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See:
Description
Interface Summary | |
---|---|
Operation<T> | Interface for implementing arbitrary operations to be executed. |
OperationExecutor | Interface for implementing objects that can execute Operation s. |
Pi.BinarySplittingSeries | Terms for the binary splitting series. |
PiAWT.StatusIndicator | Interface to indicate an error status in the application. |
Class Summary | |
---|---|
ApfloatHolder | Simple JavaBean to hold one Apfloat . |
BackgroundOperation<T> | Class for running an Operation in the background in a separate thread. |
LocalOperationExecutor | Class to execute Operation s locally. |
OperationServer | Server for executing Operation s from remote calls. |
Pi | Calculates pi using four different algorithms. |
Pi.AbstractBinarySplittingSeries | Abstract base class for the binary splitting series. |
Pi.BinarySplittingPiCalculator | Class for implementing the binary splitting algorithm. |
Pi.BinarySplittingProgressIndicator | Indicates progress of the pi calculation using the binary splitting algorithm. |
Pi.BorweinPiCalculator | Calculates pi using the Borweins' quartic algorithm. |
Pi.ChudnovskyBinarySplittingSeries | Chudnovskys' algorithm terms for the binary splitting series. |
Pi.ChudnovskyPiCalculator | Basic class for calculating pi using the Chudnovskys' binary splitting algorithm. |
Pi.GaussLegendrePiCalculator | Calculates pi using the Gauss-Legendre algorithm. |
Pi.RamanujanBinarySplittingSeries | Ramanujan's algorithm terms for the binary splitting series. |
Pi.RamanujanPiCalculator | Basic class for calculating pi using the Ramanujan binary splitting algorithm. |
PiApplet | Applet for calculating pi using four different algorithms. |
PiAWT | Graphical AWT elements for calculating pi using four different algorithms. |
PiDistributed | Calculates pi using a cluster of servers. |
PiDistributed.DistributedBinarySplittingPiCalculator | Distributed version of the binary splitting algorithm. |
PiDistributed.DistributedChudnovskyPiCalculator | Class for calculating pi using the distributed Chudnovskys' binary splitting algorithm. |
PiDistributed.DistributedRamanujanPiCalculator | Class for calculating pi using the distributed Ramanujan's binary splitting algorithm. |
PiDistributed.Node | RemoteOperationExecutor that implements the weight property. |
PiGUI | AWT client application for calculating pi using four different algorithms. |
PiParallel | Calculates pi using multiple threads in parallel. |
PiParallel.ParallelBinarySplittingPiCalculator | Parallel version of the binary splitting algorithm. |
PiParallel.ParallelChudnovskyPiCalculator | Class for calculating pi using the parallel Chudnovskys' binary splitting algorithm. |
PiParallel.ParallelRamanujanPiCalculator | Class for calculating pi using the parallel Ramanujan's binary splitting algorithm. |
PiParallel.ThreadLimitedOperation<T> | Class to execute operations while setting ApfloatContext.setNumberOfProcessors(int)
to some value. |
PiParallelApplet | Applet for calculating pi using multiple threads in parallel. |
PiParallelAWT | Graphical AWT elements for calculating pi using multiple threads in parallel. |
PiParallelGUI | AWT client application for calculating pi using multiple threads in parallel. |
RemoteOperationExecutor | Class to call an OperationServer to execute Operation s remotely. |
Sample applications demonstrating apfloat use.
Three different versions of an application for calculating π are
included. The simplest, Pi
runs on one
computer using one processor (and one thread) only. PiParallel
executes multiple threads in parallel and has vastly better performance
on multi-core computers. Finally, PiDistributed
can use multiple separate computers for calculating pi with even
greater processing power.
As a curiosity, two applets are provided for running Pi
and PiParallel
through a graphical user
interface: PiApplet
and PiParallelApplet
,
correspondingly. These programs can also be run as stand-alone
Java applications: PiGUI
and PiParallelGUI
.
Compared to the C++ version of apfloat, the Java version pi calculation program is usually just as fast. Even in worst cases the Java version achieves roughly 50% of the performance of the assembler-optimized C++ versions of apfloat. Modern JVMs are nearly as efficient as optimizing C++ compilers in code generation. The advantage that JVMs have over native C++ compilers is obviously that the JVM generates optimal code for every target architecture and runtime profile automatically, from an intermediate portable binary executable format. With C++, the source code must be compiled and profiled manually for every target architecture, which can be difficult and tedious.
On multi-core computers the Java parallel pi calculator is often significantly faster than the C++ parallel version. The same applies to the distributed pi calculator. Multi-threaded and distributed applications are more efficient to implement in Java due to C++'s historical lack of standard libraries for threading and networking.
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