Performance Analysis of the NWChem TCE for Different Communication Patterns

Ghosh, Priyanka; Hammond, Jeff R.; Ghosh, Sayan; Chapman, Barbara

doi:10.1007/978-3-319-10214-6_14

Cited by 3 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ma et al studied CCSD(T) performance on several GPU platforms using hybrid CPU-GPU execution [14,15]. Ghosh et al studied the communication performance for TCE [8]. Ozog et al explored a set of static and dynamic scheduling algorithms for block-sparse tensor contractions within the NWChem computational chemistry code [17].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Thread-level parallelization and optimization of NWChem for the Intel MIC architecture

Shan

Williams

Jong

et al. 2015

Proceedings of the Sixth International Workshop on Programming Models and Applications for Multicores and Manycores

View full text Add to dashboard Cite

In the multicore era it was possible to exploit the increase in on-chip parallelism by simply running multiple MPI processes per chip. Unfortunately, manycore processors' greatly increased thread-and data-level parallelism coupled with a reduced memory capacity demand an altogether different approach. In this paper we explore augmenting two NWChem modules, triples correction of the CCSD(T) and Fock matrix construction, with OpenMP in order that they might run efficiently on future manycore architectures. As the next NERSC machine will be a self-hosted Intel MIC (Xeon Phi) based supercomputer, we leverage an existing MIC testbed at NERSC to evaluate our experiments. In order to proxy the fact that future MIC machines will not have a host processor, we run all of our experiments in native mode. We found that while straightforward application of OpenMP to the deep loop nests associated with the tensor contractions of CCSD(T) was sufficient in attaining high performance, significant effort was required to safely and efficiently thread the TEXAS integral package when constructing the Fock matrix. Ultimately, our new MPI+OpenMP hybrid implementations attain up to 65× better performance for the triples part of the CCSD(T) due in large part to the fact that the limited on-card memory limits the existing MPI implementation to a single process per card. Additionally, we obtain up to 1.6× better performance on Fock matrix constructions when compared with the best MPI implementations running multiple processes per card.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Parallelize tce sort: To reduce memory consumption, the 2D and 4D tensors are divided into tiles and stored in a complex hash space [3,8]. Once fetched, their indices need to be permuted to proper order by calling function tce sort.…”

Section: Performance and Further Optimizationmentioning

confidence: 99%

Thread-level parallelization and optimization of NWChem for the Intel MIC architecture

Shan

Williams

Jong

et al. 2015

Proceedings of the Sixth International Workshop on Programming Models and Applications for Multicores and Manycores

View full text Add to dashboard Cite

show abstract

“…J. Mellor-Crummey et al [22] examined the performance of the Challenge Benchmark Suite in CAF 2.0. P. Ghosh et al [17] explored the ordering of one-sided messages to achieve better performance. GPI-2 is an open-source PGAS communication library similar to GASNet [15] and ARMCI [1] and has been used in a number of computational applications and performance studies [26,21,19,18].…”

Section: Related Workmentioning

confidence: 99%

Evaluation of PGAS Communication Paradigms with Geometric Multigrid

Shan

Kamil

Williams

et al. 2014

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

View full text Add to dashboard Cite

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.

show abstract