  Silent data corruptions (SDCs) hinder the correctness of long-running
scientific applications on large scale computing systems. Selective particle
replication (SPR) is proposed herein as the first particle-based replication
method for detecting SDCs in Smoothed particle hydrodynamics (SPH) simulations.
SPH is a mesh-free Lagrangian method commonly used to perform hydrodynamical
simulations in astrophysics and computational fluid dynamics. SPH performs
interpolation of physical properties over neighboring discretization points
(called SPH particles) that dynamically adapt their distribution to the mass
density field of the fluid. When a fault (e.g., a bit-flip) strikes the
computation or the data associated with a particle, the resulting error is
silently propagated to all nearest neighbors through such interpolation steps.
SPR replicates the computation and data of a few carefully selected SPH
particles. SDCs are detected when the data of a particle differs, due to
corruption, from its replicated counterpart. SPR is able to detect many DRAM
SDCs as they propagate by ensuring that all particles have at least one
neighbor that is replicated. The detection capabilities of SPR were assessed
through a set of error-injection and detection experiments and the overhead of
SPR was evaluated via a set of strong-scaling experiments conducted on an HPC
system. The results show that SPR achieves detection rates of 91-99.9%, no
false-positives, at an overhead of 1-10%.
