Scalable Analysis for Multi-Scale Dataflow Models

Abstract

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Optimising Multiprocessor Image-Based Control Through Pipelining and Parallelism

“…7 (c), the throughput is 1 65 and the latency, relative to the period equalling the inverse of the throughput, is 65. We omit the details of the computation, referring the reader to [40]. But the results should not be surprising given the timing analysis of the scenario execution given earlier.…”

“…In this subsection, we summarise the relevant definitions for our analysis. For detailed explanations, the reader is referred to [40].…”

Automated Buffer Sizing of Dataflow Applications in a High-level Synthesis Workflow

“…The HLS pragma is compatible with the free-running mode and we use both in this paper. Yet, most Xilinx dataflow examples are single-rate ones not benefiting from the free-running mode, such as Xilinx version of Gaussian difference 3 .…”

“…In [3], authors develop a method to compute the maximum achievable throughput of a dataflow graph of actors similar to FPGA kernels. Their analysis takes benefit of an extra Finite State Machine (FSM) separating the kernel phases into an initial read (rush-in), a cyclic computation phase and a final write (rush-out).…”

Designing image-based control systems considering workload variations

“…The execution times for the tasks RoID, RoIP, RoIM, C and A are e d , e p , e m , e c and e a respectively. A scenarioaware dataflow graph [14] (see Fig. 3) is composed of: (i) a set of scenarios that model the workload variations (and are hence called workload scenarios); and (ii) a language that describes a set of infinite scenario (switching) sequences.…”