BSPlib: The BSP programming library

Hill, Jonathan M. D.; McColl, Bill; Ştefănescu, Dan; Goudreau, Mark W.; Lang, Kévin; Rao, Satish; Suel, Torsten; Tsantilas, Thanasis; Bisseling, Rob H.

doi:10.1016/s0167-8191(98)00093-3

Cited by 234 publications

(140 citation statements)

References 31 publications

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“…We have run our experiments, coded in Fortran using BSPlib [14], in an IBM SP2 computer. To implement these methods, we have considered the Matrix E j,l is partitioned accordingly with M j,l changing L j,l by I and 4I by the zero matrix.…”

Section: Numerical Resultsmentioning

confidence: 99%

Sequential and parallel synchronous alternating iterative methods

Climent¹,

Perea²,

Tortosa³

et al. 2003

Math. Comp.

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Abstract. The so-called parallel multisplitting nonstationary iterative Model A was introduced by Bru, Elsner, and Neumann [Linear Algebra and its Applications 103:175-192 (1988)] for solving a nonsingular linear system AÜ = using a weak nonnegative multisplitting of the first type. In this paper new results are introduced when A is a monotone matrix using a weak nonnegative multisplitting of the second type and when A is a symmetric positive definite matrix using a P -regular multisplitting. Also, nonstationary alternating iterative methods are studied. Finally, combining Model A and alternating iterative methods, two new models of parallel multisplitting nonstationary iterations are introduced. When matrix A is monotone and the multisplittings are weak nonnegative of the first or of the second type, both models lead to convergent schemes. Also, when matrix A is symmetric positive definite and the multisplittings are P -regular, the schemes are also convergent.

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Section: Numerical Resultsmentioning

confidence: 99%

Sequential and parallel synchronous alternating iterative methods

Climent¹,

Perea²,

Tortosa³

et al. 2003

Math. Comp.

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“…To ease the development and analysis of parallel programs, the BSP programming model was implemented as API libraries [17], and recently enhanced to simplify programming on GPU architectures [18]. These developments help to create scientific applications in massively parallel environments computing in an easier and better way.…”

Section: It Is Common To Present the Parameters Of The Bsp Model As Amentioning

confidence: 99%

A Simple BSP-based Model to Predict Execution Time in GPU Applications

Amarís

Cordeiro

Goldman

et al. 2015

2015 IEEE 22nd International Conference on High Performance Computing (HiPC)

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Abstract-Models are useful to represent abstractions of software and hardware processes. The Bulk Synchronous Parallel (BSP) is a bridging model for parallel computation that allows algorithmic analysis of programs on parallel computers using performance modeling. The main idea of BSP model is the treatment of communication and computation as abstractions of a parallel system. Meanwhile, the use of GPU devices are becoming more widespread and they are currently capable of performing efficient parallel computation for applications that can be decomposed on thousands of simple threads. However, few models for predicting application execution time on GPUs have been proposed.In this work we present a simple and intuitive BSP-based model for predicting the CUDA application execution times on GPUs. The model is based on the number of computations and memory accesses of the GPU, with additional information on cache usage obtained from profiling. Scalability, divergence, effect of optimizations and differences of architectures are adjusted by a single parameter. We evaluated our model using two applications and six different boards. We showed by using profile information for a single board, that the model is general enough to predict the execution time of an application with different input sizes and on different boards with the same architecture. Our model predictions were within 0.8 to 1.2 times the measured execution times, which are reasonable for such a simple model. These results indicate that the model is good enough to generalize the predictions for different problem sizes and GPU configurations.

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“…Unlike BSPlib [14] or PUB [5] we do not distinguish communication phase and synchronization barrier. The two primitives put and at are used to program the communication phase implicitly and immediately followed by a synchronization barrier.…”

Section: Functional Bulk Synchronous Parallelismmentioning

confidence: 99%