29 citations · 59 across the 17 of their papers we have counts for
17 papers
Scalability of the asynchronous discontinuous Galerkin method for compressible flow simulations
Shubham Kumar Goswami, Dapse Vidyesh, Konduri Aditya
The scalability of time-dependent partial differential equation (PDE) solvers based on the discontinuous Galerkin (DG) method is increasingly limited by data communication and sync…
A graph neural network based chemical mechanism reduction method for combustion applications
Manuru Nithin Padiyar, Priyabrat Dash, Konduri Aditya
Direct numerical simulations of turbulent reacting flows involving millions of grid points and detailed chemical mechanisms with hundreds of species and thousands of reactions are…
Modeling subgrid scale production rates on complex meshes using graph neural networks
Priyabrat Dash, Mathis Bode, Konduri Aditya
Large-eddy simulations (LES) require closures for filtered production rates because the resolved fields do not contain all correlations that govern chemical source terms. We develo…
Super-resolution of turbulent reacting flows on complex meshes using graph neural networks
Priyabrat Dash, Konduri Aditya, Christos E. Frouzakis +1
State-of-the-art deep learning models have been extensively utilized to reconstruct small-scale structures from coarse-grained data in turbulent flows. However, their application h…
ChemXDyn: Dynamics-informed species and reaction detection methodology from atomistic simulations
Raj Maddipati, Dhruthi Boddapati, Elangannan Arunan +2
Accurate identification of chemical species and reaction pathways from molecular dynamics (MD) trajectories is a prerequisite for deriving predictive chemical-kinetic models and fo…
Structure of Turbulent Radiative Mixing Layers
Prateek Sharma, Arnav Kumar, Dipayan Datta +3
Turbulent radiative mixing layers (TRMLs), where shear-driven turbulence mixes dense and diffuse gas into rapidly cooling intermediate-temperature gas, are ubiquitous in the inters…
Accuracy and scalability of asynchronous compressible flow solver for transitional flows
Aswin Kumar Arumugam, Shubham Kumar Goswami, Nagabhushana Rao Vadlamani +1
To overcome the communication bottlenecks observed in state-of-the-art parallel time-dependent flow solvers at extreme scales, an asynchronous computing approach that relaxes commu…
An a-posteriori analysis of co-kurtosis PCA based dimensionality reduction using a neural ODE solver
Tadikonda Shiva Sai, Hemanth Kolla, Konduri Aditya
A low-dimensional representation of thermochemical scalars based on cokurtosis principal component analysis (CoK-PCA) has been shown to effectively capture stiff chemical dynamics…
An asynchronous discontinuous Galerkin method for combustion simulations
Aswin Kumar Arumugam, Konduri Aditya
The discontinuous Galerkin (DG) method has been widely considered in recent years to develop scalable flow solvers for its ability to handle discontinuities, such as shocks and det…
An asynchronous discontinuous Galerkin method for massively parallel PDE solvers
Shubham Kumar Goswami, Konduri Aditya
The discontinuous Galerkin (DG) method is widely being used to solve hyperbolic partial differential equations (PDEs) due to its ability to provide high-order accurate solutions in…
A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks
Dibyajyoti Nayak, Anirudh Jonnalagadda, Uma Balakrishnan +2
For turbulent reacting flows, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the compu…
Level Set Restricted Voronoi Tessellation for Large scale Spatial Statistical Analysis
Tyson Neuroth, Martin Rieth, Konduri Aditya +3
Spatial statistical analysis of multivariate volumetric data can be challenging due to scale, complexity, and occlusion. Advances in topological segmentation, feature extraction, a…
A co-kurtosis based dimensionality reduction method for combustion datasets
Anirudh Jonnalagadda, Shubham P. Kulkarni, Akash Rodhiya +2
Principal Component Analysis (PCA) is a dimensionality reduction technique widely used to reduce the computational cost associated with numerical simulations of combustion phenomen…
Diva: A Declarative and Reactive Language for In-Situ Visualization
Qi Wu, Tyson Neuroth, Oleg Igouchkine +3
The use of adaptive workflow management for in situ visualization and analysis has been a growing trend in large-scale scientific simulations. However, coordinating adaptive workfl…
A scalable weakly-synchronous algorithm for solving partial differential equations
Konduri Aditya, Tobias Gysi, Grzegorz Kwasniewski +3
Synchronization overheads pose a major challenge as applications advance towards extreme scales. In current large-scale algorithms, synchronization as well as data communication de…
Anomaly detection in scientific data using joint statistical moments
Konduri Aditya, Hemanth Kolla, W. Philip Kegelmeyer +3
We propose an anomaly detection method for multi-variate scientific data based on analysis of high-order joint moments. Using kurtosis as a reliable measure of outliers, we suggest…
High-order asynchrony-tolerant finite difference schemes for partial differential equations
Konduri Aditya, Diego A. Donzis
Synchronizations of processing elements (PEs) in massively parallel simulations, which arise due to communication or load imbalances between PEs, significantly affect the scalabili…