Model-Based Representations for Dataflow Schedules

Bhattacharyya, Shuvra S.; Lilius, Johan

doi:10.1007/978-3-319-95246-8_6

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…The decision state modeling approach [10] provides a modelbased schedule representation that is formulated directly on general SDF graphs, and does not require expansion to homogeneous SDF form. An extensive review of modelbased schedule representations is provided in [2].…”

Section: Related Workmentioning

confidence: 99%

Software synthesis from dataflow schedule graphs

Lee

Raina

et al. 2021

SN Appl. Sci.

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The dataflow-model of computation is widely used in design and implementation of signal processing systems. In dataflow-based design processes, scheduling—the assignment and coordination of computational modules across processing resources—is a critical task that affects practical measures of performance, including latency, throughput, energy consumption, and memory requirements. Dataflow schedule graphs (DSGs) provide a formal abstraction for representing schedules in dataflow-based design processes. The DSG abstraction allows designers to model a schedule as a separate dataflow graph, thereby providing a formal, abstract (platform- and language-independent) representation for the schedule. In this paper, we introduce a design methodology that is based on explicit specifications of application graphs and schedules as cooperating dataflow models. We also develop new techniques and tools for automatically synthesizing efficient implementations on multicore platforms from these coupled application and schedule models. We demonstrate the proposed methodology and synthesis techniques through a case study involving real-time detection of people and vehicles using acoustic and seismic sensors.

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Section: Related Workmentioning

confidence: 99%

Software synthesis from dataflow schedule graphs

Lee

Raina

et al. 2021

SN Appl. Sci.

Self Cite

View full text Add to dashboard Cite

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“…Scheduling often has major impact on metrics for efficiency evaluation, including the ones listed above. Model-based scheduling representations provide for-mal, platform-independent approaches for representing, reasoning about, and transforming schedules [9].…”

Section: Compact System-level Modelsmentioning

confidence: 99%

Research Challenges for Heterogeneous CPS Design

Bhattacharyya¹,

Wolf²

2020

Preprint

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Heterogeneous computing is widely used at all levels of computing from data center to edge due to its power/performance characteristics. However, heterogeneity presents challenges. Interoperability-the management of workloads across heterogeneous resources-requires more careful design than is the case for homogeneous platforms. Cyberphysical systems present additional challenges. This article considers research challenges in heterogeneous CPS design, including interoperability, physical modeling, models of computation, selfawareness and adaptation, architecture, and scheduling.

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Research Challenges for Heterogeneous Cyberphysical System Design

Bhattacharyya

Wolf

2020

Computer

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Model-Based Representations for Dataflow Schedules

Cited by 3 publications

References 22 publications

Software synthesis from dataflow schedule graphs

Software synthesis from dataflow schedule graphs

Research Challenges for Heterogeneous CPS Design

Research Challenges for Heterogeneous Cyberphysical System Design

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