  The purely numerical evaluation of multi-loop integrals and amplitudes can be
a viable alternative to analytic approaches, in particular in the presence of
several mass scales, provided sufficient accuracy can be achieved in an
acceptable amount of time. For many multi-loop integrals, the fraction of time
required to perform the numerical integration is significant and it is
therefore beneficial to have efficient and well-implemented numerical
integration methods. With this goal in mind, we present a new stand-alone
integrator based on the use of (quasi-Monte Carlo) rank-1 shifted lattice
rules. For integrals with high variance we also implement a variance reduction
algorithm based on fitting a smooth function to the inverse cumulative
distribution function of the integrand dimension-by-dimension. Additionally,
the new integrator is interfaced to pySecDec to allow the straightforward
evaluation of multi-loop integrals and dimensionally regulated parameter
integrals. In order to make use of recent advances in parallel computing
hardware, our integrator can be used both on CPUs and CUDA compatible GPUs
where available.
