Enabling lock-free concurrent workers over temporal graphs composed of multiple time-series

Time series are commonly used to store temporal data, e.g., sensor measurements. However, when it comes to complex analytics and learning tasks, these measurements have to be combined with structural context data. Temporal graphs, connecting multiple time-series, have proven to be very suitable to organize such data and ultimately empower analytic algorithms. Computationally intensive tasks often need to be distributed and parallelized among …