Cellular Automata (CA) are extensively utilized for modeling and simulating complex systems due to their simplicity, flexibility, and ability to represent diverse phenomena. However, the computational intensity of CA ...
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advances in graph algorithmics have allowed in-depth study of many natural objects from molecular biology or chemistry to social networks. Particularly in molecular biology and cheminformatics, understanding complex s...
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Confidential computing on GPUs, like NVIDIA H100, mitigates the security risks of outsourced Large Language Models (LLMs) by implementing strong isolation and data encryption. Nonetheless, this encryption incurs a sig...
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The k-hop query represents a fundamental challenge in various graph applications, often supported by numerous distributed systems. The conventional approach to this query paradigm typically involves iterative layer-by...
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In recent years, considerable attention has been drawn to the development of algorithms for subgraph matching in distributed scenarios. Many distributed engines inherently support join-based methods, which can lead to...
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Existing decentralized learning of Generative Adversarial Network (GAN) suffers from a slower convergence rate and training instability due to the changes in the gradient-sharing approach among workers. It requires mo...
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Scientific computing centers or private (in-house) cloud data centers do not rely on the standard pay-as-you-go business model which is common in commercial clouds to allocate resources. Instead, the system is typical...
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In this paper we present a novel distributed algorithm for solving the Bi-Objective Minimum Spanning Tree (BMST) problem using a two-phase method. The proposed approach leverages the MapReduce computing paradigm to de...
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When all the qubits needed for solving a problem are not located in a single quantum computer, qubits from different quantum computers can be collectively utilized. In this case, quantum communication is needed for th...
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ISBN:
(数字)9798331531591
ISBN:
(纸本)9798331531607
When all the qubits needed for solving a problem are not located in a single quantum computer, qubits from different quantum computers can be collectively utilized. In this case, quantum communication is needed for the multiple quantum computers to communicate with each other. Several studies address the problem of minimizing the number of quantum communications when evaluating a general quantum circuit. The solutions proposed typically involve solving some intractable problems. In this paper, we show that we can obtain much better solutions when we focus on solving specific problems (instead of seeking solutions for generic circuits). Specifically, we consider several fundamental quantum circuits and identify communication protocols that need a much smaller number of communication steps than those offered by generic solutions. Our work is in line with traditional parallel and distributedcomputing research where typically scientists focus on solving specific problems (such as sorting, matrix multiplication, network flow, etc.) in a parallel or distributed setting.
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