Actuarial cycle time
Summary
The ongoing COVID-19 pandemic has introduced millions of ordinary people to some basic aspects of epidemiology, such as the R number to measure the reproductive ability of a virus. The very short cycle time of the Delta variant makes it a very productive virus indeed, as demonstrated in an earlier blog. Nowadays the answer lies in parallel computing; ignoring the overhead of setting up the calculations, doubling the number of executing CPU threads can halve the time it takes to get your results. There are many levels to program optimisation, and it is usually a separate stage of software maturation as it requires a different mindset and skills from the original development. To pick a recent example here at Longevitas, consider the following summation for modelling mortality shocks in portfolio data: where \(B_j(y)\) is the \(j^{\rm th}\) \(B\)-spline evaluated at time \(y\), and \(\kappa_{0,j}\) is the coefficient of \(B_j\).
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