Interface | Description |
---|---|
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 | Description |
---|---|
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. |
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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