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GICS follows the outline of Algorithm 20, Section 65 Naturally, the chromosome encodes the processor allocation, which is an indirect representation (Section 652) Hence, the construction of the schedule corresponding to each chromosome, which is necessary for the evaluation of its tness, requires the application of a heuristic As already mentioned, this is performed by a list scheduling heuristic under the involvement contention model (see later discussion) Strictly speaking, this means that a two-phase heuristic is applied multiple times in GICS once for each new chromosome To reduce the running time of the evaluation, the node order is determined only once at the beginning of the algorithm, namely, according to their bottom levels Like most GAs, GICS starts with a random initial population, enhanced with a chromosome representing a sequential schedule (all nodes are allocated to a single processor) The pool is completed by one allocation extracted from a schedule produced with a list scheduling heuristic (Section 841) Most other components are fairly standard In fact, the algorithm can even be employed for scheduling under the classic or the contention model, using a modi ed evaluation (ie, scheduling heuristic) Phase 2 List Scheduling From Section 52 it is known that the second phase can be performed with a simple list scheduling algorithm The processor choice of list scheduling is simply a lookup from the given mapping A established in the rst phase Even though list scheduling under the involvement contention model was already studied in Section 841, it must be revisited as there are three alternatives for the scheduling of the edges when the processor allocation is already given (Section 832) Scheduling of the Edges The rst alternative corresponds to direct scheduling, and the procedures for the scheduling of a node and the calculation of the DRT are presented in Algorithms 23 and 24 The scheduling of an edge on the source processor must be modi ed (line 16 in Algorithm 23), since it is no longer necessary to assume the worst case Lines 1 5 (removing local edges) and line 9 (correcting the nish time) can be dropped completely, since the provisional scheduling of the edges is not necessary with the given processor allocation The other two alternatives are only distinguished from this procedure through the place where the edges are scheduled on the links and the destination processor So, for the second alternative, where the edge is scheduled on the links as a leaving edge, lines 8 and 10 of Algorithm 23 move o the for loop on lines 15 17 In the third alternative, the edge is also scheduled on the destination processor within this loop, and the for loop for the entering edges (lines 6 13) is completely dropped Of course, in the determination of the DRT the entering edges do not need to be tentatively scheduled, as the processor allocation is already given Complexity The complexity of list scheduling with a given processor allocation decreases slightly in comparison to list scheduling with start/ nish time minimization It is not necessary to tentatively schedule a node and its edges on every processor Thus,.

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723 Scheduling Network Model Sections 721 and 722 analyzed, from the perspective of scheduling, the topologies of communication networks and their routing policies It remains merely to summarize this analysis to establish a network model based on the topology graph (Sinnen and Sousa [172, 179]) De nition 75 (Network Model) A communication network of a parallel system is represented by a topology graph TG = (N, P, D, H, b) (De nition 73) The routing algorithm carried out n the topology graph is that of the represented network (or its closest approximation) Furthermore, routing has the following properties: 1 Static Routing in the network is static; the selected route does not depend on the state of the network If the represented network employs adaptive routing, the default behavior (ie, the behavior without traf c con icts) is reproduced 2 Circuit Switching The communication route between two processors of the network is the same for the entire message 3 Cut-through A message cuts through the communication stations (processor or switch) on its route; that is, all links of the route are utilized at the same time 4 No Routing Delay per Hop No delay is in icted by the transition between links on the communication route Edge scheduling, which is investigated in the next section, employs this model for the representation of the network.NET framework Control to read, scan read, scan image in VS .NET applications /div>. ECC200 In .NET Framework Using Barcode printer for ASP .Related: Print QR Code VB.NET Data, Create QR Code .NET Size, Create QR Code ASP.NET Size

Within the framework of testing, isolation provides the advantage of having a single testable interface A public service API can be checked and agreed upon Changes within the service need not affect how the API responds to commands The testing of a service s interface is very much like unit or model testing within a Rails application The only difference is that the callable methods are HTTP methods that can be called by any application All the details of the business logic and how data is stored or optimized are hidden behind the service interface The big advantage isolation provides with regard to testing is in the time required to run the test suite Rails developers orking on mature projects with large code bases routinely have to wait longer than 15 minutes for their test suites to run to completion In fact, it s not entirely uncommon for some teams to work with large code bases that take longer than 40 minutes to run their entire suite of tests This becomes a major problem when you want to change something small After even a small change, the full suite of tests must be run to ensure that the change didn t break anything With isolated application components, testing to make sure other parts of an application are functioning properly becomes a much smaller problem For example, consider an application code base that takes 20 minutes to run the full suite of tests Then break that application into four fairly evenly sized, separate, isolated components Now the test time for a single change to one of these components is cut down to one-fourth of what was previously needed If a change is made to one of the new components, it isn t necessary to run the test suite for everything Only the tests for the single component need to be run, and in this example, that would take roughly 5 minutes rather than 20 As long as the public-facing interface for the component is well tested, changes can be deployed without concern that the other three-fourths of the application still works Of course, if the API of a service changes, then each consumer must be tested to ensure proper operation.

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