Virtual Architecture Mapping: A SystemC Based Methodology for Architectural Exploration of System-on-Chip Designs

2008

IJES

Abstract:In this paper, we present an overview of the Artemis workbench, which provides modelling and simulation methods and tools for efficient performance evaluation and exploration of heterogeneous embedded multimedia systems. More specifically, we describe the Artemis system-level modelling methodology, including its support for gradual refinement of architecture performance models as well as for calibration of the system-level models. We show that this methodology allows for architectural exploration at different levels of abstraction while maintaining high-level and architecture independent application specifications. Moreover, we illustrate these modelling aspects using a case study with a Motion-JPEG application.

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

The Artemis workbench for system-level performance evaluation of embedded systems

2008

IJES

“…As mentioned in our introduction, there are various related architectural exploration environments (e.g., [7,13,24,27,35]) that, like Sesame, also facilitate flexible system-level performance evaluation by providing support for mapping a behavioral application specification to an architecture specification. In Gries [18], an excellent survey is presented of various methods, tools and environments for early design space exploration.…”

Section: Related Workmentioning

confidence: 99%

“…A fair number of promising system-level simulation-based exploration environments have been proposed in recent years, such as Metropolis [6], MESH [13], Milan [27], Sesame [14,31], and various SystemC-based environments like GRACE++ [24]. These environments typically facilitate efficient and flexible performance evaluation of embedded systems architectures.…”

Section: Introductionmentioning

confidence: 99%

Calibration of Abstract Performance Models for System-Level Design Space Exploration

J Sign Process Syst Sign Image

Thompson

Polstra

et al. 2007

Abstract. High-level performance modeling and simulation have become a key ingredient of system-level design as they facilitate early architectural design space exploration. An important precondition for such highlevel modeling and simulation methods is that they should yield trustworthy performance estimations. This requires validation (if possible) and calibration of the simulation models, which are two aspects that have not yet been widely addressed in the system-level community. This article presents a number of mechanisms for both calibrating isolated model components as well as a system-level performance model as a whole. We discuss these model calibration mechanisms in the context of our Sesame system-level simulation framework. Two illustrative case studies will also be presented to indicate the merits of model calibration.

“…In recent years, a fair number of system-level simulation-based exploration environments have been proposed, such as Metropolis [2], GRACE++ [3], Koski [4], and our own Sesame [5] framework. The Sesame modeling and simulation framework aims at efficient system-level design space exploration of embedded multimedia systems, allowing rapid performance evaluation of different architecture designs, application to architecture mappings, and hardware/software partitionings.…”

Section: Introductionmentioning

confidence: 99%

Towards Multi-application Workload Modeling in Sesame for System-Level Design Space Exploration

Thompson

Lecture Notes in Computer Science

Abstract. The Sesame modeling and simulation framework aims at early and thus efficient system-level design space exploration of embedded multimedia system architectures. So far, Sesame only supported performance evaluation when mapping a single application onto a (multi-processor) architecture at the time. But since modern multimedia embedded systems are increasingly multi-tasking, we need to address the modeling of effects of executing multiple applications concurrently in our system-level performance models. To this end, this paper conceptually describes two multi-application workload modeling techniques for the Sesame framework. One technique is based on the use of synthetic application workloads while the second technique deploys only real application workloads to model concurrent execution of applications. For illustrative purposes, we also present a preliminary case study in which a Motion-JPEG encoder application is executed concurrently with a small synthetic producer-consumer application.