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Some concurrent programming techniques have much in common with those in event frameworks employed in GUI toolkits supported by javaawt and javaxswing, and in other languages such as Tcl/Tk and Visual Basic In GUI frameworks, events such as mouse clicks are encapsulated as Event objects that are placed in a single EventQueue These events are then dispatched and processed one-by-one in a single event loop, which normally runs as a separate thread As discussed in 41, this design can be extended to support additional concurrency by (among other tactics) creating multiple event loop threads, each concurrently processing events, or even dispatching each event in a separate thread Again, this opens up new design possibilities, but also introduces new concerns about interference and coordination among concurrent activities 1233 Concurrent systems programming Object-oriented concurrent programming differs from multithreaded systems programming in languages such as C mainly due to the encapsulation, modularity, extensibility, security, and safety features otherwise lacking in C Additionally, concurrency support is built into the Java programming language, rather than supplied by libraries This eliminates the possibility of some common errors, and also enables compilers to automatically and safely perform some optimizations that would need to be performed manually in C While concurrency support constructs in the Java programming language are generally similar to those in the standard POSIX pthreads library and related packages typically used in C, there are some important differences, especially in the details of waiting and notification (see 322) It is very possible to use utility classes that act almost just like POSIX routines (see 344) But it is often more productive instead to make minor adjustments to exploit the versions that the language directly supports 1234 Other concurrent programming languages Essentially all concurrent programming languages are, at some level, equivalent, if only in the sense that all concurrent languages are widely believed not to have defined the right concurrency features However, it is not all that hard to make programs in one language look almost equivalent to those in other languages or those using other constructs, by developing packages, classes, utilities, tools, and coding conventions that mimic features built into others In the course of this book, constructions are introduced that provide the capabilities and programming styles of semaphore-based systems ( 341), futures ( 433), barrier-based parallelism ( 443), CSP ( 451) and others It is a perfectly great idea to write programs using only one of these styles, if this suits your needs However, many concurrent designs, patterns, frameworks, and systems have eclectic heritages and steal good ideas from anywhere they can.

sequentialThreshold) = seqFib(n); = new Fib(n - 1); = new Fib(n - 2);

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Data is stored and maintained in different data sources. Some data source applications include MS-Access, SQL Server, Oracle, and Sybase. Each data source uses its own native syntax. Therefore, when you need to manage data stored in data sources from your applications, you would prefer to use standard objects and syntaxes irrespective of the data sources. It is inconvenient to use different objects, methods, and syntaxes to manage different data sources. ADOX provides a set of standard objects that you can use to manage data stored in different data sources. ActiveX Data Objects Extensions (ADOX) is an extension of the ADO objects and programming model that allows creation, modification, and manipulation of schema objects, such as databases, tables, and columns. ADOX also includes security objects that enable you to maintain users and groups that access the schema objects. ADOX

coInvoke(f1, f2); }

number = f1number + f2number;

security objects can be used to grant and revoke permissions on objects that are accessed by different users and groups. ADOX is part of the Microsoft Data Access Components (MDAC) SDK. When you install Visual Studio .NET, the Windows Component update installs MDAC 2.7. You can visit the http://www.microsoft.com/data/download.htm site to get the latest release of MDAC SDK. Standard ADOX objects ADOX objects are a set of standard objects that are used to create and manipulate data stored in different data sources irrespective of their native syntaxes. Table 12-4 describes the ADOX objects. Table 12-4: ADOX objects Object Catalog Description Represents the collections that describe the schema catalog of a data source. Represents a table stored in a database. This object includes columns, indexes, and keys. Represents a column that might be from a table, index, or key. Represents a table index. Represents a key field: primary, foreign, or unique. Represents a view, which is a set of filtered records from a table. Represents a stored procedure in

public static void main(String[] args) { // sample driver try { int groupSize = 2; // 2 worker threads int num = 35; // compute fib(35) FJTaskRunnerGroup group = new FJTaskRunnerGroup(groupSize); Fib f = new Fib(num); groupinvoke(f); int result = fgetAnswer(); Systemoutprintln("Answer: " + result); } catch (InterruptedException ex) {} // die } }

Notes:

The Common Type System (CTS) is a component of the CLR and provides a common set of data types, each having a common set of behaviors. In Visual Basic, for example,

The class maintains a field holding the argument for which to compute the Fibonacci function Also, we need a variable to hold the result However, as is fairly typical in such classes, there is no need to keep two variables For economy (bearing in mind that many millions of Fib objects might be constructed in the course of a computation), we can microoptimize to use one variable, and overwrite the argument with its result after it is computed (This is the first of several hand-optimizations that are uncomfortably petty, but are shown here in order to demonstrate minor tweaks that can be pragmatically important in constructing efficient parallel programs) The number field is declared as volatile to ensure visibility from other tasks/threads after it is computed (see 227) Here and in subsequent examples, volatile fields are read and/or written only once per task execution, and otherwise held in local variables This avoids interfering with potential compiler optimizations that are otherwise disabled when using volatile Alternatively, we could have synchronized access to the number field But there is no good reason to do so The use of volatile fields is much more common in lightweight parallel task frameworks than in general-purpose concurrent programming Tasks usually do not require other synchronization and control mechanics, yet often need to communicate results via field access The most common reason for using synchronized instead of volatile is to deal with arrays Individual array elements cannot be declared as volatile Processing arrays within synchronized methods or blocks is the simplest way to ensure visibility of array updates, even in the typical case in which locking is not

otherwise required An occasionally attractive alternative is instead to create arrays each of whose elements is a forwarding object with volatile fields The method isDone returns true after the completion of a run method that has been executed via invoke or coInvoke It is used as a guard in getAnswer to help detect programming errors that could occur if the ultimate consumer of an answer tries to access it prematurely (There is no chance of this happening here, but this safeguard helps avoid unintended usages) The sequentialThreshold constant establishes granularity It represents the balance point at which it is not worth the overhead to create tasks, also reflecting the goal of maintaining good sequential performance For example, on one set of runs on a four-CPU system, setting sequentialThreshold to 13 resulted in a 4% performance degradation versus seqFib for large argument values when using a single worker thread But it sped up by a factor of at least 38 with four worker threads, processing several million Fib tasks per second Rather than wiring in a compile-time constant, we could have defined the threshold as a runtime variable and set it to a value based on the number of CPUs available or other platform characteristics This is useful in task-based programs that do not scale linearly, as is likely to be true even here As the number of CPUs increase, so do communication and resource management costs, which could be balanced by increasing the threshold The parallel analog of recursion is performed via a convenient method, coInvoke(FJTask t, FJTask u), which in turn acts as:

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