Adfg

Honorat, Alexandre; Tran, Hai Nam; Besnard, Loïc; Gautier, Thierry; Talpin, Jean-Pierre; Bouakaz, Adnan

doi:10.1145/3139258.3139267

Cited by 4 publications

(2 citation statements)

References 36 publications

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“…This experiment measures the graph period gap between the proposed non-preemptive offline scheduler Algorithm 2 and a standard preemptive real-time scheduler: EDF. The ADFG tool [22] is used as a reference, using Global EDF scheduling [4] (with an algorithm adapted from the forced-forward demand bound function). ADFG considers that all actors are periodic and computes their optimal smallest period for a given number of cores.…”

Section: Gap Between the Proposed Scheduler And Preemptive Earliest Dmentioning

confidence: 99%

“…The Darts tool [2] is able to schedule SDF graphs under a throughput constraint, equivalent to a graph period constraint, for EDF and FP schedulers. ADFG [22] is similar to Darts, but it optimizes the throughput under a total buffer size constraint. SDF graphs can be modeled with synchronous languages such as Prelude [35], which generates code for EDF and FP schedulers.…”

Section: Related Workmentioning

confidence: 99%

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Scheduling of Synchronous Dataflow Graphs with Partially Periodic Real-Time Constraints

Honorat

Desnos

Bhattacharyya

et al. 2020

Proceedings of the 28th International Conference on Real-Time Networks and Systems

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Modern Cyber-Physical Systems (CPSs) are composed of numerous components, some of which require real-time management: for example, management of sensors and actuators requires periodic deadlines while processing parts do not. We refer to these systems as partially periodic. In a partially periodic system, precedence constraints may exist between periodic and aperiodic components. It is notably the case in CPSs where sensors measuring physical variables at a fixed sampling rate are typically feeding data to one or more processing part. A critical challenge for any real-time CPS software is its scheduling on an embedded computing platform. The increasing number of cores in such platforms (as Kalray MPPA Bostan having 288 cores) makes offline non-preemptive scheduling techniques efficient to respect real-time constraints, but requires new analysis and synthesis algorithms. In this paper, we study the schedulability of partially periodic systems modeled as Synchronous Data Flow (SDF) graphs. Our contributions are a few necessary conditions on any live SDF graph, and a linearithmic offline non-preemptive scheduling algorithm on vertices of any directed acyclic task graph. The presented algorithm has been evaluated on a set of randomly generated SDF graphs and on one real use-case. Experiments show that our proposed non-preemptive scheduling algorithm allocates thousands of tasks in less than a second. In the last experiment, the computed schedules achieve a throughput close to that one obtained with global Earliest Deadline First (EDF) scheduling.

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Section: Gap Between the Proposed Scheduler And Preemptive Earliest Dmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Scheduling of Synchronous Dataflow Graphs with Partially Periodic Real-Time Constraints

Honorat

Desnos

Bhattacharyya

et al. 2020

Proceedings of the 28th International Conference on Real-Time Networks and Systems

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A Framework for Fixed Priority Periodic Scheduling Synthesis from Synchronous Data-Flow Graphs

Tran

Honorat²,

Bhattacharyya³

et al. 2022

Lecture Notes in Computer Science

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Synchronous data-flow graphs (SDF) are widely used in the design of concurrent real-time digital signal processing applications on multiprocessor system-on-chip. The increasing complexity of these hardware platforms advocates the use of real-time operating systems and fixed-priority scheduling to manage applications and resources. This trend calls for new methods to synthesize and implement actors in SDF graphs as real-time tasks with computed scheduling parameters (periods, priorities, processor mapping, etc.). This article presents a framework supporting scheduling synthesis, scheduling simulation, and code generation of these graphs. The scheduling synthesis maps each actor to a periodic real-time task and computes the appropriate buffer sizes and scheduling parameters. The results are verified by a scheduling simulator and instantiated by a code generator targeting the RTEMS (Real-Time Executive for Multiprocessor Systems) operating system. Experiments are conducted to evaluate the framework's performance and scalability as well as the overhead induced by the code generator.

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Efficient Contention-Aware Scheduling of SDF Graphs on Shared Multi-Bank Memory

Tran

Honorat

Talpin

et al. 2019

2019 24th International Conference on Engineering of Complex Computer Systems (ICECCS)

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Novel memory architectures have been introduced in multi/many-core processors to address the performance bottle neck due to shared memory accesses. Taking the advantages brought by these architectures in scheduling analysis is still an open challenge. In this article, we present a scheduling analysis technique that exploits a shared multi-bank memory architecture to efficiently schedule parallel real-time applications modeled as synchronous data flow (SDF) graphs by minimizing the memory access contentions. Our approach aims at producing a static timetriggered schedule with the objective of minimizing the makespan and buffer size requirements while respecting consistency and data dependency constraints. An Integer Linear Programming formulation of the scheduling problem is presented, as well as a heuristic with significantly lower time complexity. Experimental results are given using synthetic SDF graphs generated by the SDF3 tool and applications available in the StreamIt benchmark.

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Adfg

Cited by 4 publications

References 36 publications

Scheduling of Synchronous Dataflow Graphs with Partially Periodic Real-Time Constraints

Scheduling of Synchronous Dataflow Graphs with Partially Periodic Real-Time Constraints

A Framework for Fixed Priority Periodic Scheduling Synthesis from Synchronous Data-Flow Graphs

Efficient Contention-Aware Scheduling of SDF Graphs on Shared Multi-Bank Memory

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