Parallel Platform Packages (PPPs)
A Parallel Platform Package (PPP) is used with a particular teaching module and an appropriate corresponding platform resource. Learn more>>
The available PPPs that we provide information about are found in the collection below.
Platform Resources
Most Parallel Platform Package libraries/languages require certain platform resources, such as a cluster or a multicore machine. Information about which platform resource is needed for a particular PPP can be found on the PPP page, or you can learn more about each type of resource.
The PPP Libraries, Languages, and Interfaces Collection
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Computational Model
showing only Shared Memory
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Language Support
Operating System Support
Physical Resource Support
Computational Model Show all Computational Model
Shared Memory
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java.util.concurrent
The standard Java package java.util.concurrent contains utility classes which are useful in implementing concurrent programming in Java. This package includes a few small standardized extensible frameworks, as well as some classes that provide useful functionality and are otherwise tedious or difficult to implement.
OpenMP
Taken from OpenMP's mission statement: "The OpenMP Application Program Interface (API) supports multi-platform shared-memory parallel programming in C/C++ and Fortran on all architectures, including Unix platforms and Windows NT platforms. Jointly defined by a group of major computer hardware and software vendors, OpenMP is a portable, scalable model that gives shared-memory parallel programmers a simple and flexible interface for developing parallel applications for platforms ranging from the desktop to the supercomputer."
Intel Threading Building Blocks
Threading Building Blocks (TBB), created by IntelÂ, offers an approach to implementing parallelism in a C++ program. TBB is a library that helps programmers take advantage of multi-core processor performance without having to be an expert on threading. The library represents a higher-level, task-based parallelism that abstracts platform details and threading mechanisms for scalability and performance.

