Parallel Programming

Fortress is a programming language designed for high-performance computing. It was created by Sun Microsystems with funding from DARPA's High Productivity Computing Systems project. One of the language designers is Guy L. Steele Jr., whose previous work includes Scheme, Common Lisp, and Java.

Chapel, the Cascade High Productivity Language, is a parallel programming language developed by Cray.[1] It is being developed as part of the Cray Cascade project, a participant in DARPA's High Productivity Computing Systems (HPCS) program, which had the goal of increasing supercomputer productivity by the year 2010. Chapel aims to improve the programmability of parallel computers in general and the Cascade system in particular, by providing a higher level of expression than current programming languages do and by improving the separation between algorithmic expression and data structure implementation details.

Chapel supports a multithreaded parallel programming model at a high level by supporting abstractions for data parallelism, task parallelism, and nested parallelism. It enables optimizations for the locality of data and computation in the program via abstractions for data distribution and data-driven placement of subcomputations. It allows for code reuse and generality through object-oriented concepts and generic programming features. For instance, Chapel allows for the declaration of locales.[2]

While Chapel borrows concepts from many preceding languages, its parallel concepts are most closely based on ideas from High Performance Fortran (HPF), ZPL, and the Cray MTA's extensions to Fortran and C.

It is being developed as an open source project, under the BSD license.[3]

X10 is a programming language being developed by IBM at the Thomas J. Watson Research Center as part of the Productive, Easy-to-use, Reliable Computing System (PERCS) project funded by DARPA's High Productivity Computing Systems (HPCS) program. Its primary authors are Kemal Ebcioğlu, Vijay Saraswat, and Vivek Sarkar.[1]

X10 is designed specifically for parallel programming using the partitioned global address space (PGAS) model. A computation is divided among a set of places, each of which holds some data and hosts one or more activities that operate on those data. It has a constrained type system for object-oriented programming, a form of dependent types. Other features include user-defined primitive struct types; globally distributed arrays, and structured and unstructured parallelism.[2]

X10 uses the concept of parent and child relationships for activities to prevent the lock stalemate that can occur when two or more processes wait for each other to finish before they can complete. An activity may spawn one or more child activities, which may themselves have children. Children cannot wait for a parent to finish, but a parent can wait for a child using the finish command.[3]

Unified Parallel C (UPC) is an extension of the C programming language designed for high-performance computing on large-scale parallel machines, including those with a common global address space (SMP and NUMA) and those with distributed memory (e.g. clusters). The programmer is presented with a single shared, partitioned address space, where variables may be directly read and written by any processor, but each variable is physically associated with a single processor. UPC uses a Single Program Multiple Data (SPMD) model of computation in which the amount of parallelism is fixed at program startup time, typically with a single thread of execution per processor.

In order to express parallelism, UPC extends ISO C 99 with the following constructs:

* An explicitly parallel execution model
* A shared address space
* Synchronization primitives and a memory consistency model
* Explicit communication primitives, e.g. upc_memput
* Memory management primitives

The UPC language evolved from experiences with three other earlier languages that proposed parallel extensions to ISO C 99: AC, Split-C, and Parallel C Preprocessor (PCP). UPC is not a superset of these three languages, but rather an attempt to distill the best characteristics of each. UPC combines the programmability advantages of the shared memory programming paradigm and the control over data layout and performance of the message passing programming paradigm.

Coarray Fortran (CAF), formerly known as F--, is an extension of Fortran 95/2003 for parallel processing created by Robert Numrich and John Reid in the 1990s. The Fortran 2008 standard (ISO/IEC 1539-1:2010) now includes coarrays (spelt without hyphen), as decided at the May 2005 meeting of the ISO Fortran Committee; the syntax in the Fortran 2008 standard is slightly different from the original CAF proposal.

A CAF program is interpreted as if it were replicated a number of times and all copies were executed asynchronously. Each copy has its own set of data objects and is termed an image. The array syntax of Fortran is extended with additional trailing subscripts in square brackets to provide a concise representation of references to data that is spread across images.

The CAF extension has been available for a long time and was implemented in some Fortran compilers such as those from Cray (since release 3.1). Since the inclusion of coarrays in the Fortran 2008 standard, the number of implementations is growing. The first open-source compiler which implemented coarrays as specified in the Fortran 2008 standard for Linux architectures is G95.