Browsing Department of Computational and Data Sciences (CDS) by Title
Now showing items 59-78 of 84
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Optimization of Traversal Queries on Distributed Graph Stores
In this era of Big Data Analytics, much of the semi-structured data has inherent interconnectivity between representative entities. These are increasingly being modeled as property graphs because of the semantic advantages ... -
Optimizing Matrix Multiplication for the REDEFINE Many-Core Co-processor
Matrix-matrix multiplication is an important operation for many applications and hence it is required to be parallelized optimally for the architecture the applications will run on. REDE- FINE is a many-core co-processor ... -
Optimizing the Interval-centric Distributed Computing Model for Temporal Graph Algorithms
Graphs with temporal characteristics are increasingly becoming prominent. Their vertices, edges and attributes are annotated with a lifespan, allowing one to add or remove vertices and edges. Such graphs can grow to millions ... -
Parallel Smoothers for Multigrid Method in Heterogeneous CPU-GPU Environment
Real-world applications require the solution of large a sparse system of algebraic equations that arise from the discretization of partial di erential equations with the help of supercomputers. Modern supercomputers are ... -
Prediction of Dynamical Systems by Constraining the Dynamics on the Observational Manifold
Evolution models of dynamical systems posed as differential equations generally do not include all the factors affecting the system. This leads to a mismatch between the model prediction and the observations. In this work, ... -
Projection based Variational Multiscale Methods for Incompressible Navier-Stokes Equations to Model Turbulent Flows in Time-dependent Domains
(2018-06-15)Numerical solution of differential equations having multitude of scales in the solution field is one of the most challenging research areas, but highly demanded in scientific and industrial applications. One of the natural ... -
Relating Representations in Deep Learning and the Brain
Deep Neural Networks (DNN) inspired by the human brain have redefined the state-of-the-art performance in AI during the past decade. Much of the research is still trying to understand and explain the function of these ... -
Reliable and Efficient Application Scheduling on Edge, Fog and Cloud
Cloud computing has emerged in the last decade as a popular distributed computing service offered by commercial providers. Public Clouds offer pay-as-you-go access to elastic resources that can be acquired and released ... -
Scalability Bottleneck Analysis of High Performance Applications
Obtaining high performance and scalability for high performance applications are challenging. There are various bottlenecks including, higher rate of memory access, complex algorithm, high rate of communication, big ... -
Scalable Asynchrony-Tolerant PDE Solver for Multi-GPU Systems
Partial differential equations (PDEs) are used to model various natural phenomena and engineered systems. At conditions of practical interest, these equations are highly non-linear and demand massive computations. Current ... -
Self-Supervised Domain Adaptation Frameworks for Computer Vision Tasks
There is a strong incentive to build intelligent machines that can understand and adapt to changes in the visual world without human supervision. While humans and animals learn to perceive the world on their own, almost ... -
Similarity between Scalar Fields
(2017-10-05)Scientific phenomena are often studied through collections of related scalar fields such as data generated by simulation experiments that are parameter or time dependent . Exploration of such data requires robust measures ... -
Sparsification of Reaction-Diffusion Dynamical Systems on Complex Networks
Graph sparsification is an area of interest in computer science and applied mathematics. Spar- sification of a graph, in general, aims to reduce the number of edges in the network while preserving specific properties of ... -
Spectrum Sensing Receivers for Cognitive Radio
(2018-02-16)Cognitive radios require spectral occupancy information in a given location, to avoid any interference with the existing licensed users. This is achieved by spectrum sensing. Existing narrowband, serial spectrum sensors ... -
Stability Preserving Bisection Algorithms in Reaction-Diffusion Complex Networks
Reaction-Diffusion complex networks are ubiquitous in many pragmatic models of network of interacting nodes with individual dynamics, such as social interactions, neuronal functions, transportation models, ecological ... -
Stabilized finite element schemes for computations of viscoelastic free-surface and two-phase flows
Viscoelastic flows can be found in a wide range of industrial and commercial applications such as enhanced oil recovery, pesticide deposition, medicinal/pharmaceutical sprays, drug delivery, injection molding, polymer ... -
Static Analysis and Dynamic Monitoring of Program Flow on REDEFINE Manycore Processor
Manycore heterogeneous architectures are becoming the promising choice for high-performance computing applications. Multiple parallel tasks run concurrently across different processor cores sharing the same communication ... -
Studies on Kernel Based Edge Detection an Hyper Parameter Selection in Image Restoration and Diffuse Optical Image Reconstruction
(2018-05-25)Computational imaging has been playing an important role in understanding and analysing the captured images. Both image segmentation and restoration has been in-tegral parts of computational imaging. The studies performed ... -
A study on Deep Learning Approaches, Architectures and Training Methods for Crowd Analysis
Analyzing large crowds quickly is one of the highly sought-after capabilities nowadays. Especially in terms of public security and planning, this assumes prime importance. But automated reasoning of crowd images or videos ... -
Theory and Algorithms for sequential non-Gaussian Bayesian filtering and estimation
Seamless integration of dynamical system models with sparse measurements, called as Data Assimilation, is important in many applications like weather forecasting, socio-economics, navigation, and beyond. In order to produce ...