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The MPI + CUDA Gaia AVU-GSR Parallel Solver Toward Next-generation Exascale Infrastructures

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Publications of the Astronomical Society of the Pacific 2023年第1049期135卷 074504-074504页

作者： Cesare, Valentina Becciani, Ugo Vecchiato, Alberto Gilberto Lattanzi, Mario Pitari, Fabio Aldinucci, Marco Bucciarelli, Beatrice INAF Astrophysical Observatory of Catania via Santa Sofia 78 CT Catania 95123 Italy ICSC—Centro Nazionale di Ricerca in High Performance Computing Big Data and Quantum Computing Italy INAF Astrophysical Observatory of Turin via Osservatorio 20 TO Pino Torinese 10025 Italy CINECA via Magnanelli 6/3 BO Casalecchio di Reno 40033 Italy University of Turin Computer Science Department corso Svizzera 185 TO Turin 10149 Italy

We ported to the GPU with CUDA the Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver developed for the ESA Gaia mission, by optimizing a previous OpenACC porting of this application. The code aims to find, with a [10, 100] μarcsec precision, the astrometric parameters of ∼10⁸ stars, the attitude and instrumental settings of the Gaia satellite, and the global parameter γ of the parametrized Post-Newtonian formalism, by solving a system of linear equations, A × x = b , with the LSQR iterative algorithm. The coefficient matrix A of the final Gaia data set is large, with ∼10¹¹ × 10⁸ elements, and sparse, reaching a size of ∼10-100 TB, typical for the Big Data analysis, which requires an efficient parallelization to obtain scientific results in reasonable timescales. The speedup of the CUDA code over the original AVU-GSR solver, parallelized on the CPU with MPI + OpenMP, increases with the system size and the number of resources, reaching a maximum of ∼14×, >9× over the OpenACC application. This result is obtained by comparing the two codes on the CINECA cluster Marconi100, with 4 V100 GPUs per node. After verifying the agreement between the solutions of a set of systems with different sizes computed with the CUDA and the OpenMP codes and that the solutions showed the required precision, the CUDA code was put in production on Marconi100, essential for an optimal AVU-GSR pipeline and the successive Gaia Data Releases. This analysis represents a first step to understand the (pre-)Exascale behavior of a class of applications that follow the same structure of this code. In the next months, we plan to run this code on the pre-Exascale platform Leonardo of CINECA, with 4 next-generation A200 GPUs per node, toward a porting on this infrastructure, where we expect to obtain even higher performances. © 2023. The Author(s). Published by IOP Publishing Ltd on behalf of the Astronomical Society of the Pacific (ASP).

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computing Electronic Correlation Energies using Linear Depth quantum Circuits

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arXiv 2022年

作者： Chee, Chong Hian Mak, Adrian M. Leykam, Daniel Barkoutsos, Panagiotis Kl. Angelakis, Dimitris G. Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore117543 Singapore Institute of High Performance Computing 1 Fusionopolis Way #16-16 Connexis Singapore138632 Singapore Ibm Quantum Ibm Research Zurich Säumerstrasse 4 Rüschlikon8803 Switzerland School of Electrical and Computer Engineering Technical University of Crete Chania73100 Greece AngelQ Quantum Computing 531A Upper Cross Street #04-95 Hong Lim Complex Singapore051531 Singapore

Efficient computation of molecular energies is an exciting application of quantum computing for quantum chemistry, but current noisy intermediate-scale quantum (NISQ) devices can only execute shallow circuits, limiting existing variational quantum algorithms, which require deep entangling quantum circuit ansatzes to capture correlations, to small molecules. Here we demonstrate a variational NISQ-friendly algorithm that generates a set of mean-field Hartree-Fock (HF) ansatzes using multiple shallow circuits with depth linear in the number of qubits to estimate electronic correlation energies via perturbation theory up to the second order. We tested the algorithm on several small molecules, both with classical simulations including noise models and on cloud quantum processors, showing that it not only reproduces the equilibrium molecular energies but it also captures the perturbative electronic correlation effects at longer bond distances. As fidelities of quantum processors continue to improve our algorithm will enable the study of larger molecules compared to other approaches requiring higher-order polynomial circuit depth. © 2022, CC BY.

关键词： quantum chemistry

Galaxy populations of ProtoClusters in cosmological hydrodynamical simulations

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arXiv 2025年

作者： Esposito, Michela Borgani, Stefano Strazzullo, Veronica Pannella, Maurilio Granato, Gian Luigi Ragone-Figueroa, Cinthia Saro, Alex Nonino, Mario Valentini, Milena Department of Physics University of Trieste via G. Tiepolo 11 TriesteI-34131 Italy INAF - Observatory of Trieste via G. Tiepolo 11 TriesteI-34143 Italy IFPU - Institute for Fundamental Physics of The Universe via Beirut 2 TriesteI-34014 Italy INFN - Istituto Nazionale di Fisica Nucleare via Valerio 2 TriesteI-34127 Italy ICSC - Italian Research Center on High Performance Computing Big Data and Quantum Computing via Magnanelli 2 Casalecchio di Reno40033 Italy Universidad Nacional de Córdoba Laprida 854 CórdobaX5000BGR Argentina

Context. The study of protoclusters at cosmic noon is essential for understanding the impact on galaxy properties of the environment and of the transformational processes occurring during this epoch. Aims. This work tests the predictions on galaxy evolution of the DIANOGA cosmological hydrodynamical simulations of cluster progenitors at z = 2.2, comparing them with observations, and investigates the environmental effects on galaxy populations by comparing simulated protoclusters with an average volume of the Universe. Methods. We analyze 14 DIANOGA protoclusters and a cosmological box of 49 cMpc/h per side, simulated with OpenGADGET3. We compare predictions and observations of the galaxy stellar mass function (GSMF), the star-forming Main Sequence (MS), the fraction of star-forming gas, gas depletion times, and the fraction of quenched galaxies. We also compute the rest-frame UV-to-NIR colors of galaxies with the SKIRT-9 radiation transfer code, to analyze UVJ diagrams. Results. We showed that the DIANOGA simulations produce a GSMF in broad agreement with observations. The simulated GSMF shows a higher fraction of high-mass galaxies (M∗ > 1010 M☉) in massive halos in protoclusters, compared to the cosmological box. The same signal, albeit with lower significance, is also observed in the wide-field protocluster structures, indicating an accelerated evolution of galaxies before their infall into massive halos. Our simulations underestimate star formation rates of galaxies both in protoclusters and in the cosmological box, compared to observed counterparts, due to an underestimation of the star-forming gas reservoirs. We find a weak suppression of SFRs in protocluster galaxies (∼ 0.05 dex), compared to the cosmological box, increasing up to ∼ 0.25 dex in massive halos, reflecting suppressed cold gas reservoirs. The quenched galaxy fraction varies significantly across different protocluster halos, consistent with observations at z ∼ 2 − 2.5. The simulations show a stron

关键词： Cosmology

Meta Actor-Critic Framework for Multi-Agent Reinforcement Learning 21

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Meta Actor-Critic Framework for Multi-Agent Reinforcement Le...

Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

作者： Jiateng Huang Wanrong Huang Dan Wu Long Lan Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology China Artifcial Intelligence Research Center National Innovation Institute of Defense Technology China College of Computer & Hefei Interdisciplinary Center National University of Defense Technology China

ISBN: (纸本)9781450384087

In recent years, multi-agent reinforcement learning has received sustained attention in the last few years. The typical Actor-Critic methods learn mappings directly from observation to action without understanding the tasks themselves. In this paper, we present a meta actor-critic framework for meta-actor critique based on observational learning processes and the additional loss of meta-learning actors to accelerate and improve multi-agent learning across agents' experiences. Within our framework, all agents are deliberately designed to share the same meta-critic loss to achieve the optimum actor learning progress. Meanwhile, by minimizing the loss of meta-actors, the meta actor learns the features of the meta-observation, leading to better actions. We implemented the MADDPG and MATD3 algorithms in our proposed framework and empirically demonstrated the superiority of our framework on two kinds of multi-agent tasks. In addition, the framework can be flexibly incorporated into various contemporary multi-agent Actor-Critic methods.

关键词： Reinforcement learning meta-learning multi-agent system

HeadCap: A Hierarchical Encoder-And-Decoder Image Captioning Model

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HeadCap: A Hierarchical Encoder-And-Decoder Image Captioning...

2020 International Conference on Intelligent computing, Automation and Systems, ICICAS 2020

作者： Yang, Wenjing Wang, Shiwei Lan, Long Institute for Quantum Information State Key Laboratory of High Performance Computing National University of Defense Technology Changsha410073 China Yunnan North Optical Electronic Instrument Co. Ltd Kunming650000 China

ISBN: (纸本)9781728191461

Image captioning achieves its goal by two steps traditionally, it first extracts image features using deep networks, and then translates the features into correct text descriptions. Though recent compelling captioning results have surged continuously, the bridge between visual cues and texts is usually limited by weak single-layer CNN features and one-word one-attention strategy. In this paper, we propose a simple yet effective Hierarchical Encoder-And-Decoder image CAPtioning model (HeadCap) to capture visual cues across different levels whilst conducting one-word multi-attention scheme in a unified hierarchical architecture. In specific, we collect multi-layer features from feature pyramid network (FPN), which allows stringing visual features across different levels hierarchically. More importantly, a multi-attention LSTM module (mLSTM) is established on such hierarchical features, which performs multiple attentions over hierarchical features progressively when predicting a word. This provides LSTM more attention chance to reduce the risk of the mismatch between visual cues and texts, and further to bridge the gap between each other. Experiments on MSCOCO image captioning dataset show that HeadCap yields favorable performance against several well-behaved deep captioning models. © 2020 IEEE.

关键词： Network coding

Optimal quantum State Tomography via Weak Value

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arXiv 2024年

作者： Zhu, Xuanmin Zhang, Dezheng Gao, Runping Wei, Qun Liu, Lixia Luo, Zijiang Center for Quantum Information School of Information Guizhou University of Finance and Economics Guizhou Guiyang550025 China International Joint Research Center for Data Science and High-Performance Computing School of Information Guizhou University of Finance and Economics Guizhou Guiyang550025 China School of Physics and Optoelectronic Engineering Xidian University Xi’an710071 China School of Mathematics and Statistics Xidian University Xi’an710071 China Institute of Intelligent Manufacturing Shunde Polytechnic Guangdong Shunde 528300 China

To improve the efficiency of the state tomography strategy via weak value, we have searched the optimal coupling strength between the system and measuring device. For an arbitrary d-dimensional quantum system, the optimal strengths being used in measuring the real and imaginary parts of the density matrix are obtained. The optimal efficiency of the state tomography has also been studied by using mean square error. The minimal mean square errors in the reconstructed density matrices have been derived. The state tomography strategy studied in this article may be useful in the measurement of the unknown quantum states. Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

Precise and scalable evaluation on the robustness metric of neural networks as classifiers

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Precise and scalable evaluation on the robustness metric of ...

作者： Yangyi Hu Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology College of Computer Science National University of Defense Technology

It is well known that the minimum adversarial distortion associated with a specific sample x reflects the local robustness of neural ***,it is intractable to solve the optimization problem related to the minimum adversarial distortion for general neural network cause it is *** have studied the lower bound or upper bound of the minimum adversarial distortion to give a robustness metrics for neural networks,such as CLEVER score and CW *** this paper,we provide a formal robustness guarantee to transform the robustness analysis into two sub-problems:（1）,compute out the maximum of the objective function g_t（r~t）;（2）,generate a sequence {r_n~t} *** r_n~t is the minimum adversarial distortion for targeted *** on this transformation,we propose an efficient and effective algorithm to directly estimate the instance-specific minimum adversarial distortion on the norm of the input manipulation required to change the classifier *** results on two data-sets,MNIST and CIFAR,show that our measure of robustness is between the lower bound given by CLEVER and the upper bound by CW,indicating our approach gives a precise measure of the robustness of neural *** addition,the powerful mathematical technique Extreme Value Estimation enables our algorithm computationally feasible for large neural *** the best of our knowledge,our algorithm is the first attack-independent approach to directly evaluate the minimum adversarial distortion as a robustness metric for neural network.

关键词： minimum adversarial distortion robustness metric instance-specific attack-independent

An Unbiased quantum Random Number Generator Based on Boson Sampling

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arXiv 2022年

作者： Shi, Jinjing Zhao, Tongge Wang, Yizhi Yu, Chunlin Lu, Yuhu Shi, Ronghua Zhang, Shichao Wu, Junjie School of Computer Science and Engineering Central South University Changsha410083 China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China China Greatwall Quantum Laboratory China Greatwall Technology Group CO. LTD. Changsha410073 China

It has been proven that Boson sampling is a much promising model of optical quantum computation, which has been applied to designing quantum computer successfully, such as "Jiuzhang". However, the meaningful randomness of Boson sampling results, whose correctness and significance were proved from a specific quantum mechanical distribution, has not been utilized or exploited. In this research, Boson sampling is applied to design a novel quantum Random Number Generator (QRNG) by fully exploiting the randomness of Boson sampling results, and its prototype system is constructed with the programmable silicon photonic processor, which can generate uniform and unbiased random sequences and overcome the shortcomings of the existing discrete QRNGs such as source-related, high demand for the photon number resolution capability of the detector and slow self-detection generator speed. Boson sampling is implemented as a random entropy source, and random bit strings with satisfactory randomness and uniformity can be obtained after post-processing the sampling results. It is the first approach for applying the randomness of Boson sampling results to develop a practical prototype system for actual tasks, and the experiment results demonstrate the designed Boson sampling-based QRNG prototype system pass 15 tests of the NIST SP 800-22 statistical test component, which prove that Boson sampling has great potential for practical applications with desirable performance besides quantum advantage. Copyright © 2022, The Authors. All rights reserved.

关键词： Sampling

Explicitly represent the boundary of ReLU NN as a classifier and measure its robustness

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Explicitly represent the boundary of ReLU NN as a classifier...

Adversarial examples pose a great threat to the application of neural network as a classifier in areas with high security ***,the adversarial property of neural network is closely related to the ***,works barely give a rigorous description of *** paper for the first time studies the boundary of ReLU NN,which separates the sample space into distinct cells,each of which belongs to the same *** the demonstration,we discuss the algebraic property of border points upon the separating boundary and the topological difference between border points and odd *** derive Theorem Ⅲ.7 to give a rigorous,comprehensive and concise description on the boundary of ReLU ***,an algorithm,based on the description,is proposed to give a standard and exact metric for the local robustness of ReLU *** metric gives the local adversarial property of NN and reflects some aspects of its security performance,*** nimimum distortion needed to craft an adversarial *** the best of our knowledge,this is the first work proposed to give a rigorous and example-specific metric for the local robustness of ReLU NN.

关键词： Index Terms-adversarial examples boundary odd points local robustness metric