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There's nothing much to this What we have here is a collection of MOV instructions which set up values in registers before calling VIDEO through interrupt 10H Note that all of the entry points must be given as valid labels with olons The multiple entry points exist only to allow you to skip certain portions of the procedure that set up values that you don't want set All the registers used by VIDEO service 6 must be set up somewhere However, they can either be set within the procedure or in the caller's code just before the procedure is called If the procedure sets them, they have to be set to some generally useful configuration (say, clearing the entire screen), whereas if the caller sets them, the registers can be set to serve the caller's needs and make service 6 perform any of its varied combinations So it is with procedure ClrScr If you enter ClrScr through its main or top entry point, all of its internal code will be executed CX and DX will be set to the upper-left and lower-right corner coordinates of the full screen, AL is set to 0 to clear the full screen rather than scroll it, and BH is loaded with the "normal" (that is, blank, for white text on a black background) text display attribute Then service 6 is called If you wish to clear only a rectangular area of the screen (a window), you would use the ClrWin entry point This entry point starts executing the code after CX and DX are set to the corners of the full screen This means that the caller must load CX and DX with the upper-left and lower-right corners of the screen region to be cleared Calling ClrWin without setting CX and DX at all will execute service 6 with whatever leftover garbage values happen to be in CX and DX Something will happen, for certain Whether it's something that you want to happen is far less certain Keeping in mind that for proper operation, all of service 6's required registers must be set, calling ClrWin would be done this way: mov CX,0422H ; Set upper left corner to X=22H; Y=04H mov DX,093AH ; Set lower right corner to X=3AH; Y=09H call ClrWin ; Call the window-clear procedure The two MOV instructions are worth a closer look Rather than use a separate instruction to load each half of DX and CX, the two halves are loaded together by loading a 16-bit immediate data value into the full 16-bit register Thus, two MOV instructions can do the work that a first glance might think would take four MOV instructions This is a good example of writing tight, efficient assembler code The trick is to document it (as I've done in the preceding) to make sure you understand six weeks from now what the magic number 093AH really means! The first instruction at the label ClrWin sets AL to 0 Setting AL to 0 indicates that the region is to be cleared, not scrolled If, in fact, you do want to scroll the region, you need to skip the MOV instruction that loads 0 into AL This is the purpose of the entry point labeled ScrlWin It gets you into the procedure below the point at which you select clearing over scrolling This means that you not only have to set the corners of the region to be scrolled, but also the number of lines to scroll as well: mov CX, 0422H mov DX, 093AH mov AL, 1 call ScrlWin ; ; ; ; Set upper left corner to X=22H; Y=04H Set lower right corner to X=3AH; Y=09H Set to scroll by one line Call the window-scroll procedure.

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In the previous chapters we saw that in the analysis of many operational systems the concepts of a state of a system and a state transition are of basic importance For dynamic systems with a given probabilistic law of motion, the simple Markov model is often appropriate However, in many situations with uncertainty and dynamism, the state transitions can be controlled by taking a sequence of actions The Markov decision model is a versatile and powerful tool for analysing probabilistic sequential decision processes with an in nite planning horizon This model is an outgrowth of the Markov model and dynamic programming The latter concept, being developed by Bellman in the early 1950s, is a computational approach for analysing sequential decision processes with a nite planning horizon The basic ideas of dynamic programming are states, the principle of optimality and functional equations In fact dynamic programming is a recursion procedure for calculating ptimal value functions from a functional equation This functional equation re ects the principle of optimality, stating that an optimal policy has the property that whatever the initial state and the initial decision, the remaining decisions must constitute an optimal policy with regard to the state resulting from the rst transition This principle is always valid when the number of states and the number of actions are nite At much the same time as Bellman (1957) popularized dynamic programming, Howard (1960) used basic principles from Markov chain theory and dynamic programming to develop a policy-iteration algorithm for solving probabilistic sequential decision processes with an in nite planning horizon In the two decades following the pioneering work of Bellman and Howard, the theory of Markov decision processes has expanded at a fast rate and a powerful technology has developed However, in that period relatively little effort was put into applying the quite useful Markov decision model to practical problems.

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50 Figure 36: URL Shortening 51 Figure 37: Sequence Generator 52 Page 5. Page 5 of 73 Barcode Studio User Manual Figure 38: Export Dialog 53 .Related: 

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such a problem for parallel execution, an initial search tree is generated until there is a suf ciently large number of leaf nodes that can be executed in parallel (ie, until the required degree of concurrency is met) Each of these leaf nodes corresponds to an independent task, which searches for a solution in the subtree induced below this node The overall computation can nish as soon as one of the parallel tasks nds a solution This fact is the main difference between exploratory decomposition and data decomposition, where all subproblems must be solved in their entirety Speculative Decomposition Speculative decomposition takes the idea of exploratory decomposition even one step further In applications where the choice for a certain computation branch depends on the result of an earlier step, a speedup can be achieved by speculatively executing all (or a subset of all) branches At the time the data for making the choice is nally available, only the result of the correct branch is chosen; the others are discarded For example, an if statement in a programming language has wo lines of execution one if the evaluated expression is true, another if it is false In speculative decomposition, each of the two branches is made a task and executed concurrently At the time the expression of the if statement can nally be evaluated, the result of the correct branch is chosen and the result of the other branch is discarded 243 Computation Type and Program Formulation Essential for the subtask decomposition is the granularity, the dependence structure, and the regularity inherent in an application and its description as a program The computation type of an application and its expression as a program may already give a strong indication for its decomposition into subtasks Computation Type Most applications belonging to one area might employ certain types of computation and data structures For instance, an application of signal processing is likely to perform linear algebra on matrices In this case, data decomposition is probably the right technique Other application areas might typically use other types of data structures (eg, lists and graphs) and computations (eg, matching and search algorithms) For these application areas, recursive or exploratory decomposition can be a good candidate Furthermore, depending on the computation type, an application might consist of several distinct steps or one iterative block of computation In the former case, each step can be represented by one task, hence using coarse grained parallelism, while in the latter case the iterative computation suggests a regular, small grained decomposition, potentially based on data decomposition The type of the application also limits the inherent degree of concurrency For example, the matrix vector multiplication in Figure 216 performs n2 multiplications and n(n 1) additions All multiplications can be performed concurrently, but the additions must wait for the multiplications to nish Hence, the degree of concurrency is bounded by n2 Also, it is often pointless to partition an application into subtasks that strongly depend on each other s results, preventing their parallel execution due to the small degree of concurrency As will be shown in the next section,.

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Do you see the crash-and-burn bug in this sample This code crashes occasionally because it accesses released memory The m_ReturnDataPtr access is safe if the ThreadData class is not released until after Finished returns True ThreadData stays alive because it holds a reference on the Controller object, which, being public, keeps the main thread alive The other direct memory access call involves m_CancelPtr, which is valid as long s Worker is alive The problem is that Worker can complete and terminate at any time, so the memory might be invalid The CancelWorker code can be improved to first check if data has been returned, indicating that m_CancelPtr is now invalid Friend Sub CancelWorker() 'Signal if we haven't signaled before If m_CancelPtr Then If Not IsEmpty(m_ReturnData) Then InterlockedIncrement m_CancelPtr End If m_CancelPtr = 0 End If End Sub The timing problem that occurs when CancelWorker is called while the Worker class is being released is a classic case of a cross-thread synchronization bug These bugs are very difficult to reproduce reliably because the code runs in a random order You can best track these bugs by using the painstaking and error prone process of manually examining code from the interacting threads Step through the program from outside the debugger, and analyze alternating blocks of code from each thread to see if there is a potential problem The size of a block of code should range from a procedure to parts of a single statement For example, let's look at the interaction between the concluding code in Worker's FireTimer_Go and ThreadData's CancelWorker Lines from Worker are marked with a W; lines from ThreadData with a T T:If m_CancelPtr Then T:If Not IsEmpty(m_ReturnData) Then W:CopyMemory ByVal m_ReturnDataPtr, ByVal VarPtr(Data), 16 W:CopyMemory ByVal VarPtr(Data), 0, 2 T:InterlockedIncrement m_CancelPtr.

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