Morteza Damavandpeyma

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Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG can be extended with scheduling decisions, allowing SDFG analysis to obtain properties like throughput or buffer sizes for the scheduled graphs. Analysis times depend strongly on the size of the SDFG. SDFGs can be statically scheduled using static-order(More)
—Dynamic behavior of streaming applications can be effectively modeled by scenario-aware dataflow graphs (SADFs). Many streaming applications must provide timing guarantees (e.g., throughput) to assure their quality-of-service. For instance, a video decoder which is running on a mobile device is expected to deliver a video stream with a specific frame rate.(More)
—Scenario-aware dataflow graphs (SADFs) efficiently model dynamic applications. The throughput of an application is an important metric to determine the performance of the system. For example, the number of frames per second output by a video decoder should always stay above a threshold that determines the quality of the system. During design-space(More)
—The ever increasing performance gap between processors and memories is one of the biggest performance bottlenecks for computer systems. In this paper, we propose a task scheduling technique that schedules an application, modeled with a task graph, on a multiprocessor system-on-chip (MPSoC) that contains a limited on-chip memory. The proposed scheduling(More)
—Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG can be extended with scheduling decisions, allowing SDFG analysis to obtain properties like throughput or buffer sizes for the scheduled graphs. Analysis times depend strongly on the size of the SDFG. SDFGs can be statically scheduled using static-order(More)
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