Commercial-off-the-shelf (COTS) platforms feature several cores that share and contend for memory resources. In real-time system applications, it is of paramount importance to correctly estimate tight upper bounds to the delays due to memory contention. However, without proper support from the hardware (e.g. a real-time bus scheduler), it is difficult to estimate such upper bounds. This work aims at avoiding contention for a set of tasks modeled using the Predictable Execution Model (PREM), i.e. each task execution is divided into a memory phase and a computation phase, on a hardware multicore architecture where each core has its private scratchpad memory and all cores share the main memory. We consider non-preemptive scheduling for memory phases, whereas computation phases are scheduled using partitioned preemptive EDF. In this work, we propose three novel approaches to avoid contention in memory phases: (i) a task-level time-triggered approach, (ii) job-level time-triggered approach, and (iii) on-line scheduling approach. We compare the proposed approaches against the state of the art using a set of synthetic experiments in terms of schedulability and analysis time. Furthermore, we implemented the different approaches on an Infineon AURIX TC397 multicore microcontroller and validated the proposed approaches using a set of tasks extracted from well-known benchmarks from the literature.