Architecture of Computing Systems (Lecture Notes in Computer ...

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42 P. Bellasi, W. Fornaciari, and D. Siorpaes “Feasible System-wide Configurations” (FSC) available for the target system, that we named: FSC model. A FSC is a region on the SWCS, thus is defined by a set of validity ranges for each SWM, where it is granted that each device could be configured to operate in a WM that does not have any conflict with any other device. These regions are particularly important because they grant that any inter-dependency among devices is safely solved. Though a number of interesting theoretical techniques can be defined to identify at run-time what is the optimal system configuration, according to both the available resources and the required performance, every outcome is useless if it cannot be actually applied to the real system because of implicit inter-dependencies or hardware constraints ignored by the optimization policy itself. Indeed an optimized configuration cannot be identified regardless of its feasibility. Thanks to their interesting property, the identification of all system’s FSCs is especially important. Considering this, the optimization technique proposed is based on the ’a-priori identification’ of all and only the system feasible configurations. Thus, any optimization policy that will be developed on top of this framework, it will be granted to operate on a set of real and valid configurations and consequently each result can be safely applied to real system. The Optimization Layer exploits the system view offered by the underlying FSC model to support the global optimization policy of the proposed hierarchical distributed control. This is obtained by the definition of a strategy to assign a “weight” to each feasible configuration according to the running optimization policy. The weight associated to FSC is defined to be a sufficiently abstract metric which can be easily adapted for a generic multi-objective optimization. The run-time tracking of application requirements is another goal of this layer. The abstract system model, based on the concept of FSC and their representation in the SWCS, is properly exploited at this layer to translate application requirements on constraints for the research of the optimal configuration. Indeed, application requirements are translated on constraints for the optimization problem which could invalidates some FSCs. Thus, this layer provides support for both: FSC pre-ordering, according to the optimization objectives of the running policy, and optimal FSC selection, considering user-space requirements to filter out run-time invalidated FSC. 3.3 Formal Validation of the Optimization Policy The hierarchical distributed control problem can be conveniently reformulated using an appropriate formal model. A transposition of this type has been done not only to provides a rigorous description of the problem and a formal proof of the solution quality, but also allows to identify more easily a possible alternative solution strategy by taking into account the particularities of the specific formulation. We have reformulated the problem using Linear Programming. A simple representation of the LP formulation is depicted in Fig. 3. In this simple scenario we consider a system with three devices (d1, d2 and d3) and two SWMs (p1 and p2). The available FSCs are only three, but at run-time it could happen that some of them (FSC3 in the example) are invalidated by
Hierarchical Distributed Control of Power and Performances 43 π 2M p 2 C 31 O FSC 1 C 22 C 21 C 11 Convex−Hall C 32 π 1c d 1 C 23 d 2 C 12 C 33 d 3 π 1M working regions Fig. 3. Example of LP formulation for the global optimization problem the constraints representing application requirements. The optimization policy is represented in the LP formulation by an objective function og which identifies the direction of a multi-objective optimization in the domain of the SWM. Indeed, the global optimization policy is defined by the composition of multiple objectives, each one corresponding to a different SWM metric with an associated optimization priority. It is possible to prove that the solution of the LP problem, O in the example, can always be mapped to one ore more FSC. These will represent the feasible configurations which are optimal w.r.t. the running policy. 3.4 Framework Implementation The formal representation of the problem certifies the goodness of the configuration identified. Moreover, it also suggests an efficient implementation of the optimization algorithm which is composed by three steps: 1) FSC Identification: at boot time all the drivers register to CPM by exposing their DWRs using the abstraction layer interface. Thereafter, all the FSCs can be automatically identified by the model layer. 2) FSC ordering: a multi-objective optimization policy is settled by simply defining the optimization priority for each metric in the configuration space, i.e. by associating a “weight” to each SWM. Thus, starting from the set of all FSCs which are identified by the model layer, it is possible to pre-order the solutions of the optimization problem. In the previous example, according to the optimization policy represented by the vector og, the solutions ordered starting from the best one are: FSC3, FSC1 and finally FSC2. 3) FSC selection: at run-time the requirements asserted by applications are aggregated and properly translated into constraints for the optimization O’ FSC 2 FSC 3 o g o 1 o 2 v 1 p 1 v 3 v 3
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Lecture Notes in Computer Science 5
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106 K. Kloch et al. constant. This
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Exploiting Inactive Rename Slots fo
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128 M. Kayaalp et al. In a supersca
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130 M. Kayaalp et al. INSTRUCTION 1
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Efficient Transaction Nesting in Ha
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140 Y. Liu et al. HTMs include TCC
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142 Y. Liu et al. rollback T0 begin
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144 Y. Liu et al. Processor core Pr
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146 Y. Liu et al. 5.2 Results and A
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148 Y. Liu et al. decreases, partia
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Decentralized Energy-Management to
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152 B. Becker et al. Furthermore, t
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154 B. Becker et al. An optimizing
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156 B. Becker et al. smart-home man
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EnergySaving Cluster Roll: Power Sa
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Optimizing Stencil Application on M
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244 F. Xudong et al. 5 Related Work
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Abdullah, Tariq 174 Alima, Luc Onan
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