Virtually all real-valued computations are carried out using floating-point data types and
operations. The precision of these data types must be set with the goals of reducing the …

HPC applications use floating point arithmetic operations extensively to solve computational
problems. Mixed-precision computing seeks to use the lowest precision data type that is …

This paper aims to take stock of recent advances in the field of energy-quality (EQ) scalable
circuits and systems, as promising direction to continue the historical exponential energy …

Mixed-precision approaches can provide substantial speed-ups for both computing-and
memory-bound codes with little effort. Most scientific codes have overengineered the …

This paper describes the rpe (reduced-precision emulator) library which has the capability to
emulate the use of arbitrary reduced floating-point precision within large numerical models …

With the ever-increasing need for computation of scientific applications, new application
domains, and major energy constraints, the landscape of floating-point computation is …

The type length chosen for floating-point numbers (eg 32 bits or 64 bits) may have an impact
on the execution time, especially on SIMD (Single Instruction Multiple Data) units …

With the increasing interest in applying approximate computing to HPC applications,
representative benchmarks are needed to evaluate and compare various approximate …

Mixed-precision computing offers potential data size reduction and performance
improvement at the cost of accuracy, a tradeoff that many practitioners in high-performance …

The growing demands of the worldwide IT infrastructure stress the need for reduced power
consumption, which is addressed in so-called transprecision computing by improving …