Abstract: An apparatus, one or more computer readable media, a distributed edge computing system, and a method. The apparatus includes one or more processors to determine dependencies between sets of tasks of a plurality of tasks to be executed by a plurality of cores of a network; determine latency deadlines of respective ones of the plurality of tasks; and determine an allocation of individual ones of the plurality of among the plurality of cores for execution based on the dependencies and based on the latency deadlines.

Abstract: A method, system, and apparatus are provided for computing soft bits in a non-linear MIMO detector which decodes a signal received at a plurality of receive antennas using channel estimate information and a decoding tree to produce output data for a bit estimation value which includes a maximum likelihood solution along with a naturally ordered vector identifying all explored node metrics and node indices, where soft bits are computed for each bit estimation value by determining a set of bit-masks through repetition and indexing operations applied on the explored node indices, masking the naturally ordered vector with the set of bit-masks to generate masked node metrics, determining candidate soft bit values by subtracting metrics of all nodes that form the maximum likelihood solution from the masked node metrics, and determining a final soft bit value by identifying which of the candidate soft bit values has a lowest value.

Abstract: A method, system, and apparatus are provided for computing soft bits in a non-linear MIMO detector which decodes a signal received at a plurality of receive antennas using channel estimate information and a decoding tree to produce output data for a bit estimation value which includes a maximum likelihood solution along with a naturally ordered vector identifying all explored node metrics and node indices, where soft bits are computed for each bit estimation value by determining a set of bit-masks through repetition and indexing operations applied on the explored node indices, masking the naturally ordered vector with the set of bit-masks to generate masked node metrics, determining candidate soft bit values by subtracting metrics of all nodes that form the maximum likelihood solution from the masked node metrics, and determining a final soft bit value by identifying which of the candidate soft bit values has a lowest value.