Portable run-time support for dynamic object-oriented parallel processing
ACM Transactions on Computer Systems (TOCS)
A flexible operation execution model for shared distributed objects
Proceedings of the 11th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Integrating task and data parallelism using shared objects
ICS '96 Proceedings of the 10th international conference on Supercomputing
Performance evaluation of the Orca shared-object system
ACM Transactions on Computer Systems (TOCS)
A task- and data-parallel programming language based on shared objects
ACM Transactions on Programming Languages and Systems (TOPLAS)
CTK: Configurable Object Abstractions for Multiprocessors
IEEE Transactions on Software Engineering
Approaches for Integrating Task and Data Parallelism
IEEE Concurrency
Interoperability of Data Parallel Runtime Libraries
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
Interoperability of Data Parallel Runtime Libraries
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
Combined scheduling and mapping for scalable computing with parallel tasks
Scientific Programming - Biological Knowledge Discovery and Data Mining
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Archetype data parallel or task parallel applications are well served by contemporary languages. However, for applications containing a balance of task and data parallelism the choice of language is less clear. While there are languages that enable both forms of parallelism, e.g., one can write data parallel programs using a task parallel language, there are few languages which support both. We present a set of data parallel extensions to the Mentat Programming Language (MPL) which allow us to integrate task parallelism, data parallelism, and nested task and data parallelism within a single language on top of a single run time system. The result is an object-oriented language, Braid, that supports both task and data parallelism on MIMD machines. In addition, the data parallel extensions define a language in and of itself which makes a number of contributions to the data parallel programming style. These include subset-level operations (a more general notion of element-level operations), compiler provided iteration within a data parallel data set and the ability to define complex data parallel operations.