Paper Info
Title
Reducing Energy Consumption of Data Transfers Using Runtime Data Type Conversion.
Abstract
Reducing the energy consumption of todayu0027s microprocessors, for which Approximate Computing AC is a promising candidate, is an important and challenging task. AC comprises approaches to relax the accuracy of computations in order to achieve a trade-off between energy efficiency and an acceptable remaining quality of the results. A high amount of energy is consumed by memory transfers. Therefore, we present an approach in this paper that saves energy by converting data before transferring it to memory. We introduce a static approach that can reduce the energy upi¾źto a factor of 4. We evaluate different methods to get the highest possible accuracy for a given data width. Extending this approach by a dynamic selection of different storage data types improves the accuracy for a 2D Fast Fourier Transformation by two orders of magnitude compared to the static approach using 16-bit data types, while still retaining the reduction in energy consumption. First results show that such a conversion unit can be integrated in low power processors with negligible impact on the power consumption.
Year
Venue
Field
2016
ARCS
Computer science,Efficient energy use,Real-time computing,Fast Fourier transform,Data type,Energy consumption,Order of magnitude,Approximate computing,Power consumption,Computation
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
10
3
Name
Order
Citations
PageRank
Michael Bromberger142.11
Vincent Heuveline217930.51
Wolfgang Karl3466.44