Bitslice Vectors: A Software Approach to Customizable Data Precision on Processors with SIMD Extensions
Shixiong Xu, David P. Gregg · 2017
Customizing the precision of data can provide attractive trade-offs between accuracy and hardware resources. Custom hardware and FPGA designs allow bit-level control over precision, but software is typically limited by the range of types supported by the underlying processor. We propose a new form of vector computing aimed at arrays of custom-precision data on general-purpose processors with SIMD extensions. We represent these vectors in bitslice format and use bitwise instructions to build arithmetic operators that operate on the customized bit precision. We construct a domain-specific code generator that builds bit-level customizable floating-point and integer operators for our vector types. Using a hardware circuit optimization tool we optimize our logical expressions, and synthesize fast software arithmetic operators for bitslice vector types. We evaluate the resulting code and find that advanced logic optimization significantly improves performance. Experiments on a platform with Intel AVX2 SIMD extensions show that this approach is efficient for vectors of low-precision custom floating-point types, while providing arbitrary bit precision.