Multiparadigm, multilingual interoperability: Experience with converse

Kalé, Laxmikant V.; Bhandarkar, Milind; Brunner, Richard; Yelon, Joshua

doi:10.1007/3-540-64359-1_682

Cited by 13 publications

(10 citation statements)

References 13 publications

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“…NAMD is implemented using the Converse [8] runtime system, and the major components of NAMD are written in Charm++ [10], a parallel version of C++. Converse supplies several important capabilities for parallel applications.…”

Section: Runtime Support For Dynamic Computationmentioning

confidence: 99%

Scalable Molecular Dynamics for Large Biomolecular Systems

Brunner¹,

Phillips²,

Kalé³

2000

ACM/IEEE SC 2000 Conference (SC'00)

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We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far.The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

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Section: Runtime Support For Dynamic Computationmentioning

confidence: 99%

Scalable Molecular Dynamics for Large Biomolecular Systems

Brunner¹,

Phillips²,

Kalé³

2000

ACM/IEEE SC 2000 Conference (SC'00)

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“…Eventually, a limit is reached in which the communication overhead exceeds the useful computational work, at which point additional processors can no longer be used effectively. In this article, we introduce a new parallelization strategy for CPAIMD based on the concept of virtualization , as embodied in the Charm++ runtime system 47, 48. Virtualization simply means that computational work to be done is divided into individual concurrent entities or “threads,” also called virtual processors (VPs), that are then mapped onto the physical processors by the runtime system (rather than by the programmer).…”

Section: Introductionmentioning

confidence: 99%

Scalable fine‐grained parallelization of plane‐wave–based ab initio molecular dynamics for large supercomputers

et al. 2004

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Many systems of great importance in material science, chemistry, solid-state physics, and biophysics require forces generated from an electronic structure calculation, as opposed to an empirically derived force law to describe their properties adequately. The use of such forces as input to Newton's equations of motion forms the basis of the ab initio molecular dynamics method, which is able to treat the dynamics of chemical bond-breaking and -forming events. However, a very large number of electronic structure calculations must be performed to compute an ab initio molecular dynamics trajectory, making the efficiency as well as the accuracy of the electronic structure representation critical issues. One efficient and accurate electronic structure method is the generalized gradient approximation to the Kohn-Sham density functional theory implemented using a plane-wave basis set and atomic pseudopotentials. The marriage of the gradient-corrected density functional approach with molecular dynamics, as pioneered by Car and Parrinello (R. M. Parrinello, Phys Rev Lett 1985, 55, 2471), has been demonstrated to be capable of elucidating the atomic scale structure and dynamics underlying many complex systems at finite temperature. However, despite the relative efficiency of this approach, it has not been possible to obtain parallel scaling of the technique beyond several hundred processors on moderately sized systems using standard approaches. Consequently, the time scales that can be accessed and the degree of phase space sampling are severely limited. To take advantage of next generation computer platforms with thousands of processors such as IBM's BlueGene, a novel scalable parallelization strategy for Car-Parrinello molecular dynamics is developed using the concept of processor virtualization as embodied by the Charmϩϩ parallel programming system. Charmϩϩ allows the diverse elements of a Car-Parrinello molecular dynamics calculation to be interleaved with low latency such that unprecedented scaling is achieved. As a benchmark, a system of 32 water molecules, a common system size employed in the study of the aqueous solvation and chemistry of small molecules, is shown to scale on more than 1500 processors, which is impossible to achieve using standard approaches. This degree of parallel scaling is expected to open new opportunities for scientific inquiry.

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“…Converse [19] provides the tools for implementing different paradigms in a message-driven system with objectbased VPs. Apart from providing a scheduler on each processor, Converse also provides a messaging framework with primitives for point-to-point communication and multicasts, and methods for handling a message on the receiving processor.…”

Section: A Multi-paradigm Runtime Systemmentioning

confidence: 99%

“…Our approach relies on Converse [19], an ARTS which fully realizes the tightly coupled interoperability of multiple paradigms. Converse meets many of the goals mentioned in a recent report from Berkeley [3], including the need for models to be independent of the number of processors, and it alleviates cognitive load on programmers by performing automatic resource management.…”

Section: Introductionmentioning

confidence: 99%

A Case Study in Tightly Coupled Multi-paradigm Parallel Programming

Chakravorty

Becker

Wilmarth

et al. 2008

Languages and Compilers for Parallel Computing

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Abstract. Programming paradigms are designed to express algorithms elegantly and efficiently. There are many parallel programming paradigms, each suited to a certain class of problems. Selecting the best parallel programming paradigm for a problem minimizes programming effort and maximizes performance. Given the increasing complexity of parallel applications, no one paradigm may be suitable for all components of an application. Today, most parallel scientific applications are programmed with a single paradigm and the challenge of multi-paradigm parallel programming remains unmet in the broader community. We believe that each component of a parallel program should be programmed using the most suitable paradigm. Furthermore, it is not sufficient to simply bolt modules together: programmers should be able to switch between paradigms easily, and resource management across paradigms should be automatic. We present a pre-existing adaptive runtime system (ARTS) and show how it can be used to meet these challenges by allowing the simultaneous use of multiple parallel programming paradigms and supporting resource management across all of them. We discuss the implementation of some common paradigms within the ARTS and demonstrate the use of multiple paradigms within our feature-rich unstructured mesh framework. We show how this approach boosts performance and productivity for an application developed using this framework.

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Multiparadigm, multilingual interoperability: Experience with converse

Cited by 13 publications

References 13 publications

Scalable Molecular Dynamics for Large Biomolecular Systems

Scalable Molecular Dynamics for Large Biomolecular Systems

Scalable fine‐grained parallelization of plane‐wave–based ab initio molecular dynamics for large supercomputers

A Case Study in Tightly Coupled Multi-paradigm Parallel Programming

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