Multiprocessor Systems on Chip

Kempf, Torsten; Ascheid, Gerd; Leupers, Rainer

doi:10.1007/978-1-4419-8153-0

Cited by 18 publications

(6 citation statements)

References 141 publications

(215 reference statements)

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“…In order to achieve the advantages from analytical and simulation based approaches, e.g., evaluation speed and accuracy, JAS-DSE approaches have been proposed [19]. A common JAS-DSE approach is to use simulation traces to compute the workloads which are later used in an analytical phase.…”

Section: Related Workmentioning

confidence: 99%

“…A summary of them can be found in [19]. DSE frameworks such as Sesame [27,36] or Multicube [31] have proposed a clear separation among application, platform architecture, and mapping in the system description, and moreover, the separation of the system simulatable performance model from the exploration tool, e.g., Multicube Explorer [39], which steers the search.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, simulation-based performance analysis considers the dynamism of the application. In order to combine the advantages from both approaches, Joint Analytical and Simulation-based Design Space Exploration (JAS-DSE) has been proposed in [19]. In most cases, a two-phase approach is proposed, where in a first step simulation is used, to get traces and/or perform a calibration before a second analytical phase [19].…”

Section: Introductionmentioning

confidence: 99%

“…DSE has become a high and active research field. In [19], two main approaches to DSE are distinguished, analytical and simulation-based DSE. In an analytical approach the design problem is abstracted into a formal problem, in order to enable the application of analysis techniques [21].…”

Section: Introductionmentioning

confidence: 99%

“…In an analytical approach the design problem is abstracted into a formal problem, in order to enable the application of analysis techniques [21]. Analytical approaches are convenient for a first and fast filtering of the design space [19]. However, analytical approaches have also limitations.…”

Section: Introductionmentioning

confidence: 99%

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Combining Analytical and Simulation-Based Design Space Exploration for Efficient Time-Critical and Mixed-Criticality Systems

Herrera

Sander

2014

Lecture Notes in Electrical Engineering

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In the context of the design on time-critical systems, analytical models with worst case workloads are used to identify safe solutions that guarantee hard timing constraints. However, the focus on the worst case often leads to unnecessarily pessimistic and inefficient solutions, in particular for mixed-critical systems. To overcome the situation, the paper proposes a novel design flow integrating analytical and simulation-based Design Space Exploration (DSE). This combined approach is capable to find more efficient design solutions, without sacrificing timing guarantees. For it, a first analytical DSE phase obtains a set of solutions compliant with the critical time constraints. Search of the Pareto optimum solutions is done among this set, but it is delegated to a second simulation-based search. The simulation-based search enables more accurate estimations, and the consideration of a specific (or an averagecase) scenario. The chapter shows that this can lead to different Pareto sets which reflect improved design decisions with respect to a pure analytical DSE approach, and which are found faster than through a pure simulation-based DSE approach. This is illustrated through an accompanying example and a proof-of-concept implementation of the proposed DSE flow.

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Section: Related Workmentioning

confidence: 99%