14:30
The standard rounding procedure in floating-point computations is round to nearest (RN). In this talk we consider an alternative rounding strategy called stochastic rounding (SR) which has the appealing property of being exact (actually exact!) in expectation. In the first part of the talk we discuss recent developments in probabilistic rounding error analysis and we show how rounding errors grow at an O(\sqrt{n}) rate rather than O(n) when SR is employed. This shows that Wilkinson's rule of thumb provably holds for this type of rounding. In the second part of the talk we consider the application of SR to parabolic PDEs admitting a steady state solution. We show that when the heat equation is solved in half precision RN fails to compute an accurate solution, while SR successfully solves the problem to decent accuracy.