The use of reduced precision to improve performance metrics such as computation latency
and power consumption is a common practice in the embedded systems field. This practice …

In modern low-power embedded platforms, the execution of floating-point (FP) operations
emerges as a major contributor to the energy consumption of compute-intensive …

In recent years approximate computing has been extensively explored as a paradigm to
design hardware and software solutions that save energy by trading off on the quality of the …

A mixed-precision program is a floating-point program that utilizes different precisions for
different operations, providing the opportunity of balancing the trade-off between accuracy …

This article presents GRAM (G PU-based R untime A daption for M ixed-precision) a
framework for the effective use of mixed precision arithmetic for CUDA programs. Our …

Direct computation of functions using low-complexity algorithms can be applied both for
hardware constraints and in systems where storage capacity is a challenge for processing a …

Neural networks can be costly in terms of memory and execution time. Reducing their cost
has become an objective, especially when integrated in an embedded system with limited …

Precision tuning or customized precision number representations is emerging, in these
recent years, as one of the most promising techniques that make it possible to save the …

Efficient numerical programs are required for proper functioning of many systems. Today's
tools offer a variety of optimizations to generate efficient floating-point implementations that …

Floating-Point Units (FPUs) count as a significant part of computing resources in modern
general-purpose and application-specific processors. Full-precision FPUs can be a source …