Browsing by Issue Date, starting with "2022-08-23"
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- IPDeN: Real-Time deflection-based NoC with in-order flits deliveryPublication . Ribot González, Yilian; Nelissen, Geoffrey; Tovar, EduardoIn deflection-based Network-on-Chips (NoC), when several flits entering a router contend for the same output port, one of the flits is routed to the desired output and the others are deflected to alternatives outputs. The approach reduces power consumption and silicon footprint in comparison to virtual channels (VCs) based solutions. However, due to the nondeterministic number of deflections that flits may suffer while traversing the network, flits may be received in an out-of-order fashion at their destinations. In this work, we present IPDeN, a novel deflectionbased NoC that ensures in-order flit delivery. To avoid the use of costly reordering mechanisms at the destination of each communication flow, we propose a solution based on a single small buffer added to each router to prevents flits from over taking other flits belonging to the same communication flow. We also develop a worst-case traversal time (WCTT) analysis for packets transmitted over IPDeN. We implemented IPDeN in Verilog and synthesized it for an FPGA platform. We show that a router of IPDeN requires "483-times less hardware resources than routers that use VCs. Experimental results shown that the worst-case and average packets communication time is reduced in comparison to the state-of-the-art
- Analyzing Fixed Task Priority Based Memory Centric Scheduler for the 3-Phase Task ModelPublication . Arora, Jatin; Rashid, Syed Aftab; Maia, Cláudio; Tovar, EduardoThe sharing of main memory among concurrently executing tasks on a multicore platform results in increasing the execution times of those tasks in a non-deterministic manner. The use of phased execution models that divide the execution of tasks into distinct memory and execution phase(s), e.g., the PRedictable Execution Model (PREM) and the 3-Phase task model, along with Memory Centric Scheduling (MCS) present a promising solution to reduce main memory interference among tasks. Existing works in the state-of-the-art that focus on MCS have considered (i) a TDMA based memory scheduler, i.e., tasks' memory requests are served under a static TDMA schedule, and (ii) Processor-Priority (PP) based memory scheduler, i.e., tasks' memory requests are served depending on the priority of the processor/core on which the task is executing. This paper extends MCS by considering a Task-Priority (TP) based memory scheduler, i.e., tasks' memory requests are served under a global priority order depending on the priority of the task that issues the requests. We present an analysis to bound the total memory interference that can be suffered by the tasks under the TP-based MCS. In contrast to most existing works on MCS that consider non-preemptive tasks, our analysis considers limited preemptive scheduling. Additionally, we investigate the impact of different preemption points on the memory interference of tasks. Experimental results show that our proposed TP-based MCS can significantly reduce memory interference that can be suffered by the tasks in comparison to the PP-based MCS approach.