MNEMEE - Electronic Systems - Technische Universiteit Eindhoven

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in the tile binding and scheduling phase. This phase binds actors and channels from the resource-aware SDFG to the resources in the platform graph. When a resource is shared between different actors or applications, a schedule should be constructed that orders the accesses to the resource. The accesses from the actors in the resource-aware SDFG to a resource are ordered using a static-order schedule. TDMA scheduling is used to provide virtualization of the resources to the application. The third phase of the design flow does not consider the scheduling of the communication on the NoC. This problem is considered in the NoC routing and scheduling phase of the design flow. The actor bindings and schedules impose timing-constraints on the communication that must be met when constructing a communication schedule. These timing constraints are extracted from the bindingaware SDFG and subsequently a schedule is constructed for the token communication that satisfies these timing constraints while minimizing the resource usage. The mapping of the streaming application to the NoC-based MP-SoC may fail at various steps of the design flow. This may occur due to lack of resources (step 7) or infeasible timing constraints (step 9 and 12). In those situations, the design flow iterates back to the first or third step of the flow and design decisions made in those steps are revised. Consider as an example the H.263 encoder shown in Figure 4. This application has been mapped, using the predictable design flow, onto a multiprocessor platform that consists of two general purpose processors and three accelerators. These processing elements are interconnected using a Network-on- Chip. The resulting MP-SoC configuration is shown in Figure 6. The predictable design flow has been implemented in SDF 3 [45]. It takes this tool 415ms to find a MP-SoC configuration that satisfies the throughput constraints of the application, while at the same time it tries to minimize the resource usage of the application. Public Page 18 of 87
Figure 6 – H.263 encoder mapped onto MP-SoC platform. 7.3. FSM-based SADF The SDF Model-of-Computation (MoC) is introduced in Section 7.2.2. That section also shows how an application can be modelled with an SDFG. The SDF model of an application assumes worst-case rates for the edges and worst-case execution times for the actors. In the situation that an application contains a lot of dynamism, the use of worst-case values could lead to over-dimensioning of the system for many run-time situations. Therefore, the concept of system scenarios has been introduced in [28][29] (see also Section 7.2.1). However, these scenarios cannot be modelled into an SDFG. This section introduces an extension to the SDF MoC that can be used to model an application together with its scenarios. This new MoC is called the Finite State Machine-based Scenario-Aware Data-Flow (FSM-based SADF) MoC. The FSM-based SADF MoC is a restricted form of the general SADF MoC that has been introduced in [48]. These restrictions make analysis of the timing behaviour of a model specified in the FSM-based SADF MoC faster than a model specified in the general SADF MoC. However, analysis result may be less tight due to the abstractions made in the FSM-based SADF MoC. A formal definition of the FSMbased SADF MoC and a discussion on the differences between this MoC and the general SADF MoC can be found in [46]. Here, we focus on an example. Public Page 19 of 87
Page 1 and 2: Information Societies Technology (I
Page 3 and 4: 9.5. METRICS AND COST FACTORS FOR D
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Page 7 and 8: 4. Preface The main objectives of t
Page 9 and 10: 6. Introduction Multimedia applicat
Page 11 and 12: Figure 2 - Preliminary MNEMEE sourc
Page 13 and 14: modelled with an FSM-based SADF, on
Page 15 and 16: analyzing the basic operations of t
Page 17: Figure 5 - SDFG-based MP-SoC design
Page 21 and 22: transitions reflect possible next s
Page 23 and 24: parameters is modified, the applica
Page 25 and 26: There is however one problem with u
Page 27 and 28: 7.6. FSM-based SADF-based multi-pro
Page 29 and 30: 8. Statically allocated data storag
Page 31 and 32: Embedded systems differ from genera
Page 33 and 34: Plasma), etc., is enabled by compre
Page 35 and 36: One of the most important developme
Page 37 and 38: The Atomium/Analysis version includ
Page 39 and 40: 8.4.3. Profiling steps Profiling th
Page 41 and 42: Array size [bytes] Number of access
Page 43 and 44: For multimedia application this is
Page 45 and 46: Figure 22 - Data re-use at differen
Page 47 and 48: Figure 24 - (Pruned) re-use graph o
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Page 51 and 52: has to be refreshed completely, bec
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Page 57 and 58: 9. Dynamically allocated data stora
Page 59 and 60: combination of DDT implementations.
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Page 65 and 66: Improving the performance of the DM
Page 67 and 68: The problem with the aforementioned
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1. Problem 1: Increased complexity
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Table 3 - Comparison of different p
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Table 4 - Profiling information sto
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Figure 40 - Maximum number of objec
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Figure 43 - Utilization of the allo
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10. Conclusions Future multimedia a
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[17] Ang, S., Constantinides, G., L
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[34] MPEG-2. Generic coding of movi
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[65] SGI. Standard template library
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12. Glossary ANL Atomium analysis D
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