HPCwire: Closing the Parallelism Gap with the Chapel Language

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November 19, 2008

Closing the Parallelism Gap with the Chapel Language

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Chapel is a high-level parallel programming language being developed by Cray for DARPA's High Productivity Computing Systems (HPCS) program. The goal of the language is to increase programmer productivity for large-scale computing platforms.

An all-day Chapel tutorial and a joint PGAS tutorial with X10 and UPC were conducted this week at SC08 by Brad Chamberlain, the technical lead for the Chapel language project, along with Steven Deitz, David Iten and Samuel Figueroa. We asked Chamberlain to give us an overview of the language, the rational behind its design, and an update on the current state of the Chapel effort.

HPCwire: What problem is Chapel designed to solve?

Chamberlain: In the broadest terms, Chapel is being designed to make parallel programmers more productive. In designing the language, our goal is to support the elegant expression of parallel algorithms without sacrificing the performance and portability enjoyed by MPI programmers today. This is obviously a challenging goal, yet it's one that we have had successes with previously, and it's a primary motivator in our work with Chapel.

More specifically, we are designing Chapel to be a very general parallel language. If you have any parallel algorithm in mind, you ought to be able to express it in Chapel without running into some limitation in the language that forces you to go back to the parallel programming model that you were using previously. This is a fairly significant departure from many of the previous parallel languages that have inspired our work, in that most of them have tended to address only one specific portion of the parallel computing space -- data parallelism, say -- without offering much for algorithms that require other styles of parallelism such as task-parallelism, concurrent programming, or a combination of all three. Focusing on a restricted problem domain is a reasonable (and wise) approach to take in an academic project, but in order to create a parallel language with any chance of being broadly adopted and used, we believe that greater generality and applicability is necessary.

Chapel's support for general parallel programming also means that the language is applicable to general levels of parallelism within software and hardware. Most applications contain opportunities for parallelism at multiple levels within the program's structure: modules, functions, statements, and expressions. Yet most existing parallel programming models only support a single level of software parallelism -- say, cooperating executables -- requiring the user to mix in additional programming models and notations in order to express parallelism at other levels. This raises a significant barrier to expressing and exposing all of the parallelism within an application. Similarly, parallel computers support concurrency at many levels: across machines, across multiple nodes within a machine, across the processor cores within a node, and even within the core in the form of vector instructions, multithreading, or other forms of instruction-level parallelism. We are designing Chapel's features so that an application's parallelism can take advantage of all of these levels of architectural parallelism.

Finally, Chapel is being designed to solve the generation gap that exists between mainstream and parallel languages. Students today graduate with experience in languages like Java, C#, Perl, Python, and MATLAB, yet if they enter the HPC workforce, they are likely to find themselves programming in Fortran, C, and, if they are lucky, C++. Chapel is being designed to bring some of the concepts and philosophies found in modern mainstream languages into the HPC arena, and to do so without disenfranchising programmers who are most comfortable in traditional languages like C and Fortran. This is a bit of a balancing act, but based on comments from both camps, we are optimistic that we've designed a language that's palatable to both perspectives.

HPCwire: In layman's terms, can you give us a brief overview of the language?

Chamberlain: Chapel has four main feature areas: the base language, its task-parallel features, its data-parallel features, and features for controlling locality. The base language consists of all of the features that you would traditionally expect to find in a sequential programming language: types, variables, expressions, statements, functions, and so forth. We very intentionally decided not to make Chapel an extension of an existing language, yet the base language features should be familiar to anyone who has programmed in languages like C, C++, Java, or Fortran. It's worth mentioning a few of the departures from these languages as well: Chapel has support for iterators in the CLU or Ruby sense of the term -- functions that generate a stream of values during their execution rather than a single return value, making them useful for driving loops. Chapel also supports the option to elide type specifications in many contexts such as variable declarations or formal argument lists. This supports code reuse and exploratory programming as in most scripting languages. Unlike scripting languages, all Chapel variables have a fixed, static type in order to avoid runtime overheads.

Chapel's task-parallel features support the ability to create a number of tasks running concurrently in structured and unstructured ways. These tasks can coordinate with one another through the use of synchronization variables which support a "full/empty" state in addition to their normal value. By default, reads and writes on these synchronization variables block until the variable is full/empty, providing a more elegant means of coordinating than traditional locks and semaphores. Chapel's data parallel features are built around a rich set of array types including multidimensional, strided, sparse, and associative arrays. Parallel loops can be used to iterate over an array's indices or elements, and scalar functions can be promoted which applies them to array values in parallel.

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