Customizing the precision of data can provide attractive trade-offs between accuracy and hardware resources. We propose a novel form of vector computing aimed at arrays of custom-precision floating point data. We represent these vectors in bitslice format. Bitwise instructions are used to implement arithmetic circuits in software that operate on customized bit-precision. Experiments show that this approach can be efficient for vectors of low-precision custom floating point types, while providing arbitrary bit precision.
@article{arxiv.1602.04716,
title = {Customizable Precision of Floating-Point Arithmetic with Bitslice Vector Types},
author = {Shixiong Xu and David Gregg},
journal= {arXiv preprint arXiv:1602.04716},
year = {2016}
}