Titanium Performance and Potential: An NPB Experimental Study

Languages and Compilers for Parallel Computing

Yelick

2014

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Abstract. Large-scale parallel machines are programmed mainly with the single program, multiple data (SPMD) model of parallelism. While this model has advantages of scalability and simplicity, it does not fit well with divide-and-conquer parallelism or hierarchical machines that mix shared and distributed memory. In this paper, we define the recursive single program, multiple data model (RSPMD) that extends SPMD with a hierarchical team mechanism to support hierarchical algorithms and machines. We implement this model in the Titanium language and describe how to eliminate a class of deadlocks by ensuring alignment of collective operations. We present application case studies evaluating the RSPMD model, showing that it enables divide-and-conquer algorithms such as sorting to be elegantly expressed and that team collective operations increase performance of conjugate gradient by up to a factor of two. The model also facilitates optimizations for hierarchical machines, improving scalability of particle in cell by 8x and performance of sorting and a stencil code by up to 40% and 14%, respectively.

Section: Algorithmic Hierarchymentioning

confidence: 99%

Hierarchical Computation in the SPMD Programming Model

Languages and Compilers for Parallel Computing

Yelick

2014

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“…On the other hand, Titanium's multidimensional array library is one of its most productive features [9], allowing one-sided remote access to arrays and one-sided bulk copies of non-contiguous subsets of arrays. These features are especially useful in adaptive block-structured computations; for example, a port of the Chombo adaptive mesh refinement (AMR) application requires an order of magnitude fewer lines in Titanium than in C++/Fortran, largely due to Titanium's array library [15].…”

Section: Background and Related Workmentioning

confidence: 99%

A Local-View Array Library for Partitioned Global Address Space C++ Programs

Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming

Yelick

2014

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Multidimensional arrays are an important data structure in many scientific applications. Unfortunately, built-in support for such arrays is inadequate in C++, particularly in the distributed setting where bulk communication operations are required for good performance. In this paper, we present a multidimensional library for partitioned global address space (PGAS) programs, supporting the one-sided remote access and bulk operations of the PGAS model. The library is based on Titanium arrays, which have proven to provide good productivity and performance. These arrays provide a local view of data, where each rank constructs its own portion of a global data structure, matching the local view of execution common to PGAS programs and providing maximum flexibility in structuring global data. Unlike Titanium, which has its own compiler with array-specific analyses, optimizations, and code generation, we implement multidimensional arrays solely through a C++ library. The main goal of this effort is to provide a library-based implementation that can match the productivity and performance of a compiler-based approach. We implement the array library as an extension to UPC++, a C++ library for PGAS programs, and we extend Titanium arrays with specializations to improve performance. We evaluate the array library by porting four Titanium benchmarks to UPC++, demonstrating that it can achieve up to 25% better performance than Titanium without a significant increase in programmer effort.

“…K. Datta et al [10] studied the performance and potential of Titanium, the language on which the UPC++ array library is based. They argued that Titanium provides greater expressive power than conventional approaches, enabling concise and expressive code and minimizing time to solution without sacrificing performance.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of PGAS Communication Paradigms with Geometric Multigrid

Shan

Proceedings of the 8th International Conference on Partitioned Global Address Space Programming Models

Williams

et al. 2014

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Partitioned Global Address Space (PGAS) languages and one-sided communication enable application developers to select the communication paradigm that balances the performance needs of applications with the productivity desires of programmers. In this paper, we evaluate three different one-sided communication paradigms in the context of geometric multigrid using the miniGMG benchmark. Although miniGMG's static, regular, and predictable communication does not exploit the ultimate potential of PGAS models, multigrid solvers appear in many contemporary applications and represent one of the most important communication patterns. We use UPC++, a PGAS extension of C++, as the vehicle for our evaluation, though our work is applicable to any of the existing PGAS languages and models. We compare performance with the highly tuned MPI baseline, and the results indicate that the most promising approach towards achieving performance and ease of programming is to use high-level abstractions, such as the multidimensional arrays provided by UPC++, that hide data aggregation and messaging in the runtime library.