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

Kamil, Amir; Yelick, Katherine

doi:10.1145/2627373.2627378

Cited by 11 publications

(6 citation statements)

References 11 publications

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“…DASH also comes with a set of optimized parallel algorithms akin to those found in the STL while UPC++ offers no such algorithms. DASH also supports globalview multidimensional distributed arrays with flexible data distribution schemes, UPC++ only supports a local view multidimensional array inspired by Titanium [37].…”

Section: Related Workmentioning

confidence: 99%

DASH: A C++ PGAS Library for Distributed Data Structures and Parallel Algorithms

Fuerlinger

Fuchs

Kowalewski

2016

2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference On

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Abstract-We present DASH, a C++ template library that offers distributed data structures and parallel algorithms and implements a compiler-free PGAS (partitioned global address space) approach. DASH offers many productivity and performance features such as global-view data structures, efficient support for the owner-computes model, flexible multidimensional data distribution schemes and inter-operability with STL (standard template library) algorithms. DASH also features a flexible representation of the parallel target machine and allows the exploitation of several hierarchically organized levels of locality through a concept of Teams. We evaluate DASH on a number of benchmark applications and we port a scientific proxy application using the MPI two-sided model to DASH. We find that DASH offers excellent productivity and performance and demonstrate scalability up to 9800 cores.

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Section: Related Workmentioning

confidence: 99%

DASH: A C++ PGAS Library for Distributed Data Structures and Parallel Algorithms

Fuerlinger

Fuchs

Kowalewski

2016

2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference On

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“…It includes features such as global memory management, one-sided communication, remote function invocation and multidimensional arrays [3]. 1) Multidimensional Arrays: A general multidimensional array abstraction is very important for scientific applications, but unfortunately, the support for multidimensional arrays in the C++ standard library is limited [9]. The UPC++ library implements a multidimensional array abstraction that incorporates many features that are useful in the PGAS setting, and we build our own distributed array representation on top of UPC++ multidimensional arrays.…”

Section: Upc++ and Multidimensional Arraysmentioning

confidence: 99%

A Hartree-Fock Application Using UPC++ and the New DArray Library

Ozog

Kamil

Hargrove

et al. 2016

2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)

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Abstract-The Hartree-Fock (HF) method is the fundamental first step for incorporating quantum mechanics into manyelectron simulations of atoms and molecules, and it is an important component of computational chemistry toolkits like NWChem. The GTFock code is an HF implementation that, while it does not have all the features in NWChem, represents crucial algorithmic advances that reduce communication and improve load balance by doing an up-front static partitioning of tasks, followed by work stealing whenever necessary.To enable innovations in algorithms and exploit next generation exascale systems, it is crucial to support quantum chemistry codes using expressive and convenient programming models and runtime systems that are also efficient and scalable. This paper presents an HF implementation similar to GTFock using UPC++, a partitioned global address space model that includes flexible communication, asynchronous remote computation, and a powerful multidimensional array library. UPC++ offers runtime features that are useful for HF such as active messages, a rich calculus for array operations, hardwaresupported fetch-and-add, and functions for ensuring asynchronous runtime progress. We present a new distributed array abstraction, DArray, that is convenient for the kinds of randomaccess array updates and linear algebra operations on blockdistributed arrays with irregular data ownership. We analyze the performance of atomic fetch-and-add operations (relevant for load balancing) and runtime attentiveness, then compare various techniques and optimizations for each. Our optimized implementation of HF using UPC++ and the DArrays library shows up to 20% improvement over GTFock with Global Arrays at scales up to 24,000 cores.

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“…To support non-contiguous data transfer, UPC ++ provides a multidimensional domain and array library [11] that can automatically compute the intersection of two boxes and fill in the ghost regions. A version of HPGMG-FV that uses this domain and array library is currently under development.…”

Section: Scalabilitymentioning

confidence: 99%

Implementing High-Performance Geometric Multigrid Solver with Naturally Grained Messages

Shan

Williams

Kamil

et al. 2015

2015 9th International Conference on Partitioned Global Address Space Programming Models

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Abstract-Structured-grid linear solvers often require manual packing and unpacking of communication data to achieve high performance. Orchestrating this process efficiently is challenging, labor-intensive, and potentially error-prone. In this paper, we explore an alternative approach that communicates the data with naturally grained message sizes without manual packing and unpacking. This approach is the distributed analogue of shared-memory programming, taking advantage of the global address space in PGAS languages to provide substantial programming ease. However, its performance may suffer from the large number of small messages. We investigate the runtime support required in the UPC ++ library for this naturally grained version to close the performance gap between the two approaches and attain comparable performance at scale using the High-Performance Geometric Multgrid (HPGMG-FV) benchmark as a driver.

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

Cited by 11 publications

References 11 publications

DASH: A C++ PGAS Library for Distributed Data Structures and Parallel Algorithms

DASH: A C++ PGAS Library for Distributed Data Structures and Parallel Algorithms

A Hartree-Fock Application Using UPC++ and the New DArray Library

Implementing High-Performance Geometric Multigrid Solver with Naturally Grained Messages

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