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We provide a simple example of how these functions are used in Fig A10 The program prints the thread ID and the number of threads to the standard output The output from the program in Fig A10 would look something like this:

Before actually serializing an object, its writeReplace method, if any, is called This method returns an Object to be serialized By default, if no writeReplace method is present, this is the same object However, a writeReplace method may substitute a surrogate object in the output stream After de serializing an object, its readResolve method, if any, is called:

import comnttdocomouiIApplication; public class HelloIAppli extends IApplication{ public void start() { MyCanvas myCanvas = new MyCanvas(); DisplaysetCurrent(myCanvas);

libraries be thread safe Which thread prints its record when, however, is not specified, and any valid interleaving of the output records can occur

Graphics The comnttdocomouiGraphics class is very similar to the MIDP's Graphics class There are some interesting additions and omissions, however:

ANY-ACCESS-MODIFIER Object readResolve() throws ObjectStreamException;

drawPolyline(int[] xPoints, int[] yPoints, int numPoints)

.

fillPolygon(int[] xPoints, int[] yPoints, int numPoints) Paints a filled polygon with vertices indicated by xPoints and yPoints arrays There is no

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Many OpenMP programs can be written using only the parallel and parallel for (parallel do in Fortran) constructs There are algorithms, however, where one needs more careful control over how variables are shared When multiple threads read and write shared data, the programmer must ensure that the threads do not interfere with each other, so that the program returns the same results regardless of how the threads are scheduled This is of critical importance since as a multithreaded program runs, any semantically allowed interleaving of the instructions could actually occur Hence, the programmer must manage reads and writes to shared variables to ensure that threads read the correct value and that multiple threads do not try to write to a variable at the same time Synchronization is the process of managing shared resources so that reads and writes occur in the correct order regardless of how the threads are scheduled The concepts behind synchronization are discussed in detail in the section on synchronization (Section 63) in the Implementation Mechanisms design space Our focus here will be on the syntax and use of synchronization in OpenMP Consider the loop based program in Fig A5 earlier in this chapter We used this example to introduce worksharing in OpenMP, at which time we assumed the combination of the computed results (res) did not take much time and had to occur in the sequential order Hence, it was no problem to store intermediate results in a shared array and later (within a serial region) combine the results into the final answer In the more common case, however, results of big_comp() can be accumulated in any order as long as the accumulations do not interfere To make things more interesting, we will assume that the combine() and big_comp() routines are both time consuming and take unpredictable and widely varying amounts of time to execute Hence, we need to bring the combine() function into the parallel region and use synchronization constructs to ensure that parallel calls to the combine() function do not interfere The major synchronization constructs in OpenMP are the following.

This method also returns an Object representing the result of the de serialization By default, if no readResolve method is present, this is also the same object as was just de serialized However, a readResolve method may substitute a surrogate object in the input stream Note

lock() Begins double buffering setOrigin(int x, int y) Sets the origin upon which all coordinates will be

flush defines a synchronization point at which memory consistency is enforced This can be subtle Basically, a modern computer can hold values in registers or buffers that are not guaranteed to be consistent with the computer's memory at any given point Cache coherency protocols guarantee that all processors ultimately see a single address space, but they do not guarantee that memory references will be up to date and consistent at every point in time The syntax of flush is

setColor(int color) Sets a color to be used for drawing Note that you must grab the appropriate color for the given handset using either the getColorOfName(int color) method or getColorOfRGB(int r,int g,int b) For example gsetColor((ggetColorOfName(gYELLOW)))

If the original class's writeReplace method returns an object of a different class, the readResolve method of the different class will be called on de serialization, not the readResolve method of the original class To use this technique successfully, either the writeReplace and readResolve methods must return objects of the same class as the original object being serialized, or the class of the object returned by writeReplace must implement a readResolve method which returns an object of the original class A class which replaces itself on serialization is shown in Example 36

gsetColor((ggetColorOfRGB(128,128,128))) unlock(boolean forced) Ends double buffering When you lock the graphics

#pragma omp flush [(list)]

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