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A logic Programming Approach to VM Placement 14

A Logic Programming Approach to VM Placement

引用

14th international conference on Cloud Computing and Services Science, CLOSER 2024

作者： Andreoli, Remo Forti, Stefano Pannocchi, Luigi Cucinotta, Tommaso Brogi, Antonio Sant’Anna School of Advanced Studies Pisa Italy Department of Computer Science University of Pisa Pisa Italy

ISBN: (纸本)9789897587016

Placing virtual machines so to minimize the number of used physical hosts is an utterly important problem in cloud computing and next-generation virtualized networks. this article proposes a declarative reasoning methodology, and its open-source prototype, including four heuristic strategies to tackle this problem. Our proposal is extensively assessed over real data from an industrial case study and compared to state-of-the-art approaches, both in terms of execution times and solution optimality. As a result, our declarative approach determines placements that are only 6% far from optimal, outperforming a state-of-the-art genetic algorithm in terms of execution times, and a first-fit search for optimality of found placements. Last, its pipelining with a mathematical programming solution improves execution times of the latter by one order of magnitude on average, compared to using a genetic algorithm as a primer. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Cloud computing

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Activation of a real closed loop solar tracking system using field programmable Gate Array (FPGA) 14

Activation of a real closed loop solar tracking system using...

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14th IEEE international conference on Industry applications, INDUSCON 2021

作者： Silva, Gabriel Barbarossa Rodor, Fadul Ferrari de Sousa, Clodualdo Venfcio Pugliese, Luiz Felipe Instituto de Ciencias Tecnologicas Universidade Federal de Itajubd Minas Gerais Itabira Brazil

ISBN: (纸本)9781665441186

the present work aims to propose the development of a real solar tracking system using an FPGA (field programmable Gate Array) for control, and together with the development of all interfaces and drivers connected to the electronics involved for the correct functioning of the components. the module in question is a set of 6 solar panels in series, supported on a single axis support. the movement of the plates will be carried out by a DC motor that will be attached to the structure that it supports. thus, the aim is to develop the control system for the motor activation in closed loop using MATLAB/Simulink associated with the FPGA as an auxiliary platform. Finally, it is verified the closed loop operation, simulating the behavior of the DC motor by an RL load, performing the activation of the system in the positive and negative direction, obtaining in the end a similar response between the simulation and the real system. © 2021 IEEE

关键词： DC motors

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14th international conference on Large-Scale Scientific Computations, LSSC 2023

14th International Conference on Large-Scale Scientific Comp...

引用

14th international conference on Large-Scale Scientific Computations, LSSC 2023

ISBN: (纸本)9783031562075

the proceedings contain 50 papers. the special focus in this conference is on Large-Scale Scientific Computations. the topics include: Numerical Comparison of Block Preconditioners for Poroelasticity;Two-Dimensional Semi-linear Riesz Space Fractional Diffusion Equations in Convex Domains: GLT Spectral Analysis and Multigrid Solvers;continuation Newton Methods with applications to Plasticity;mixed and Nitsche’s Discretizations of Frictional Contact-Mechanics in Fractured Porous Media;Towards Efficient SOT-Assisted STT-MRAM Cell Switching Using Reinforcement Learning;machine Learning Algorithms for Parameter Identification for Reactive Flow in Porous Media;randomized Symplectic Model Order Reduction for Hamiltonian Systems;Adaptive Localized Reduced Basis Methods for Large Scale PDE-Constrained Optimization;Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling;parametric Analysis of Space-Time Fractional Pennes Bioheat Model Using a Collocation Method Based on Radial Basis Functions and Chebyshev Polynomials;numerical Determination of Source from Point Observation in a Time-Fractional Boundary-Value Problem on Disjoint Intervals;the Wright Function – Numerical Approximation and Hypergeometric Representation;Study of Sparsification Schemes for the FEM Stiffness Matrix of Fractional Diffusion Problems;fractional Diffusion Problems with Reflecting Boundaries;A Mean field Model for Counter CBRN threats;a Sufficient Condition for a Discrete-Time Optimal Control Problem;computation of the Unknown Time-Dependent Volatility of American Options from Integral Observations;efficient Solution of Stochastic Galerkin Matrix Equations via Reduced Basis and Tensor Train Approximation;the Tensor-Train Mimetic Finite Difference Method for three-Dimensional Maxwell’s Wave Propagation Equations;A Functional Tensor Train Library in RUST for Numerical Integration and Resolution of Partial Differential Equations;solving the Mountain Car Problem Using Gene

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A low-cost 4 ps root-mean-square resolution time-todigital converter implemented in a 28 nm field-programmable gate array

A low-cost 4 ps root-mean-square resolution time-todigital c...

引用

international conference on Electronics Technology (ICET)

作者： Jinxin Liu Peipei Deng Juan Liu Ying Wang Microsystem and Terahertz Research Center China Academy of Engineering Physics Chengdu China

ISBN: (数字)9798350363951

ISBN: (纸本)9798350363968

this paper presents the implementation of a 28 nm field-programmable gate array (FPGA)-based time-to-digital converter (TDC), which has both high resolution and low-cost characteristics. Due to the simple TDC structure, only a few resources are required, making it suitable for multi-channel applications. An eight-channel TDC was designed in this study. In addition, an automatic nonlinearity calibration logic is implemented within the FPGA, guaranteeing stable performance of the TDC over a wide temperature range. the test results show that the average bin size of a typical channel is 2.55 ps, and the single-shot precision is better than 4 ps.

关键词： Temperature distribution logic gates Calibration logic field programmable gate arrays

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Secure Medical Image Transmission Using the RLCD Algorithm

Secure Medical Image Transmission Using the RLCD Algorithm

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Sentiment Analysis and Deep Learning (ICSADL), international conference on

作者： C Sheeba Joice S Hitha Shanthini K Harsha S Gopika Department of Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

As digital platforms increasingly manage sensitive medical information, securing the transmission of medical images is essential to maintain confidentiality and data integrity. this project introduces an efficient and secure cryptographic framework specifically designed for medical image encryption using Reversible logic Cryptography Design (RLCD). the approach incorporates Linear Feedback Shift Registers (LFSR) combined with XOR gates, enabling low-power and high-speed encryption and decryption to protect patient data without sacrificing performance. By integrating reversible logic gates, this system effectively reduces energy dissipation and prevents information loss, making it well-suited for applications where data accuracy is critical. Implemented in Verilog HDL and deployed on a field programmable Gate Array (FPGA), this design provides a robust solution to address the unique security demands in medical imaging.

关键词： Sentiment analysis programmable logic arrays logic gates Hardware Software Encryption Hardware design languages field programmable gate arrays Biomedical imaging Python

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PolyLUT-Add: FPGA-based LUT Inference with Wide Inputs

PolyLUT-Add: FPGA-based LUT Inference with Wide Inputs

引用

international conference on field programmable logic and applications

作者： Binglei Lou Richard Rademacher David Boland Philip H.W. Leong School of Electrical and Computer Engineering The University of Sydney Australia

ISBN: (数字)9798331530075

ISBN: (纸本)9798331530082

FPGAs have distinct advantages as a technology for deploying deep neural networks (DNNs) at the edge. Lookup Table (LUT) based networks, where neurons are directly modeled using LUTs, help maximize this promise of offering ultra-low latency and high area efficiency on FPGAs. Unfortunately, LUT resource usage scales exponentially with the number of inputs to the LUT, restricting PolyLUT to small LUT sizes. this work introduces PolyLUT-Add, a technique that enhances neuron connectivity by combining A PolyLUT sub-neurons via addition to improve accuracy. Moreover, we describe a novel architecture to improve its scalability. We evaluated our implementation over the MNIST, Jet Substructure classification, and Network Intrusion Detection benchmark and found that for similar accuracy, PolyLUT-Add achieves a LUT reduction of $2.0-13.9 \times$ with a $1.2-1.6 \times$ decrease in latency.

关键词： Accuracy Scalability Neurons Network intrusion detection Benchmark testing Polynomials Table lookup logic field programmable gate arrays Optimization

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Artificial Intelligence for Cancer Diagnosis and Prognosis: Current Status and Future Directions 14

Artificial Intelligence for Cancer Diagnosis and Prognosis: ...

引用

14th international conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Negi, Anushree Gupta, Preeti Pradhan, Rahul Dit University Department of Computer Science & Engineering Dehradun India GLA University Department of Computer Engineering & Applications Mathura India

ISBN: (纸本)9798350335095

the medical field and public health care has achieved radical progress in the last age, the original reasons behind abundant conditions were disclosed, novel symptomatic forms were devised, and new cures were developed. the second leading cause of death is cancer. worldwide afflicting approximately six out of every ten people. Variants of the lungs and colon of all cancers are those that prevalent and most fatal. However, detecting the disease in its infancy increases the odds of survival dramatically. Over the last three decades, the number of cancer victims and the scope of cancer survivability research has increased. this chapter provides a review of all types of cancer prediction with interventional and observational cancer survivorship research efforts. the treatment of cancer type is increasingly required in early cancer research. the advancement of healthcare research has been boosted by artificial intelligence. Researchers have developed program to help cancer identification and prognosis due to the availability of open-source healthcare statistics. In these conditions, DL and ML models give a dependable, quick, and effective method for dealing with such difficult diseases. Cancer categorization is a contentious issue in medicine since it allows for precise and effective diagnosis and promotes a favorable outcome in medical therapies. © 2023 IEEE.

关键词： Diseases

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Characterization and Classification of Mangifera Indica Ripeness with Electronic Nose using Fuzzy logic Algorithm 14

Characterization and Classification of Mangifera Indica Ripe...

引用

14th IEEE international conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2022

作者： Ibarra, Dan Melvin A. Patajo, Stephen Jubert G. Caya, Meo Vincent C. Mapua University School of Electrical Electronics and Computer Engineering Muralla St. Intramuros Manila1002 Philippines

ISBN: (纸本)9781665464932

In the Philippines, agriculture plays a vital role. Mangoes are exported to 48 nations throughout the world. the Philippines ranks 7th in the world in mango output. An electronic nose that can distinguish between ripe and unripe Mangifera Indica is the primary goal of this research. the gases generated by the mango will be used to determine the ripeness of the mango utilizing MQ sensors. the Fuzzy logic Algorithm can tell the difference between ripe and unripe mangoes. Future researchers that employ and improve the use of Electronic Nose in other applications will benefit from this research. this system can be used to determine whether a mango is unripe or ripe. the focus of the characterization will be on the results of our research's testing component. Because the electronic nose and fuzzy logic algorithm will be used for characterization and categorization. the MQ sensors were used to detect chemicals released by the Mangifera Indica, according to the researchers. Unripe mangoes were identified with an accuracy of 93.33 percent, whereas ripe mangoes were identified with an 86.67 percent accuracy. the system's total accuracy is 90 percent. © 2022 IEEE.

关键词： Fuzzy logic

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Fast and Practical Strassen’s Matrix Multiplication using FPGAs

Fast and Practical Strassen’s Matrix Multiplication using F...

引用

international conference on field programmable logic and applications

作者： Afzal Ahmad Linfeng Du Wei Zhang Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

ISBN: (数字)9798331530075

ISBN: (纸本)9798331530082

Matrix multiplication is a cornerstone operation in a wide array of scientific fields, including machine learning and computer graphics. the standard algorithm for matrix multiplication has a complexity of $O\left(n^{3}\right)$ for $n \times n$ matrices. Strassen’s algorithm improves this to $O\left(n^{2.807}\right)$, but its practicality is limited for small to medium matrix sizes due to the large number of additions it introduces. this paper presents a novel FPGA-based implementation of Strassen’s algorithm that achieves superior speed over an optimized General Matrix Multiply (GeMM) implementation for matrices as small as n = 256. Our design, tested extensively on two high-performance FPGA accelerators (Alveo U50 and U280) across various data types, matches or surpasses the performance of a highly optimized baseline across a range of matrix sizes.

关键词： Machine learning algorithms Machine learning Computer graphics Complexity theory Resource management logic field programmable gate arrays Standards

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FORC: A High-throughput Streaming FPGA Accelerator for Optimized Row Columnar File Decoders in Big Data Engines

FORC: A High-Throughput Streaming FPGA Accelerator for Optim...

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international conference on field programmable logic and applications

作者： Abdul Wadood Alec Lu Ken Zhang Zhenman Fang Simon Fraser University Burnaby BC Canada Huawei Canada Markham ON Canada

ISBN: (数字)9798331530075

ISBN: (纸本)9798331530082

To improve the file storage efficiency of large datasets, big data analytics usually use some common file formats, such as Apache ORC (optimized row columnar) format, to encode and compress the data. However, this shifts the IO bottleneck (especially with high-bandwidth SSDs) to the computation bottleneck on CPUs to decompress and decode the data. this paper presents FORC, a high-throughput streaming-based FPGA accelerator overlay that supports different ORC file format decoders, and its dataflow integration with Apache ORC. Experimental results show that FORC achieves up to $12.9 \mathrm{~GB} / \mathrm{s}$ decoding throughput on AMD/Xilinx Alveo U280 FPGA, with a geomean speedup of 65x (up to 335x) over the CPU. FORC will be released soon at https://***/SFU-HiAccel/FORC.

关键词： Big Data throughput Decoding logic field programmable gate arrays Engines

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