  Online and Real-time Object Tracking is an interesting workload that can be
used to track objects (e.g., car, human, animal) in a series of video sequences
in real-time. For simple object tracking on edge devices, the output of object
tracking could be as simple as drawing a bounding box around a detected object
and in some cases, the input matrices used in such computation are quite small
(e.g., 4x7, 3x3, 5x5, etc). As a result, the amount of actual work is low.
Therefore, a typical multi-threading based parallelization technique can not
accelerate the tracking application; instead, a throughput based
parallelization technique where each thread operates on independent video
sequences is more rewarding. In this paper, we share our experience in
parallelizing a Simple Online and Real-time Tracking (SORT) application on
shared-memory multicores.
