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Articles 1 - 12 of 12
Full-Text Articles in Computer Engineering
Online/Incremental Learning To Mitigate Concept Drift In Network Traffic Classification, Alberto R. De La Rosa
Online/Incremental Learning To Mitigate Concept Drift In Network Traffic Classification, Alberto R. De La Rosa
Open Access Theses & Dissertations
Communication networks play a large role in our everyday lives. COVID19 pandemic in 2020 highlighted their importance as most jobs had to be moved to remote work environments. It is possible that the spread of the virus, the death toll, and the economic consequences would have been much worse without communication networks. To remove sole dependence on one equipment vendor, networks are heterogeneous by design. Due to this, as well as their increasing size, network management has become overwhelming for network managers. For this reason, automating network management will have a significant positive impact. Machine learning and software defined networking …
Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios
Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios
Open Access Theses & Dissertations
Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …
Compound Vision Approach For Autonomous Vehicles Navigation, Michael Mikhael
Compound Vision Approach For Autonomous Vehicles Navigation, Michael Mikhael
Open Access Theses & Dissertations
An analogy can be made between the sensing that occurs in simple robots and drones and that in insects and crustaceans, especially in basic navigation requirements. Thus, an approach in robots/drones based on compound eye vision could be useful. In this research, several image processing algorithms were used to detect and track moving objects starting with images upon which a grid (compound eye image) was superimposed, including contours detection, the second moments of those contours along with the grid applied to the original image, and Fourier Transforms and inverse Fourier Transforms. The latter also provide information about scene or camera …
A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan
A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan
Open Access Theses & Dissertations
Soft robotics is a growing field in robotics research. Heavily inspired by biological systems, these robots are made of softer, non-linear, materials such as elastomers and are actuated using several novel methods, from fluidic actuation channels to shape changing materials such as electro-active polymers. Highly non-linear materials make modeling difficult, and sensors are still an area of active research. These issues have rendered typical control and modeling techniques often inadequate for soft robotics. Reinforcement learning is a branch of machine learning that focuses on model-less control by mapping states to actions that maximize a specific reward signal. Reinforcement learning has …
Dedicated Hardware For Machine/Deep Learning: Domain Specific Architectures, Angel Izael Solis
Dedicated Hardware For Machine/Deep Learning: Domain Specific Architectures, Angel Izael Solis
Open Access Theses & Dissertations
Artificial intelligence has come a very long way from being a mere spectacle on the silver screen in the 1920s [Hml18]. As artificial intelligence continues to evolve, and we begin to develop more sophisticated Artificial Neural Networks, the need for specialized and more efficient machines (less computational strain while maintaining the same performance results) becomes increasingly evident. Though these new techniques, such as Multilayer Perceptrons, Convolutional Neural Networks and Recurrent Neural Networks, may seem as if they are on the cutting edge of technology, many of these ideas are over 60 years old! However, many of these earlier models, at …
Decision Making For Dynamic Systems Under Uncertainty: Predictions And Parameter Recomputations, Leobardo Valera
Decision Making For Dynamic Systems Under Uncertainty: Predictions And Parameter Recomputations, Leobardo Valera
Open Access Theses & Dissertations
In this Thesis, we are interested in making decision over a model of a dynamic system. We want to know, on one hand, how the corresponding dynamic phenomenon unfolds under different input parameters (simulations). These simulations might help researchers to design devices with a better performance than the actual ones. On the other hand, we are also interested in predicting the behavior of the dynamic system based on knowledge of the phenomenon in order to prevent undesired outcomes. Finally, this Thesis is concerned with the identification of parameters of dynamic systems that ensure a specific performance or behavior.
Understanding the …
Computation Offloading Decisions For Reducing Completion Time, Salvador Melendez
Computation Offloading Decisions For Reducing Completion Time, Salvador Melendez
Open Access Theses & Dissertations
Mobile devices are being widely used in many applications such as image processing, computer vision (e.g. face detection and recognition), wearable computing, language translation, and battlefield operations. However, mobile devices are constrained in terms of their battery life, processor performance, storage capacity, and network bandwidth. To overcome these issues, there is an approach called Computation Offloading, also known as cyber-foraging and surrogate computing. Computation offloading consists of migrating computational jobs from a mobile device to more powerful remote computing resources. Upon completion of the job, the results are sent back to the mobile device. However, a decision must be made; …
Efficient, Scalable, Parallel, Matrix-Matrix Multiplication, Enrique Portillo
Efficient, Scalable, Parallel, Matrix-Matrix Multiplication, Enrique Portillo
Open Access Theses & Dissertations
For the past decade, power/energy consumption has become a limiting factor for large-scale and embedded High Performance Computing (HPC) systems. This is especially true for systems that include accelerators, e.g., high-end computing devices, such as Graphics Processing Units (GPUs), with terascale computing capabilities and high power draws that greatly surpass that of multi-core CPUs. Accordingly, improving the node-level power/energy efficiency of an application can have a direct and positive impact on both classes of HPC systems.
The research reported in this thesis explores the use of software techniques to enhance the execution-time and power-consumption performance of applications executed on a …
A Case Study Towards Verification Of The Utility Of Analytical Models In Selecting Checkpoint Intervals, Michael Joseph Harney
A Case Study Towards Verification Of The Utility Of Analytical Models In Selecting Checkpoint Intervals, Michael Joseph Harney
Open Access Theses & Dissertations
As high performance computing (HPC) systems grow larger, with increasing numbers of components, failures become more common. Codes that utilize large numbers of nodes and run for long periods of time must take such failures into account and adopt fault tolerance mechanisms to avoid loss of computation and, thus, system utilization. One of those mechanisms is checkpoint/restart. Although analytical models exist to guide users in the selection of an appropriate checkpoint interval, these models are based on assumptions that may not always be true. This thesis examines some of these assumptions, in particular, the consistency of parameters like Mean Time …
The Application Of Fuzzy Granular Computing For The Analysis Of Human Dynamic Behavior In 3d Space, Murad Mohammad Alaqtash
The Application Of Fuzzy Granular Computing For The Analysis Of Human Dynamic Behavior In 3d Space, Murad Mohammad Alaqtash
Open Access Theses & Dissertations
Human dynamic behavior in space is very complex in that it involves many physical, perceptual and motor aspects. It is tied together at a sensory level by linkages between vestibular, visual and somatosensory information that develop through experience of inertial and gravitational reaction forces. Coordinated movement emerges from the interplay among descending output from the central nervous system, sensory input from the body and environment, muscle dynamics, and the emergent dynamics of the whole neuromusculoskeletal system.
There have been many attempts to directly capture the activities of the neuronal system in human locomotion without the ability to clarify how the …
Development Of Load Balancing Algorithm Based On Analysis Of Multi-Core Architecture On Beowulf Cluster, Damian Valles
Development Of Load Balancing Algorithm Based On Analysis Of Multi-Core Architecture On Beowulf Cluster, Damian Valles
Open Access Theses & Dissertations
In this work, analysis, and modeling were employed to improve the Linux Scheduler for HPC use. The performance throughput of a single compute-node of the 23 node Beowulf cluster, Virgo 2.0, was analyzed to find bottlenecks and limitations that affected performance in the processing hardware where each compute-node consisted of two quad-core processors with eight gigabytes of memory. The analysis was performed using the High Performance Linpack (HPL) benchmark.
In addition, the processing hardware of the compute-node was modeled using an Instruction per Cycle (IPC) metric that was estimated using linear regression. Modeling data was obtained by using the Tuning …
Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea
Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea
Open Access Theses & Dissertations
The main contribution of this dissertation is the development of a method to train a Support Vector Regression (SVR) model for the large-scale case where the number of training samples supersedes the computational resources. The proposed scheme consists of posing the SVR problem entirely as a Linear Programming (LP) problem and on the development of a sequential optimization method based on variables decomposition, constraints decomposition, and the use of primal-dual interior point methods. Experimental results demonstrate that the proposed approach has comparable performance with other SV-based classifiers. Particularly, experiments demonstrate that as the problem size increases, the sparser the solution …