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Stochastic Learning of computational resource Usage as Graph-Structured Multimarginal Schrodinger Bridge

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2025年

作者： Bondar, Georgiy A. Gifford, Robert Phan, Linh Thi Xuan Halder, Abhishek Univ Calif Santa Cruz Dept Appl Math Santa Cruz CA 95064 USA Univ Penn Dept Comp & Informat Sci Philadelphia PA 19104 USA Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA

We propose to learn the time-varying stochastic computational resource usage of software as a graph-structured Schr & ouml;dinger bridge problem (SBP). In general, learning the computational resource usage from data is challenging because resources, such as the number of CPU instructions and the number of last level cache requests are both time-varying and statistically correlated. Our proposed method enables learning the joint time-varying stochasticity in computational resource usage from the measured profile snapshots in a nonparametric manner. The method can be used to predict the most-likely time-varying distribution of computational resource availability at a desired time. We provide detailed algorithms for stochastic learning in both single-core and multicore cases, discuss the convergence guarantees, computational complexities, and demonstrate their practical use in two case studies: a single-core nonlinear model predictive controller (NMPC) and a synthetic multicore software.

关键词： Multicore processing Stochastic processes Software Vectors Tensors Indexes Bridges Hardware Dynamic scheduling Predictive models computational resource multicore hardware multimarginal Schr & ouml dinger bridge stochastic learning

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A joint computational and resource allocation model for fast parallel data processing in fog computing

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JOURNAL OF SUPERCOMPUTING 2022年第10期78卷 12662-12685页

作者： Lakzaei, Mahmood Sattari-Naeini, Vahid Molahosseini, Amir Sabbagh Javadpour, Amir Islamic Azad Univ Dept Comp Engn Kerman Branch Kerman Iran Shahid Bahonar Univ Kerman Dept Comp Engn Kerman Iran Guangzhou Univ Sch Comp Sci & Technol Guangzhou 510006 Peoples R China

Fog computing can be an effective way to improve quality of services and solve network problems, with the demand for real-time, latency-sensitive applications increasing as well as limitations such as network bandwidth and Internet of Things users' resources. Due to the fact that different tasks in a network can create overhead that can reduce the quality of service, dynamic voltage, and frequency scaling along with a ranking function and a high number of physical and virtual machines were used in this research. A profit function phase is used to analyze network tasks in order to improve QoS by sending them to physical machines and sending them via the network to physical machines. The simulation results demonstrate that this method is the most effective in allocating radio and computational resources to IoT devices in fog computing. A comparison is presented in the results section between the proposed method and the SPA, Markov-Fog, and TRAM methods. Criteria for evaluating performance include the response time for heterogeneous environments, energy consumption against tasks and users, memory processing, energy consumption for physical and virtual machines, and network profitability.

关键词： Fog computing IoT Cloud computing computational resource Quality of service DVFS

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Overcoming computational resource Limitations in Deep Learning for Healthcare: Strategies Targeting Data, Model, and Computing

Medicine Advances

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Medicine Advances 2025年

作者： Han Yuan Duke-NUS Medical School National University of Singapore Singapore

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computational resources for identification of cancer biomarkers from omics data

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BRIEFINGS IN FUNCTIONAL GENOMICS 2021年第4期20卷 213-222页

作者： Kaur, Harpreet Kumar, Rajesh Lathwal, Anjali Raghava, Gajendra P. S. CSIR Inst Microbial Technol Bioinformat Ctr Bioinformat 39-A Chandigarh 160036 India CSIR Inst Microbial Technol Bioinformat Ctr Life Sci 39-A Chandigarh 160036 India Indraprastha Inst Informat Technol Dept Computat Biol Computat Biol New Delhi 110020 India Indraprastha Inst Informat Technol Dept Computat Biol Okhla Ind EstatePhase 3 New Delhi 110020 India

Cancer is one of the most prevailing, deadly and challenging diseases worldwide. The advancement in technology led to the generation of different types of omics data at each genome level that may potentially improve the current status of cancer patients. These data have tremendous applications in managing cancer effectively with improved outcome in patients. This review summarizes the various computational resources and tools housing several types of omics data related to cancer. Major categorization of resources includes-cancer-associated multiomics data repositories, visualization/analysis tools for omics data, machine learning-based diagnostic, prognostic, and predictive biomarker tools, and data analysis algorithms employing the multiomics data. The review primarily focuses on providing comprehensive information on the open-source multiomics tools and data repositories, owing to their broader applicability, economic-benefit and usability. Sections including the comparative analysis, tools applicability and possible future directions have also been discussed in detail. We hope that this information will significantly benefit the researchers and clinicians, especially those with no sound background in bioinformatics and who lack sufficient data analysis skills to interpret something from the plethora of cancer-specific data generated nowadays.

关键词： omics data cancer biomarker web server computational resource diagnosis prognosis

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A genome-wide computational approach to define microRNA-Polycomb/trithorax gene regulatory circuits in Drosophila

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DEVELOPMENTAL BIOLOGY 2023年 495卷 63-75页

作者： Solorzano, Jacobo Pau, Enrique Carrillo-de Santa Laguna, Teresa Busturia, Ana CSIC UAM Ctr Biol Mol Severo Ochoa Nicolas Cabrera 1 Madrid 28049 Spain IMDEA Food Inst Precis Nutr & Canc Res Program Computat Biol Grp CEI UAM CSIC Madrid 28049 Spain Ctr Rech Cancerol Toulouse 2 Av Hubert Curien F-31100 Toulouse France

Characterization of gene regulatory networks is fundamental to understanding homeostatic development. This process can be simplified by analyzing relatively simple genomes such as the genome of Drosophila melanogaster. In this work we have developed a computational framework in Drosophila to explore for the presence of gene regulatory circuits between two large groups of transcriptional regulators: the epigenetic group of the Polycomb/ trithorax (PcG/trxG) proteins and the microRNAs (miRNAs). We have searched genome-wide for miRNA targets in PcG/trxG transcripts as well as for Polycomb Response Elements (PREs) in miRNA genes. Our results show that 10% of the analyzed miRNAs could be controlling PcG/trxG gene expression, while 40% of those miRNAs are putatively controlled by the selected set of PcG/trxG proteins. The integration of these analyses has resulted in the predicted existence of 3 classes of miRNA-PcG/trxG crosstalk interactions that define potential regulatory circuits. In the first class, miRNA-PcG circuits are defined by miRNAs that reciprocally crosstalk with PcG. In the second, miRNA-trxG circuits are defined by miRNAs that reciprocally crosstalk with trxG. In the third class, miRNA-PcG/ trxG shared circuits are defined by miRNAs that crosstalk with both PcG and trxG regulators. These putative regulatory circuits may uncover a novel mechanism in Drosophila for the control of PcG/trxG and miRNAs levels of expression. The computational framework developed here for Drosophila melanogaster can serve as a model case for similar analyses in other species. Moreover, our work provides, for the first time, a new and useful resource for the Drosophila community to consult prior to experimental studies investigating the epigenetic regulatory networks of miRNA-PcG/trxG mediated gene expression.

关键词： Polycomb Trithorax microRNAs Drosophila computational resource Framework Epigenetic GRN (gene regulatory network) Circuits

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computational and Communication resource Allocation for Mobile Cooperative Cloudlet Computing Systems

Computational and Communication Resource Allocation for Mobi...

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International Conference on Wireless Communications and Signal Processing

作者： Xingyu Zhao Yuan Zhang Lei Wei Min Lu Nat. Mobile Commun. Res. Lab. Southeast Univ. Nanjing China

ISBN: (纸本)9781467376884

Mobile users expect mobile device to work as static computers. However, the limited computational resource of mobile devices can not satisfy users' requirements. To solve this problem, a novel mobile cooperative cloudlet computing (M3C) model is studied in this paper which utilizes computational resource distributed in nearby cloudlet access points (APs) to shorten users' waiting time. A partial critical path (PCP) based workflow scheduling algorithm is proposed to assign tasks of mobile application workflow to APs, a dynamic programming based algorithm is proposed to select placements for APs, and a channel allocation algorithm is proposed to allocate wireless communication resource to radio links between APs. Simulation results show that the M3C model can achieve a shorter users' waiting time compared with the independent cloudlet computing (Icloudlet) model.

关键词： channel allocation cloud computing dynamic programming mobile computing mobile handsets mobile radio resource allocation AP placements Icloudlet model M3C model PCP based workflow scheduling algorithm channel allocation algorithm cloudlet access points communication resource allocation computational resource computational resource allocation dynamic programming based algorithm independent cloudlet computing model mobile application workflow mobile cooperative cloudlet computing systems mobile device mobile users partial critical path based workflow scheduling algorithm radio links static computers user requirements user waiting time wireless communication resource allocation Channel allocation Cloud computing computational modeling Mobile applications Mobile communication Radio link resource management Channel allocation Radio links Cloud Computing Mobile Applications management of resources User needs Mobile phones Mobile radios mobile communication dynamic programming Allocation Algorithm Mobile Computing Mobile devices Waiting time computational modeling

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Minkowski functional evaluation of representative elementary volume of rock microtomography images at multiple resolutions

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ADVANCES IN WATER resourceS 2023年第1期179卷

作者： Sadeghnejad, Saeid Reinhardt, Marcel Enzmann, Frieder Arnold, Pit Brandsta, Bianca Ott, Holger Wilde, Fabian Hupfer, Sarah Schafer, Thorsten Kersten, Michael Tarbiat Modares Univ Fac Chem Engn Dept Petr Engn Tehran Iran Johannes Gutenberg Univ Mainz Geosci Inst D-55099 Mainz Germany Univ Leoben Dept Petr Engn Parkstr 27 A-8700 Leoben Austria Helmholtz Zentrum Hereon Inst Mat Res Max-Planck-Str 1 D-21502 Geesthacht Germany Friedrich Schiller Univ Jena Inst Geosci Appl Geol D-07749 Jena Germany

Pore-scale properties can be obtained by building a reliable digital twin of porous media through the digital rock physics (DRP) workflow. The two prerequisites of DRP are reliable imaging and computing power. Determining a proper image resolution that can reveal the actual pore-scale properties is challenging as there is a trade-off between the resolution and the representative elementary volume (REV). The REV is the smallest volume that reproduces the properties of the whole porous medium. The REV is a function of heterogeneities on the pore scale, the parameter of interest, and the scale range. Although the REV analysis for hydraulic properties is straightforward, it is computationally expensive. This study aims to estimate hydraulic pore-scale properties during REV evaluations by the geometric characterization of porous media using the Minkowski morphological functionals. Two sandstone and one carbonate rock samples were scanned at multiple imaging resolutions by both laboratory and synchrotron tomography. The REVs of various parameters of interest (porosity, permeability, surface area, tortuosity, Minkowski functionals) were computed, and the effect of image resolution and artificial rebinning on the final REV values was examined. After reaching the REV for porosity, the REV for the integrals of mean and total curvature agreed well with the permeability REV for large-volume image sizes. At constant porosity, the Minkowski integrals were found to be indicators for pore throat sizes. We also showed that the properties obtained from the rebinned (or coarsened) images differ entirely from that of actual scans at the same resolution.

关键词： REV Resolution effect Rebinning Minkowski functionals computational resource

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computational investment in generation of elliptic curves randomly over large prime fields

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第13期34卷 e6906-e6906页

作者： Abhishek, Kunal Raj, George Dharma Prakash E. Soc Elect Transact & Secur SETS Network Secur Res Grp Chennai 600113 Tamil Nadu India Bharathidasan Univ Sch Comp Sci Engn & Applicat Tiruchirappalli India

Randomly computed elliptic curves over prime fields are desirable for implementation in strategic or military grade cryptosystems. A randomly computed elliptic curve eliminates the possibility of exhibiting any pre-studied value or special structure of the curve parameters which may be doubted to have intentionally non-disclosed vulnerability. However, computing elliptic curves randomly over large prime fields for cryptography is an intricate task which requires reasonably high computational resources and time. These computational resources are considered in terms of the number of CPU clock cycles and the number of attempts or searches made in the security parameter space of elliptic curve. The estimate of the number of CPU clock cycles helps in determining processor requirements whereas the number of attempts or searches help to decide the number of CPU cores for speeding up the curve generation process. We present efficient statistical estimates of computational resources to randomly compute cryptographically safe elliptic curve over desired prime field size using a standard procedure.

关键词： computational resource cryptography elliptic curve statistical estimation supercomputer

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Robotic Technology-Based Cloud Computing for Improved Services

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SN Computer Science 2020年第4期1卷 1-8页

作者： Gundu, Srinivasa Rao Panem, Charan Arur Timmapuram, Anuradha Dravidian University Andhra Pradesh Kuppam India Goa University Goa Taleigao India

Cloud is Internet-based utility computing which offers a choice to rent and use the computational resources on subscription basis. It has the service-oriented and deployment models which would provide suitable services to the end-users. Robotics can be defined as a machine which would do some useful works as given by the user which would reduce his/her work and make smooth transactions. Cloud robotics is an upcoming technological area with a combination of cloud computing and robotics. Interconnection of these two fields would profit the mankind. Many more different varieties of applications are emerging as on today. In coming of the days, cloud robots will have major role to perform, such as to improve the ‘public utility of technology’. This paper describes the laws of robotics, characteristics of robotics, need for cloud robotics, initial steps for cloud robotics, available cloud robotic technologies, constraints on cloud robotics, cloud robotics architectures, addressing needs of cloud robotics, cloud robotic algorithm—SLAM. This present paper would bring out a review of all such aspects which would benefit the reader with a fine tune. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Addressing needs of cloud robotics Cloud robotics computational resource Public utility of technology Public utility of technology Technological area Upcoming technological area Utility computing

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EFFICIENT PARALLEL PROCESSING BY IMPROVED CPU-GPU INTERACTION

EFFICIENT PARALLEL PROCESSING BY IMPROVED CPU-GPU INTERACTIO...

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International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)

作者： Khatter, Harsh Aggarwal, Vaishali ABES Engn Coll Dept Comp Sci & Engn Ghaziabad India KIET Dept Comp Sci & Engn Ghaziabad India

ISBN: (纸本)9781479928996

In this digital world, more than 90% of desktop and notebook computers have integrated Graphics Processing Units i.e. GPU's, for better graphics processing. Graphics Processing Unit is not only for graphics applications, even for nongraphics applications too. In the past few years, the graphics programmable processor has evolved into an increasingly convincing computational resource. But GPU sits idle if graphics job queue is empty, which decreases the GPU's efficiency. This paper focuses on various tact to overcome this problem and to make the CPU-GPU processing more powerful and efficient. The graphics programmable processor or Graphics processing unit is especially well suited to address problem sets expressed as data parallel computation with the same program executed on many data elements concurrently. The objective of this paper is to increase the capabilities and flexibility of recent GPU hardware combined with high level GPU programming languages: to accelerate the building of images in a frame buffer intended for output to a display, and, to provide tremendous acceleration for numerically intensive scientific applications. This paper also gives some light on major applicative areas where GPU is in use and where GPU can be used in future.

关键词： computer graphics graphics processing units parallel processing CPU-GPU interaction computational resource data parallel computation graphics job queue graphics programmable processor integrated graphics processing units parallel processing scientific applications Acceleration Bandwidth Electroencephalography Graphics processing units Irrigation Streaming media

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