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:ObjectiveElectronic health records (EHRs) were expected to yield numerous benefits. However, early studies found mixed evidence of this. We sought to determine whether widespread adoption of modern EHRs in the US has improved clinical care.MethodsWe studied hospitals reporting performance measures from 2008-2015 in the Centers for Medicare and Medicaid Services Hospital Compare database that also reported having an EHR in the American Hospital Association 2015 IT supplement. Using interrupted time-series analysis, we examined the association of EHR implementation, EHR vendor, and Meaningful Use status with 11 process measures and 30-day hospital readmission and mortality rates for heart failure, pneumonia, and acute myocardial infarction.ResultsA total of 1246 hospitals contributed 8222 hospital-years. Compared to hospitals without EHRs, hospitals with EHRs had significant improvements over time on 5 of 11 process measures. There were no substantial differences in readmission or mortality rates. Hospitals with CPSI EHR systems performed worse on several process and outcome measures. Otherwise, we found no substantial improvements in process measures or condition-specific outcomes by duration of EHR use, EHR vendor, or a hospital's Meaningful Use Stage 1 or Stage 2 status.ConclusionIn this national study of hospitals with modern EHRs, EHR use was associated with better process of care measure performance but did not improve condition-specific readmission or mortality rates regardless of duration of EHR use, vendor choice, or Meaningful Use status. Further research is required to understand why EHRs have yet to improve standard outcome measures and how to better realize the potential benefits of EHR systems.
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Project description:To evaluate the phenotyping performance of three major electronic health record (EHR) components: International Classification of Disease (ICD) diagnosis codes, primary notes, and specific medications.We conducted the evaluation using de-identified Vanderbilt EHR data. We preselected ten diseases: atrial fibrillation, Alzheimer's disease, breast cancer, gout, human immunodeficiency virus infection, multiple sclerosis, Parkinson's disease, rheumatoid arthritis, and types 1 and 2 diabetes mellitus. For each disease, patients were classified into seven categories based on the presence of evidence in diagnosis codes, primary notes, and specific medications. Twenty-five patients per disease category (a total number of 175 patients for each disease, 1750 patients for all ten diseases) were randomly selected for manual chart review. Review results were used to estimate the positive predictive value (PPV), sensitivity, andF-score for each EHR component alone and in combination.The PPVs of single components were inconsistent and inadequate for accurately phenotyping (0.06-0.71). Using two or more ICD codes improved the average PPV to 0.84. We observed a more stable and higher accuracy when using at least two components (mean?±?standard deviation: 0.91?±?0.08). Primary notes offered the best sensitivity (0.77). The sensitivity of ICD codes was 0.67. Again, two or more components provided a reasonably high and stable sensitivity (0.59?±?0.16). Overall, the best performance (Fscore: 0.70?±?0.12) was achieved by using two or more components. Although the overall performance of using ICD codes (0.67?±?0.14) was only slightly lower than using two or more components, its PPV (0.71?±?0.13) is substantially worse (0.91?±?0.08).Multiple EHR components provide a more consistent and higher performance than a single one for the selected phenotypes. We suggest considering multiple EHR components for future phenotyping design in order to obtain an ideal result.
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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:BackgroundRNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process.ResultsIn this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories.Availabilityhttps://github.com/BioinfoUNIBA/REDItools2 .ConclusionsHPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores.
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Project description:Processing from solution is a crucial aspect of organic semiconductors, as it is at the heart of the promise of easy and inexpensive manufacturing of devices. Introducing alkyl side chains is an approach often used to increase solubility and enhance miscibility in blends. The influence of these side chains on the electronic structure, although highly important for a detailed understanding of the structure-function relationship of these materials, is still barely understood. Here, we use time-resolved electron paramagnetic resonance spectroscopy with its molecular resolution to investigate the role of alkyl side chains on the polymer PCDTBT and a series of its building blocks with increasing length. Comparing our results to the non-hexylated compounds allows us to distinguish four different factors determining exciton delocalization. Detailed quantum-chemical calculations (DFT) allows us to further interpret our spectroscopic data and to relate our findings to the molecular geometry. Alkylation generally leads to more localized excitons, most prominent only for the polymer. Furthermore, singlet excitons are more delocalized than the corresponding triplet excitons, despite the larger dihedral angles within the backbone found for the singlet-state geometries. Our results show TREPR spectroscopy of triplet excitons to be well suited for investigating crucial aspects of the structure-function relationship of conjugated polymers used as organic semiconductors on a molecular basis.
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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.
| S-EPMC7446135 | biostudies-literature
Project description:ContextHealthcare Electronic Syndromic Surveillance (ESS) is the systematic collection, analysis and interpretation of ongoing clinical data with subsequent dissemination of results, which aid clinical decision-making.ObjectiveTo evaluate, classify and analyze the diagnostic performance, strengths and limitations of existing acute care ESS systems.Data sourcesAll available to us studies in Ovid MEDLINE, Ovid EMBASE, CINAHL and Scopus databases, from as early as January 1972 through the first week of September 2012.Study selectionProspective and retrospective trials, examining the diagnostic performance of inpatient ESS and providing objective diagnostic data including sensitivity, specificity, positive and negative predictive values.Data extractionTwo independent reviewers extracted diagnostic performance data on ESS systems, including clinical area, number of decision points, sensitivity and specificity. Positive and negative likelihood ratios were calculated for each healthcare ESS system. A likelihood matrix summarizing the various ESS systems performance was created.ResultsThe described search strategy yielded 1639 articles. Of these, 1497 were excluded on abstract information. After full text review, abstraction and arbitration with a third reviewer, 33 studies met inclusion criteria, reporting 102,611 ESS decision points. The yielded I2 was high (98.8%), precluding meta-analysis. Performance was variable, with sensitivities ranging from 21% -100% and specificities ranging from 5%-100%.ConclusionsThere is significant heterogeneity in the diagnostic performance of the available ESS implements in acute care, stemming from the wide spectrum of different clinical entities and ESS systems. Based on the results, we introduce a conceptual framework using a likelihood ratio matrix for evaluation and meaningful application of future, frontline clinical decision support systems.
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