This paper studies a few randomized algorithms (e.g., random walks, gossip) in peer-to-peer networks. We leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and of ...
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Accurate Traffic Forecasts Are Crucial for a City. Traditional Methods Overlook Spatial and Temporal Dependencies, Rendering Them Ineffective for Precise Long-Term Traffic Prediction Given the Intricate and Complex Na...
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The proceedings contain 59 papers. The special focus in this conference is on Current Problems of Applied Mathematics and computersystems. The topics include: Forced Longitudinal Oscillations of Vertical Rods with Co...
ISBN:
(纸本)9783031640094
The proceedings contain 59 papers. The special focus in this conference is on Current Problems of Applied Mathematics and computersystems. The topics include: Forced Longitudinal Oscillations of Vertical Rods with Concentrated Mass;method of Guaranteed Collision Avoidance with Multiple Unpredictable Target-Vessels;computer-Oriented Lyapunov Stability Criteria for systems of Nonlinear Ordinary Differential Equations;asymptotic Estimates of the Horizontal Wind Retrieval Accuracy from Lidar Remote Sensing Data;effect of Wind Field Deformation on the Wind Components Retrieval Accuracy from Lidar Measurements;on Vibration of Multi-span Continuous Beam in View of Rotational Inertia;load Balancing Methods for distributed Data Storage: Challenges and Opportunities;method for Detecting and Correcting Errors in Arithmetic Operations Based on Rank of a Number;toward Understanding Uncertainty in Fog-Cloud Computing for Big Data Storage and Processing;simulation of a Coaxial Resonator of a Frequency-Selective Device for Communication systems, Radio Navigation and Radar;analytical Review of Orchestration Methods for distributed Computing systems Under Conditions of Dynamic Scaling;modeling of Density Properties of Subsiding Soils Under Explosive Impact;comparative Analysis of Error Correction Devices in Modular Redundant Codes;estimation of the Solution of a Spatial Parabolic Equation Describing Anisotropic Geological systems;development of a Mathematical Model of the Software Solution «Bioeconomical Diagnostics of Health Protection»;fault Tolerant System for Data Storage, Transmission and Processing in Fog Computing Using Artificial Neural networks;A 17ps Two Channel TDC System Based on XILINX ZYNQ 7000 SoC;investigation of the Rank of Numbers Represented in the Residue Number System;power Consumption Modelling for Symmetric Block Encryption Algorithms;methodology for Assessing the Security Risks of Cyber-Physical systems.
In recent years, Multiple-Input Multiple-Output (MIMO) have revolutionized reliability and spectral efficiency of wireless communication systems. These systems exploit multiplexing and spatial diversity which enabling...
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In this paper, the quantized consensus tracking problem for continuous-time multi-agent systems (MASs) under denial-of-service (DoS) attacks is studied. Based on the dynamical quantized strategy, a sampling-based cont...
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Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with ...
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ISBN:
(纸本)9798350364613;9798350364606
Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software pertimmance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT's longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.
Blockchain technology has gained significant attention in the healthcare sector due to its potential to address challenges related to data security, integrity, and interoperability. One critical aspect of blockchain n...
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Currently, one of the simplest and most effective ways for people to gain an in-depth understanding of computernetworks is through hands-on practice and experimentation on software platforms. While education is impor...
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Software effort estimation remains a persistent challenge and requires serious attention in the early stages of software project management. Inherent uncertainties arising from incomplete and inaccurate requirements p...
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Neural processing units (NPUs) have become indispensable parts of mobile SoCs. Furthermore, integrating multiple NPU cores into a single chip becomes a promising solution for ever-increasing computing power demands in...
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ISBN:
(纸本)9798400701016
Neural processing units (NPUs) have become indispensable parts of mobile SoCs. Furthermore, integrating multiple NPU cores into a single chip becomes a promising solution for ever-increasing computing power demands in mobile devices. This paper addresses techniques to maximize the utilization of NPU cores and reduce the latency of on-device inference. Mobile NPUs typically have a small amount of local memory (or scratch pad memory, SPM) that provides space only enough for input/output tensors and weights of one layer operation in deep neural networks (DNNs). Even in multicore NPUs, such local memories are distributed across the cores. In such systems, executing network layer operations in parallel is the primary vehicle to achieve performance. By partitioning a layer of DNNs into multiple sub-layers, we can execute them in parallel on multicore NPUs. Within a core, we can also employ pipelined execution to reduce the execution time of a sub-layer. In this execution model, synchronizing parallel execution and loading/storing intermediate tensors in global memory are the main bottlenecks. To alleviate these problems, we propose novel optimization techniques which carefully consider partitioning direction, execution order, synchronization, and global memory access. Using six popular convolutional neural networks (CNNs), we evaluate our optimization techniques in a flagship mobile SoC with three cores. Compared to the highest-performing partitioning approach, our techniques improve performance by 23%, achieving a speedup of 2.1x over single-core systems.
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