silicon Photonic Networks-on-Chip

The approximate computing paradigm advocates for relaxing accuracy goals...

Invocation-driven Neural Approximate Computing with a Multiclass-Classifier and Multiple Approximators

Neural approximate computing gains enormous energy-efficiency at the cos...

Modeling Silicon-Photonic Neural Networks under Uncertainties

Silicon-photonic neural networks (SPNNs) offer substantial improvements ...

GPU Computing with Python: Performance, Energy Efficiency and Usability

In this work, we examine the performance, energy efficiency and usabilit...

Architectural exploration of heterogeneous memory systems

Heterogeneous systems appear as a viable design alternative for the dark...

Energy Efficiency Analysis of Intelligent Reflecting Surface System with Hardware Impairments

Recently, as explosive growth of mobile data traffic, the performance of...

The Case for Approximate Intermittent Computing

We present the concept of approximate intermittent computing and demonst...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.