The inverse design of novel molecules with a desirable optoelectronic property requires consideration of the vast chemical spaces associated with varying chemical composition and molecular size. ...First principles-based property predictions have become increasingly helpful for assisting the selection of promising candidate chemical species for subsequent experimental validation. However, a brute-force computational screening of the entire chemical space is decidedly impossible. To alleviate the computational burden and accelerate rational molecular design, we here present an iterative deep learning workflow that combines (i) the density-functional tight-binding method for dynamic generation of property training data, (ii) a graph convolutional neural network surrogate model for rapid and reliable predictions of chemical and physical properties, and (iii) a masked language model. As proof of principle, we employ our workflow in the iterative generation of novel molecules with a target energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO).
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
We present ADIOS 2, the latest version of the Adaptable Input Output (I/O) System. ADIOS 2 addresses scientific data management needs ranging from scalable I/O in supercomputers, to data analysis in ...personal computer and cloud systems. Version 2 introduces a unified application programming interface (API) that enables seamless data movement through files, wide-area-networks, and direct memory access, as well as high-level APIs for data analysis. The internal architecture provides a set of reusable and extendable components for managing data presentation and transport mechanisms for new applications. ADIOS 2 bindings are available in C++11, C, Fortran, Python, and Matlab and are currently used across different scientific communities. ADIOS 2 provides a communal framework to tackle data management challenges as we approach the exascale era of supercomputing.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. ...Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging
distributed data parallelism
in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract
We present two open-source datasets that provide time-dependent density-functional tight-binding (TD-DFTB) electronic excitation spectra of organic molecules. These datasets represent ...predictions of UV-vis absorption spectra performed on optimized geometries of the molecules in their electronic ground state. The GDB-9-Ex dataset contains a subset of 96,766 organic molecules from the original open-source GDB-9 dataset. The ORNL_AISD-Ex dataset consists of 10,502,904 organic molecules that contain between 5 and 71 non-hydrogen atoms. The data reveals the close correlation between the magnitude of the gaps between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), and the excitation energy of the lowest singlet excited state energies quantitatively. The chemical variability of the large number of molecules was examined with a topological fingerprint estimation based on extended-connectivity fingerprints (ECFPs) followed by uniform manifold approximation and projection (UMAP) for dimension reduction. Both datasets were generated using the DFTB+ software on the “Andes” cluster of the Oak Ridge Leadership Computing Facility (OLCF).
We present the Exascale Framework for High Fidelity coupled Simulations (EFFIS), a workflow and code coupling framework developed as part of the Whole Device Modeling Application (WDMApp) in the ...Exascale Computing Project. EFFIS consists of a library, command line utilities, and a collection of run-time daemons. Together, these software products enable users to easily compose and execute workflows that include: strong or weak coupling, in situ (or offline) analysis/visualization/monitoring, command-and-control actions, remote dashboard integration, and more. We describe WDMApp physics coupling cases and computer science requirements that motivate the design of the EFFIS framework. Furthermore, we explain the essential enabling technology that EFFIS leverages: ADIOS for performant data movement, PerfStubs/TAU for performance monitoring, and an advanced COUPLER for transforming coupling data from its native format to the representation needed by another application. Finally, we demonstrate EFFIS using coupled multi-simulation WDMApp workflows and exemplify how the framework supports the project’s needs. We show that EFFIS and its associated services for data movement, visualization, and performance collection does not introduce appreciable overhead to the WDMApp workflow and that the resource-dominant application’s idle time while waiting for data is minimal.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Duplication of the gall bladder is a rare anatomic variation. The incidence is approximately 1 in 4000 in literature. Preoperative identification of such anomaly and its various types is very ...important since it can avoid damage to possible vascular and biliary aberrant anatomy during surgery. My case is a 29-year-old male patient with a complaint of epigastric pain which was on and off type. An abdominal ultrasonogram showed multiple calculi in the gallbladder lumen with normal wall thickness and no evidence of intra or extra-hepatic biliary tree dilatation. Another cystic structure was noted adjacent to it with no intraluminal pathology. Magnetic resonance cholangiopancreatography revealed the duplication of the gallbladder and a common cystic duct for both the cavities draining into a common hepatic duct. Multiple filling defects were noted within one of the cavities. The patient was discharged and advised to follow-up. Two months later the patient presented with an episode of acute cholecystitis which was managed by laparoscopic cholecystectomy. Preoperative radiological identification of this anatomic variation helps in planning the surgery accordingly and can prevent perioperative complications.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objectives: This study aims to know the functional outcomes of intramedullary nailing (IMN) osteosynthesis in long bone shaft fractures among adult patients with stable internal fixation and union. ...Additionally, it seeks to assess the specific and general complications experienced by both groups. Methods: The study was conducted at the Department of Orthopedics, Government Medical College, and Rajindra Hospital in Patiala, spanning from March 2021 to December 2022. It was a prospective, manipulative, controlled study involving a total of 40 cases of tibia diaphyseal fractures that were presented to the orthopedics department. Fractures were classified according to the AO fracture classification. Results: The average time for union in the dynamic group was 15.60 weeks (with a standard deviation of 1.27). A significant statistical difference was observed, favoring the dynamization nailing group (p<0.01), indicating a strong trend toward faster union. Out of the 40 patients, 16 (40%) experienced at least one complication. In conclusion, dynamic IMN osteosynthesis permits micromotion between fracture fragments, directly stimulating bone formation and the development of callus. Conclusion: For closed or open tibial diaphyseal fractures with minimal comminution (types A and B based on the AO classification) up to Gustilo 3A, dynamic IMN assembly is considered a safe and effective treatment option.
Processing large quantities of data is a common scenario for parallel applications. While distributed memory applications are able to improve the performance of their I/O operations by using parallel ...I/O libraries, there is no support for parallel I/O operations for applications using shared-memory programming models such as OpenMP available as of today. This paper presents parallel I/O interfaces for OpenMP. We discuss the rationale of our design decisions, present the interface specification, an implementation within the OpenUH compiler and discuss a number of optimizations performed. We demonstrate the benefits of this approach on different file systems for multiple benchmarks and application scenarios. In most cases, we observe significant improvements in I/O performance as compared to the sequential version. Furthermore, we perform a comparison of the OpenMP I/O functions introduced in this paper to message passing interface I/O, and demonstrate the benefits of the new interfaces.
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CEKLJ, DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Transcatheter aortic valve implantation is the most preferred treatment of aortic stenosis in elderly patients at high surgical risk; however, few data exist on the adoption of transcatheter aortic ...valve implantation for the management of low-flow, low-gradient severe aortic stenosis patients. We present a recent case experience with a 77-year-old man suffering from low-flow, low-gradient, symptomatic severe aortic stenosis with concomitant coronary artery lesions in the left anterior descending and right coronary arteries. He was treated successfully with balloon-expandable transcatheter aortic valve implantation after the percutaneous coronary intervention of the left anterior descending artery and right coronary artery lesion. Post-procedural and 30-day follow-ups showed good functional and hemodynamic improvements with the mean aortic gradient of 3 mmHg (baseline: 30 mmHg) without residual paravalvular leakage. Our first experience with a balloon-expandable transcatheter valve was satisfactory as we observed clinical efficacy and good performance of the balloon-expandable transcatheter aortic valve in low-flow, low-gradient, symptomatic severe AS patients.
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