  As the dimensions and operating voltages of computer electronics shrink to
cope with consumers' demand for higher performance and lower power consumption,
circuit sensitivity to soft errors increases dramatically. Recently, a new
data-type is proposed in the literature called posit data type. Posit
arithmetic has absolute advantages such as higher numerical accuracy, speed,
and simpler hardware design than IEEE 754-2008 technical standard-compliant
arithmetic. In this paper, we propose a comparative robustness study between
32-bit posit and 32-bit IEEE 754-2008 compliant representations. At first, we
propose a theoretical analysis for IEEE 754 compliant numbers and posit numbers
for single bit flip and double bit flips. Then, we conduct exhaustive fault
injection experiments that show a considerable inherent resilience in posit
format compared to classical IEEE 754 compliant representation. To show a
relevant use-case of fault-tolerant applications, we perform experiments on a
set of machine-learning applications. In more than 95% of the exhaustive fault
injection exploration, posit representation is less impacted by faults than the
IEEE 754 compliant floating-point representation. Moreover, in 100% of the
tested machine-learning applications, the accuracy of posit-implemented systems
is higher than the classical floating-point-based ones.
