The proceedings contain 247 papers. The topics discussed include: importance of cyber security in software quality assurance;an intelligent system for estimation of exergy efficiency of integrated naphtha and isomeriz...
ISBN:
(纸本)9798350315905
The proceedings contain 247 papers. The topics discussed include: importance of cyber security in software quality assurance;an intelligent system for estimation of exergy efficiency of integrated naphtha and isomerization process under uncertainty;smart scheduling of EVS through intelligent home energy management using deep reinforcement learning;cascade failure management in distributed smart grid using multi-agent control;angular accuracy improvement in digital array radar with experimental analysis;a fall detection algorithm for thigh mounted smartphones using random forest and feature selection techniques;analysis of deep learning algorithms on edge in microscopic fabric dataset;multi-exposure image fusion using edge-aware network;employing intrinsic rewards to reduce requirements engineering issues in large distributed ERP teams;and the state of practices in requirement elicitation: an improved methodology for Pak software industry.
Aiming at the problems of unsmooth path and insufficient tracking accuracy in parallel parking path planning, a parallel parking strategy for distributed drive vehicles is designed. Firstly, the arc-tangent parallel p...
详细信息
This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is pos...
详细信息
Phase retrieval is a crucial step in processing data from advanced X-ray diffraction imaging experiments to analyze the 3D structure of biological macromolecules. However, when the 3D volume is large-scale and consist...
详细信息
Motivated by the continuously growing performance demands for the Isabelle Archive of Formal Proofs (AFP), we introduce distributed cluster computing to the Isabelle platform. parallel build time on a single node has ...
详细信息
This paper addresses the challenges of optimizing task scheduling for a distributed, task-based execution model in OpenMP for cluster computing environments. Traditional OpenMP implementations are primarily designed f...
详细信息
In-situ workflow is a type of workflow where multiple components execute concurrently with data flowing continuously. The adoption of in-situ workflows not only accelerates mission-critical scientific discoveries but ...
详细信息
ISBN:
(纸本)9783031396977;9783031396984
In-situ workflow is a type of workflow where multiple components execute concurrently with data flowing continuously. The adoption of in-situ workflows not only accelerates mission-critical scientific discoveries but also enables responsive disaster predictions. Although there are recent studies on the performance and efficiency aspects of in-situ workflows, the support for portability and distributedcomputing environments is limited. We present INSTANT, a runtime framework to configure, plan, launch, and monitor in-situ workflows for distributedcomputing environments. INSTANT provides intuitive interfaces to compose abstract in-situ workflows, manages in-site and cross-site data transfers with ADIOS2, and supports resource planning using profiled performance data. We use two real-world workflows as use cases: a coupled wildfire spreading workflow and a computational fluid dynamics (CFD) workflow coupled with machine learning and visualization. Experiments with the two real-world use cases show that INSTANT effectively streamlines the orchestration of complex in-situ workflows, and its resource planning capability allows INSTANT to plan and carry out efficient in-situ workflow executions under various computing resource availability.
While significant investments have been made in the exploration of ethics in computation, recent advances in high performance computing (HPC) and artificial intelligence (AI) have reignited a discussion for more respo...
详细信息
ISBN:
(纸本)9783031346675;9783031346682
While significant investments have been made in the exploration of ethics in computation, recent advances in high performance computing (HPC) and artificial intelligence (AI) have reignited a discussion for more responsible and ethical computing with respect to the design and development of pervasive sociotechnical systems within the context of existing and evolving societal norms and cultures. The ubiquity of HPC in everyday life presents complex sociotechnical challenges for all who seek to practice responsible computing and ethical technological innovation. The present paper provides guidelines which scientists, researchers, educators, and practitioners alike, can employ to become more aware of one's personal values system that may unconsciously shape one's approach to computation and ethics.
As a core technique of machine learning, deep neural networks (DNNs) have been extensively used in today's mobile applications. However, users' mobile devices (MDs) have limited capabilities to execute computa...
详细信息
ISBN:
(纸本)9781728190549
As a core technique of machine learning, deep neural networks (DNNs) have been extensively used in today's mobile applications. However, users' mobile devices (MDs) have limited capabilities to execute computation-intensive DNN inference operations and meet the latency constraints. Offloading part of DNN computations to edge servers (ESs) in a mobile edge computing (MEC) network can mitigate these challenges. However, prior studies on offloading either overlook the varying computation demands and output data sizes for different layers of neural networks or only consider split DNN offloading based on a single user or a single ES. Driven by the question of how to partition multiple parallel DNN inferences and offload multiple partitioned DNN processes in a multi-user multi-ES network, in this paper, we design a distributed scheme that jointly optimizes user-ES association, DNN layer-level partitioning, computing and wireless communication resource allocation, and offloading. Specifically, MDs and ESs make decisions to maximize their own utilities based on a multi-leader multi-follower Stackelberg game by leveraging DNN layer characteristics and taking account of multi-server heterogeneous network environments, computation load, and available resources. The evaluation results show that the proposed joint optimization scheme can significantly improve the performance of DNN inferences, compared to the commonly used benchmarks.
In the model of measurement-based quantum computing (MBQC), computations are performed via sequential measurements on a highly entangled graph state. MBQC is a natural model for photonic quantum computing and has been...
详细信息
ISBN:
(纸本)9798350364613;9798350364606
In the model of measurement-based quantum computing (MBQC), computations are performed via sequential measurements on a highly entangled graph state. MBQC is a natural model for photonic quantum computing and has been shown to be useful for tasks like optimization and verification of general quantum computations. Therefore, it is often necessary to translate between MBQC and the predominantly used quantum circuit model in a fast and reliable way. While there are algorithms with linear complexity to extract quantum circuits from measurement patterns using additional ancilla qubits, efficient ancilla-free extraction has shown to be more costly. We develop strategies to parallelize an existing extraction algorithm based on ZX-calculus by exploiting the graph structure of measurement patterns and evaluate the performance on patterns obtained from a benchmark set of quantum circuits. Our results suggest that possible parallelization speedups are closely related to the graph structure of a pattern.
暂无评论