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检索条件"任意字段=Conference on Photonic Devices and Algorithms for Computing V"

共 1067 条记录，以下是11-20 订阅

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CNC Machine Tool Focused Edge computing in Manufacturing 17

CNC Machine Tool Focused Edge Computing in Manufacturing

引用

17th CIRP conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2023

作者： Tonejca, L. Mayer, C. Trautner, T. Mauthner, G. Bleicher, F. TU Wien Institute of Production Engineering and Photonic Technologies Karlsplatz 13 Vienna1040 Austria

This paper presents a method for standardized integration of external sensors and actuators into CNC machine tool systems utilizing edge computing technology. Different communication protocols and various means for triggering external devices at a chosen machining operation were studied and evaluated using a sensory tool holder. The benefits of the presented architecture are the independence of the host operating system, easy customization, lightweight architecture, and standard protocols. Focusing on the demands for modern edge devices led to containerized modules with customizable interfaces. During manufacturing processes, the system was evaluated in terms of performance and reliability. © 2024 Elsevier B.v.. All rights reserved.

关键词： Smart manufacturing

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A scalable integrated photonics tensor core for large vector-matrix multiplications 5

A scalable integrated photonics tensor core for large vector...

引用

conference on AI and Optical Data Sciences v

作者： Peinke, Emanuel Lacasse, Thomas Najeeb, Najla Masnad, Md Mahadi Fouda, Mohamed Peter, Yves-Alain Liboiron-Ladouceur, Odile 3E8 Inc 780 Ave Brewster Montreal PQ H4C 2K1 Canada Polytech Montreal Microphoton Lab Engn Phys 2500 Chemin Polytech Montreal PQ H3T 1J4 Canada McGill Univ Photon DataCom Team Elect & Comp Engn McConnell Engn Bldg3480 Univ St Montreal PQ H3A 0E9 Canada

ISBN: (纸本)9781510670679;9781510670662

Optical computing promises to play a major role in hardware chips dedicated to artificial intelligence (AI). Digital electronics, when employed in computing hardware, face the sunset of Moore's law and the acknowledged end of Dennard scaling (energy density of shrinking transistors). In response to these limitations, a paradigm shift towards non-digital processing is on the horizon. In optical computing devices for AI, the dominant mathematical operation is vector-matrix multiplication. It is typically limited to small vector and matrix sizes. Most approaches do not allow for significant scaling. In this context, our work focuses on the development of a silicon photonics tensor core that exhibits a unique scalability feature, enabling effective expansion to accommodate large matrix sizes. This scalability is deemed essential for the realization of meaningful AI accelerator products leveraging photonic hardware.

关键词： optics computing silicon photonics AI analog computing

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Lightweight Extension of RISC-v Core for NTT-like algorithms 35

Lightweight Extension of RISC-V Core for NTT-like Algorithms

引用

35th IEEE International conference on Application-Specific Systems, Architectures and Processors (ASAP)

作者： Wygrzywalski, Mateusz Szczygiel, Robert AGH Univ Krakow Dept Measurement & Elect Krakow Poland

ISBN: (纸本)9798350349641;9798350349634

computing on the smallest Internet of Things (IoT) devices is increasingly essential. Dedicated hardware solutions, while offering high efficiency and speed, often lack the programmability required to adapt to evolving algorithms. Small CPUs, similar in energy consumption, usually cannot match this performance but can be enhanced through meticulous programming in assembly language. Typically, this improvement comes at the cost of increased code size or necessitates switching to a more energy-consuming platform. In this paper, we propose a combined hardware/software approach to enhance the performance of data-intensive algorithms on modified, efficient, small-sized RISC-v CPUs. We demonstrate this method using the Number Theoretic Transform from the Kyber algorithm as a case study. Our approach resulted in a significant speed improvement, while maintaining a code size that is nearly the same and reasonable resource utilization increase.

关键词： hardware acceleration NTT processor microarchitecture RISC-v

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Comprehensive Survey on Internet of Medical Things (IoMT) - Applications and Challenges 15

Comprehensive Survey on Internet of Medical Things (IoMT) - ...

引用

15th International conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Anusha, v. Sai Kumar, R. Kiran Kumar, G. Charan Mabjan, Palagiri Madanapalle Institute of Technology & Science Department of Electronics and Communication Engineering Madanapalle517325 India Annamacharya University Department of Computer Applications Rajampet India

ISBN: (纸本)9798350370249

The Internet of Medical Things (IoMT) is changing healthcare through the use of the Internet to connect medical devices, apps, and systems. This helps improve patient care, makes healthcare more efficient, and improves health outcomes. This paper deals with the edge-fog-cloud computing architectures for Internet of Health applications. Remote patient monitoring is done by collecting the data from wearable health devices, processing at different communication levels, applying intelligent algorithms and providing insights to the patient and healthcare professionals. This paper reviews the IoMT architecture and how the entire workflow is managed at device, edge, fog, and cloud levels. The paper also discusses IoMT challenges, such as data security and privacy concerns due to the interconnectedness and interoperability of devices at each layer and hurdles for seamless data integration within healthcare networks. © 2024 IEEE.

关键词： Electronic health record

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Two Hybrid Heuristic algorithms for Optimizing Data Processing Schedules in Distributed Edge computing 11

Two Hybrid Heuristic Algorithms for Optimizing Data Processi...

引用

11th International conference on Wireless Networks and Mobile Communications (WINCOM) - Inclusive and Intelligent Connectivity

作者： Sayah, Achraf Aqil, Said Aadil, Bouchra Lahby, Mohamed Hassan II Univ Lab Appl Math & Comp Sci Higher Normal Sch Casablanca Morocco Hassan II Univ Lab Artificial Intelligence & Complex Syst Engn Natl Higher Sch Arts & Crafts Casablanca Morocco

ISBN: (纸本)9798350377873;9798350377866

In recent years, edge computing has emerged as a promising solution in the field of network computing. This architecture ensures the availability of distributed computing resources located closer to end-users and IoT devices. However, resource scheduling remains a significant challenge in edge computing, requiring effective strategies to optimize resource utilization and ensure efficient task allocation. In this paper, we propose two hybrid approaches that combine the NawazEnscore-Ham (NEH) algorithm with local search and Greedy Random Adaptive Search Procedure (GRASP) algorithm with local search for modeling and solving data traffic in distributed edge computing environments (DPSDEC). Through extensive evaluations, we consistently observe that the NEH algorithm outperforms GRASP, delivering minimized makespan and generating efficient schedules. Moreover, the NEH algorithm performs very well in less complex situations and maintains this advantage even in larger and more complex problems.

关键词： Local search Algorithm Edge computing Distributed Networks Scheduling.

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Entanglement-enhanced Quantum Reinforcement Learning: an Application using Single-Photons 5

Entanglement-enhanced Quantum Reinforcement Learning: an App...

引用

2024 International conference on Quantum computing and Engineering

作者： Gaspar, Joaquim M. Bergerault, Alexandre Apostolou, vassilis Ricou, Arno Quandela F-91300 Massy France Inst Polytech Paris ENSTA Paris F-91120 Palaiseau France

ISBN: (纸本)9798331541378

Quantum Reinforcement Learning (QRL) is an emerging field with many novel approaches suitable for noisy intermediate-scale quantum (NISQ) devices being proposed recently. Projective Simulation (PS) is a classical machine learning method based on random walks in a Directed Acyclic Graph (DAG), and is mainly used to train agents in a Reinforcement Learning setup. This graph corresponds to the Episodic Compositional Memory (ECM) of the agent. For the quantum version of PS we use quantum walks of single photons in quantum optical circuits, which go through tunable components (beamsplitters and phase shifters). We call this specific model Quantum Optical Projective Simulation (QOPS). In this work, we propose a general framework to translate any 2-layer ECM to a quantum optical circuit and an algorithm for solving quantum strategic games using QOPS. Moreover, we introduce QOPS with an entangled state as input. The application that we are using to evaluate the performance of the framework is the Prisoner's Dilemma. We executed the implementation using Altair's noisy simulator, designed to emulate a single photon-based quantum processor by Quandela. The algorithm provided promising results even in the presence of noise, which makes it a strong candidate for runs on single-photon -based quantum processors.

关键词： quantum reinforcement learning quantum machine learning variational quantum algorithms photonic quantum computing projective simulation quantum games

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QR-PULP: Streamlining QR Decomposition for RISC-v Parallel Ultra-Low-Power Platforms 21

QR-PULP: Streamlining QR Decomposition for RISC-V Parallel U...

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21st ACM International conference on computing Frontiers (CF)

作者： Kiamarzi, Amirhossein Rossi, Davide Tagliavini, Giuseppe Univ Bologna Bologna Italy

ISBN: (纸本)9798400705977

QR decomposition is a numerical method used in many applications from the High-Performance computing (HPC) domain to embedded systems. This broad spectrum of applications has drawn academic and commercial attention to developing many software libraries and domain-specific hardware solutions. In the Internet of Things (IoT) domain, multicore Parallel Ultra-Low-Power (PULP) architectures are emerging as energy-efficient alternatives, outperforming conventional single-core devices by coupling parallel processing with near-threshold computing. To the best of the authors' knowledge, our study introduces the first parallelized and optimized implementation of three distinct QR decomposition methods (Givens rotations, Gram-Schmidt process, and Householder transformation) on GAP-9, a commercial embodiment of the PULP architecture. Parallel execution on the 8-core cluster leads to a reduction in the total number of cycles by 241% for Givens rotations, 470% for Gram-Schmidt, and 567% for Householder, compared to the GAP9 1-core scenario. while each of them only consumes 0.013 mJ, 0.012 mJ, and 0.216 mJ, respectively. Compared to traditional single-core architectures based on ARM architectures, we achieve 8x, 24x, and 30x better performance and 36x, 35x, and 30x better energy efficiency, paving the way for broad adoption of complex linear algebra tasks in the IoT domain.

关键词： QR decomposition parallel algorithms ultra-low-power computing

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Addressed photonic Differentiator Based on Fiber Bragg and Moire Gratings Structure

Addressed Photonic Differentiator Based on Fiber Bragg and M...

引用

2024 Wave Electronics and its Application in Information and Telecommunication Systems, WECONF 2024

作者： Ivanov, A.A. Artem'ev, v.I. Morozov, O.G. Belov, A.S. Misbakhov, Rh.S. Kazan National Research Technical University Named After A.N. Tupolev-KAI Kazan Russia

ISBN: (纸本)9798350364989

For photonic differentiators, which, as a rule, are considered as separate devices, the issues of their network multiplexing for a single module of photonic processing and computing of multiple signals, as well as the stability of differentiation characteristics with deviations in the temperature regimes of the laser and differentiator with a corresponding mismatch of their central wavelengths, are not touched upon. The advantages of microwave photonic processing of information used for addressed fiber Bragg structures will make it possible to solve the above problems of photonic differentiators when they are combined into a network. This conclusion is proved by the procedure presented in the report for the synthesis of combined addressed fiber Bragg structures, one of component of which is the Moire grating and the unity of their structure with the structure of photon differentiators. © 2024 IEEE.

关键词： Fiber Bragg gratings

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Error Rate Increment of Quantum Computer using Quantity Computational Algorithm Comparing with Deutsch Jozsa Algorithm

Error Rate Increment of Quantum Computer using Quantity Comp...

引用

2024 OPJU International Technology conference on Smart computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Kumar, K. Ajay vimal, v.R. Karthick, v. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350373783

the primary purpose is to investigate the possibility of utilizing quantum algorithms in order to improve the error rate of quantum computing devices. The Components and Procedures: We gathered twenty samples and divided them into two distinct groups. Novel Quantity Computational algorithms are included in Group 1, while the Deutsch Jozsa algorithm is included in Group 2. In Group 1, there are ten samples, and in Group 2, there are also ten samples. The G power is one hundred percent, and the Alpha and Beta values are 0.05 and 0.2 individually. End Result: A high error rate of 55.6% was created by the Novel Quantity computational approach that was proposed, in comparison to the Deutsch Jozsa algorithm, which produced a rate of 48.8%. As a consequence of the results, it is clear that there was not a significant statistical difference between the two groups, and the p value is 0.2. This demonstrates that the hypothesis is correct, and it is accomplished by the utilization of an independent sample T test. The mean error rate detection is 2 standard deviations. Therefore, the error rate of the Novel Quantity computational method is significantly higher than the error rate of the Deutsch Jozsa algorithm. This is the conclusion that can be drawn from the findings. © 2024 IEEE.

关键词： Encryption algorithms

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muRISCv-NN: Challenging Zve32x Autovectorization with TinyML Inference Library for RISC-v vector Extension 21

muRISCV-NN: Challenging Zve32x Autovectorization with TinyML...

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21st ACM International conference on computing Frontiers (CF)

作者： van Kempen, Philipp Jones, Jefferson Parker Mueller-Gritschneder, Daniel Schlichtmann, Ulf Tech Univ Munich Chair Elect Design Automat Munich Bavaria Germany Vienna Univ Technol Embedded Comp Syst Vienna Austria

ISBN: (纸本)9798400704925

With the rapid adoption of deep learning workloads to resource-constrained edge devices, efficient and data-parallel computing paradigms are becoming increasingly important. The RISC-v ISA provides a set of vector extensions featuring powerful data computation capabilities to accelerate deep learning workloads at the edge. However, the RISC-v ecosystem lacks a lightweight, open-source, and vendor-agnostic compute library to support these extensions on embedded platforms. After porting the existing ARM Cortex-M specific kernel implementation to the RISC-v vector ISA, we optimized the operator implementations to make the most out of the data-level parallelism provided by supported targets. In comparison to programs vectorized by LLvM's built-in auto-vectorizer, we see an up to 60% advantage in runtime for convolutional models and large vectors while introducing less ROM overheads. Furthermore, muRISCv-NN integrates well with existing ML deployment frameworks, is bit-accurate to CMSIS-NN, and can, thus, be used as a drop-in replacement with minimal changes to the compilation flow.

关键词： Neural Network Inference RISC-v Compilers vectorization

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