Performance analysis of electronic structure codes on HPC systems: a case study of SIESTA.
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ABSTRACT:
SUBMITTER: Corsetti F
PROVIDER: S-EPMC3991679 | biostudies-literature | 2014
REPOSITORIES: biostudies-literature
Publications
Performance analysis of electronic structure codes on HPC systems: a case study of SIESTA.
PloS one 20140418 4
We report on scaling and timing tests of the SIESTA electronic structure code for ab initio molecular dynamics simulations using density-functional theory. The tests are performed on six large-scale supercomputers belonging to the PRACE Tier-0 network with four different architectures: Cray XE6, IBM BlueGene/Q, BullX, and IBM iDataPlex. We employ a systematic strategy for simultaneously testing weak and strong scaling, and propose a measure which is independent of the range of number of cores on ...[more]
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Project description:Background and objectives: Siesta, which is a short afternoon nap, is a habit that is commonly practiced in the Mediterranean and tropical areas. Data on the association between siesta and coronary artery disease has been conflicting. A protective effect has been demonstrated in the countries that commonly practice siesta, but a harmful effect has been observed in the countries that infrequently practice the siesta habit. Information on the association between siesta and ischemic stroke has been, however, lacking. Hence, the purpose of our study was to determine the effect of siesta on ischemic stroke. Materials and Methods: This was a case-control study, conducted on the patients with acute ischemic stroke who came for their first follow-up visit to the neurology clinic. Controls were randomly selected from the patients visiting the neurology clinic on the same day as the patients with ischemic stroke. In addition to basic demographics and the occurrence of established stroke risk factors, information about siesta practice was also collected from both groups. A multivariate logistic regression analysis was utilized to determine the relationship between siesta practice and ischemic stroke. Results: A total of 206 patients were recruited from the neurology clinic of King Khalid university hospital; of which only 194 subjects were included in the analysis (98 ischemic stroke cases and 96 controls). The mean age of the participants was 59.68 ± 13.75 years and 98 (50.52%) were male. Interestingly, 43% of the whole study cohort practiced regular siesta. However, when compared to the stroke population, the control group practiced siesta more frequently (30% vs. 56%). In a multivariate logistic regression analysis, hypertension, diabetes mellitus, excess body weight (body mass index > 25 kg/m2) and dyslipidemia were found to increase the risk of ischemic stroke (OR 2.12, 95% CI: 1.02-4.66, p = 0.005; OR 2.72, 95% CI: 1.94-4.88, p = 0.014; OR 2.94, 95% CI: 1.5164-5.7121 p = 0.0014; OR 3.27, 95% CI: 2.42-5.199, p ? 0.001, respectively). On the contrary, the practice of regular siesta lowered the risk of ischemic stroke (OR 0.58, 95% CI: 0.3551-0.9526, p = 0.031). Conclusions: Siesta was associated with a reduced risk for the occurrence of ischemic stroke. Large prospective longitudinal studies should be conducted to verify the protective effect of siesta on stroke.
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Project description:Expanded porphyrins provide a versatile route to molecular switching devices due to their ability to shift between several π-conjugation topologies encoding distinct properties. DFT remains the workhorse for modeling such extended macrocycles, when taking into account their size and huge conformational flexibility. Nevertheless, the stability of Hückel and Möbius conformers depends on a complex interplay of different factors, such as hydrogen bonding, π···π stacking, steric effects, ring strain, and electron delocalization. As a consequence, the selection of an exchange-correlation functional for describing the energy profile of topological switches is very difficult. For these reasons, we have examined the performance of a variety of wave function methods and density functionals for describing the thermochemistry and kinetics of topology interconversions across a wide range of macrocycles. Especially for hexa- and heptaphyrins, the Möbius structures have a stronger degree of static correlation than the Hückel and twisted-Hückel structures, and as a result the relative energies of singly twisted structures are a challenging test for electronic structure methods. Comparison of limited orbital space full CI calculations with CCSD(T) calculations within the same active spaces shows that post-CCSD(T) correlation contributions to relative energies are very minor. At the same time, relative energies are weakly sensitive to further basis set expansion, as proven by the minor energy differences between the extrapolated MP2/CBS energies estimated from cc-pV{T,Q}Z, diffuse-augmented heavy-aug-cc-pV{T,Q}Z and explicitly correlated MP2-F12/cc-pVDZ-F12 calculations. Hence, our CCSD(T) reference values are reasonably well-converged in both 1-particle and n-particle spaces. While conventional MP2 and MP3 yield very poor results, SCS-MP2 and particularly SOS-MP2 and SCS-MP3 agree to better than 1 kcal mol-1 with the CCSD(T) relative energies. Regarding DFT methods, the range-separated double hybrids, such as ωB97M(2) and B2GP-PLYP, outperform other functionals with RMSDs of 0.6 and 0.8 kcal mol-1, respectively. While the original DSD-PBEP86 double hybrid performs fairly poorly for these extended π-systems, the errors drop down to 1.9 kcal mol-1 for the revised revDOD-PBEP86-NL, which eliminates the same-spin correlation energy. Minnesota meta-GGA functionals with high fractions of exact exchange (M06-2X and M08-HX) also perform reasonably well, outperforming more robust and significantly less empirically parametrized functionals like SCAN0-D3.
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Project description:The upcoming exascale era will push the changes in computing architecture from classical CPU-based systems towards hybrid GPU-heavy systems with much higher levels of complexity. While such clusters are expected to improve the performance of certain optimized HPC applications, it will also increase the difficulties for those users who have yet to adapt their codes or are starting from scratch with new programming paradigms. Since there are still no comprehensive automatic assistance mechanisms to enhance application performance on such systems, we propose a support framework for future HPC architectures, called EASEY (Enable exASclae for EverYone). Our solution builds on a layered software architecture, which offers different mechanisms on each layer for different tasks of tuning, including a workflow management system. This enables users to adjust the parameters on each of the layers, thereby enhancing specific characteristics of their codes. We introduce the framework with a Charliecloud-based solution, showcasing the LULESH benchmark on the upper layers of our framework. Our approach can automatically deploy optimized container computations with negligible overhead and at the same time reduce the time a scientist needs to spent on manual job submission configurations.
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Project description:Students often face challenges while learning computer programming because programming languages' logic and visual presentations differ from human thought processes. If the course content does not closely match learners' skill level, the learner cannot follow the learning process, resulting in frustration, low learning motivation, or abandonment. This research proposes a web programming learning recommendation system to provide students with personalized guidance and step-by-step learning planning. The system contains front-end and back-end web development instructions. It can create personalized learning paths to help learners achieve a sense of accomplishment. The system can help learners build self-confidence and improve learning effectiveness. In study 1, the recommendation system was developed based on the personal data and feedback of 41 professional web design engineers. The system uses C4.5 decision tree methods to develop a programming learning recommendation model to provide appropriate learning recommendations and establish personalized learning paths. The test group included 13 beginner programmers. After 4 weeks' programming instructions in front-end and back-end web development, the learners were interviewed to understand their preferences and learning effectiveness. The results show that the effectiveness of the recommendation system is acceptable. In study 2, online real-time feedback and adaptive instruction platform is developed, which is different from the past adaptive curriculums mainly using the Internet platform and only the submitted assignments to determine the newly recommended learning process for students. The study found that the students' learning performance in the adaptive instruction group is better than those in the fixed instruction group.
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Project description:BACKGROUND:The advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high throughput profiling of biological systems in a cost-efficient manner. Modern biological experiments are increasingly becoming both data and computationally intensive and the wealth of publicly available biological data is introducing bioinformatics into the "Big Data" era. For these reasons, the effective application of High Performance Computing (HPC) architectures is becoming progressively more recognized also by bioinformaticians. Here we describe HPC resources provisioning pilot programs dedicated to bioinformaticians, run by the Italian Node of ELIXIR (ELIXIR-IT) in collaboration with CINECA, the main Italian supercomputing center. RESULTS:Starting from April 2016, CINECA and ELIXIR-IT launched the pilot Call "ELIXIR-IT HPC@CINECA", offering streamlined access to HPC resources for bioinformatics. Resources are made available either through web front-ends to dedicated workflows developed at CINECA or by providing direct access to the High Performance Computing systems through a standard command-line interface tailored for bioinformatics data analysis. This allows to offer to the biomedical research community a production scale environment, continuously updated with the latest available versions of publicly available reference datasets and bioinformatic tools. Currently, 63 research projects have gained access to the HPC@CINECA program, for a total handout of ~?8 Millions of CPU/hours and, for data storage, ~?100?TB of permanent and?~?300?TB of temporary space. CONCLUSIONS:Three years after the beginning of the ELIXIR-IT HPC@CINECA program, we can appreciate its impact over the Italian bioinformatics community and draw some considerations. Several Italian researchers who applied to the program have gained access to one of the top-ranking public scientific supercomputing facilities in Europe. Those investigators had the opportunity to sensibly reduce computational turnaround times in their research projects and to process massive amounts of data, pursuing research approaches that would have been otherwise difficult or impossible to undertake. Moreover, by taking advantage of the wealth of documentation and training material provided by CINECA, participants had the opportunity to improve their skills in the usage of HPC systems and be better positioned to apply to similar EU programs of greater scale, such as PRACE. To illustrate the effective usage and impact of the resources awarded by the program - in different research applications - we report five successful use cases, which have already published their findings in peer-reviewed journals.
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