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Cosmological Boltzmann codes are often used by researchers for calculating the CMB angular power spectra from different theoretical models, for cosmological parameter estimation, etc. Therefore, the accuracy of a Boltzmann code is of utmost…

Cosmology and Nongalactic Astrophysics · Physics 2025-09-09 Santanu Das , Anh Phan

Concurrent computation and communication (C3) is a pervasive paradigm in ML and other domains, making its performance optimization crucial. In this paper, we carefully characterize C3 in ML on GPUs, which are most widely deployed for ML…

Hardware Architecture · Computer Science 2025-04-28 Anirudha Agrawal , Shaizeen Aga , Suchita Pati , Mahzabeen Islam

For a specific quantum chip, multi-programming helps to improve overall throughput and resource utilization. However, the previous solutions for mapping multiple programs onto a quantum chip often lead to resource under-utilization, high…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-04-28 Lei Liu , Xinglei Dou

Within the scope of the Planck IDIS (Integrated Data Information System) project we have started to develop the data model for time-ordered data and full-sky maps. The data model is part of the Data Management Component (DMC), a software…

Astrophysics · Physics 2009-10-31 G. Giardino , A. J. Banday , K. Bennett , P. Fosalba , K. M. Gorski , W. O'Mullane , J. Tauber , C. Vuerli

Bayesian Neural Networks (BNNs) provide superior estimates of uncertainty by generating an ensemble of predictive distributions. However, inference via ensembling is resource-intensive, requiring additional entropy sources to generate…

Emerging Technologies · Computer Science 2025-05-20 Prabodh Katti , Clement Ruah , Osvaldo Simeone , Bashir M. Al-Hashimi , Bipin Rajendran

To efficiently probe primordial non-Gaussianity using Cosmic Microwave Background (CMB) data, we require theoretical predictions that are factorizable, \textit{i.e.}\ those whose kinematic dependence can be separated. This property does not…

Cosmology and Nongalactic Astrophysics · Physics 2025-11-25 Oliver H. E. Philcox , Kunhao Zhong , Salvatore Samuele Sirletti

The rapid scaling of large language models (LLMs) has unveiled critical limitations in current hardware architectures, including constraints in memory capacity, computational efficiency, and interconnection bandwidth. DeepSeek-V3, trained…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-24 Chenggang Zhao , Chengqi Deng , Chong Ruan , Damai Dai , Huazuo Gao , Jiashi Li , Liyue Zhang , Panpan Huang , Shangyan Zhou , Shirong Ma , Wenfeng Liang , Ying He , Yuqing Wang , Yuxuan Liu , Y. X. Wei

This paper presents and justifies an open benchmark suite named BEEBS, targeted at evaluating the energy consumption of embedded processors. We explore the possible sources of energy consumption, then select individual benchmarks from…

Performance · Computer Science 2013-10-01 James Pallister , Simon Hollis , Jeremy Bennett

Concept bottleneck model (CBM) is a ubiquitous method that can interpret neural networks using concepts. In CBM, concepts are inserted between the output layer and the last intermediate layer as observable values. This helps in…

Machine Learning · Statistics 2023-03-17 Naoki Hayashi , Yoshihide Sawada

The data analysis of current Cosmic Microwave Background (CMB) experiments like BOOMERanG or MAXIMA poses severe challenges which already stretch the limits of current (super-) computer capabilities, if brute force methods are used. In this…

Astrophysics · Physics 2009-11-06 O. Doré , R. Teyssier , F. R. Bouchet , D. Vibert , S. Prunet

Detecting buffer overruns from a source code is one of the most common and yet challenging tasks in program analysis. Current approaches have mainly relied on rigid rules and handcrafted features devised by a few experts, limiting…

Software Engineering · Computer Science 2017-03-08 Min-je Choi , Sehun Jeong , Hakjoo Oh , Jaegul Choo

Recently developed large language models (LLMs) such as ChatGPT, Claude, and Llama have demonstrated impressive abilities, and even surpass human-level performance in several tasks. Despite their success, the resource-intensive demands of…

Computation and Language · Computer Science 2024-06-17 Jie Wu , Yufeng Zhu , Lei Shen , Xuqing Lu

Training multimodal large language models (MLLMs) is challenged by both model and data heterogeneity. Existing systems redesign the training pipeline to address these challenges, but remain bound by a Pareto frontier between compute and…

Machine Learning · Computer Science 2026-05-26 Zili Zhang , Chengxu Yang , Shenglong Zhang , Chenyu Wang , Yufan Zhang , Tuo Dai , Zhouyang Li , Yuhong Ge , Chao Jin , Xin Jin , Yuliang Liu

The Cosmic Microwave Background (CMB) is an abundant source of cosmological information. However, this information is encoded in non-trivial ways in a signal that is difficult to observe. The resulting challenges in extracting this…

Astrophysics · Physics 2014-10-13 Benjamin D. Wandelt

Climbing Mont Blanc (CMB) is an open online judge used for training in energy efficient programming of state-of-the-art heterogeneous multicores. It uses an Odroid-XU3 board from Hardkernel with an Exynos Octa processor and integrated power…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-10 Lasse Natvig , Torbjørn Follan , Simen Støa , Sindre Magnussen , Antonio Garcia Guirado

Approximate Bayesian Computation (ABC) is a widely applicable and popular approach to estimating unknown parameters of mechanistic models. As ABC analyses are computationally expensive, parallelization on high-performance infrastructure is…

Quantitative Methods · Quantitative Biology 2023-05-02 Emad Alamoudi , Felipe Reck , Nils Bundgaard , Frederik Graw , Lutz Brusch , Jan Hasenauer , Yannik Schälte

Compute-Near-Memory (CNM) systems offer a promising approach to mitigate the von Neumann bottleneck by bringing computational units closer to data. However, optimizing for these architectures remains challenging due to their unique hardware…

Emerging Technologies · Computer Science 2025-08-18 Hamid Farzaneh , Asif Ali Khan , Jeronimo Castrillon

This paper presents the interesting observation that by performing fewer of the optimizations available in a standard compiler optimization level such as -O2, while preserving their original ordering, significant savings can be achieved in…

Performance · Computer Science 2018-06-19 Kyriakos Georgiou , Craig Blackmore , Samuel Xavier-de-Souza , Kerstin Eder

The Planck full mission cosmic microwave background(CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity(NG). Using three classes of optimal bispectrum estimators - separable…

Cosmology and Nongalactic Astrophysics · Physics 2016-07-26 Planck Collaboration , P. A. R. Ade , N. Aghanim , M. Arnaud , F. Arroja , M. Ashdown , J. Aumont , C. Baccigalupi , M. Ballardini , A. J. Banday , R. B. Barreiro , N. Bartolo , S. Basak , E. Battaner , K. Benabed , A. Benoît , A. Benoit-Lévy , J. -P. Bernard , M. Bersanelli , P. Bielewicz , J. J. Bock , A. Bonaldi , L. Bonavera , J. R. Bond , J. Borrill , F. R. Bouchet , F. Boulanger , M. Bucher , C. Burigana , R. C. Butler , E. Calabrese , J. -F. Cardoso , A. Catalano , A. Challinor , A. Chamballu , H. C. Chiang , P. R. Christensen , S. Church , D. L. Clements , S. Colombi , L. P. L. Colombo , C. Combet , F. Couchot , A. Coulais , B. P. Crill , A. Curto , F. Cuttaia , L. Danese , R. D. Davies , R. J. Davis , P. de Bernardis , A. de Rosa , G. de Zotti , J. Delabrouille , F. -X. Désert , J. M. Diego , H. Dole , S. Donzelli , O. Doré , M. Douspis , A. Ducout , X. Dupac , G. Efstathiou , F. Elsner , T. A. Enßlin , H. K. Eriksen , J. Fergusson , F. Finelli , O. Forni , M. Frailis , A. A. Fraisse , E. Franceschi , A. Frejsel , S. Galeotta , S. Galli , K. Ganga , C. Gauthier , T. Ghosh , M. Giard , Y. Giraud-Héraud , E. Gjerløw , J. González-Nuevo , K. M. Górski , S. Gratton , A. Gregorio , A. Gruppuso , J. E. Gudmundsson , J. Hamann , F. K. Hansen , D. Hanson , D. L. Harrison , A. Heavens , G. Helou , S. Henrot-Versillé , C. Hernández-Monteagudo , D. Herranz , S. R. Hildebrandt , E. Hivon , M. Hobson , W. A. Holmes , A. Hornstrup , W. Hovest , Z. Huang , K. M. Huffenberger , G. Hurier , A. H. Jaffe , T. R. Jaffe , W. C. Jones , M. Juvela , E. Keihänen , R. Keskitalo , J. Kim , T. S. Kisner , J. Knoche , M. Kunz , H. Kurki-Suonio , F. Lacasa , G. Lagache , A. Lähteenmäki , J. -M. Lamarre , A. Lasenby , M. Lattanzi , C. R. Lawrence , R. Leonardi , J. Lesgourgues , F. Levrier , A. Lewis , M. Liguori , P. B. Lilje , M. Linden-Vørnle , M. López-Caniego , P. M. Lubin , J. F. Macías-Pérez , G. Maggio , D. Maino , N. Mandolesi , A. Mangilli , D. Marinucci , M. Maris , P. G. Martin , E. Martínez-González , S. Masi , S. Matarrese , P. McGehee , P. R. Meinhold , A. Melchiorri , L. Mendes , A. Mennella , M. Migliaccio , S. Mitra , M. -A. Miville-Deschênes , A. Moneti , L. Montier , G. Morgante , D. Mortlock , A. Moss , M. Münchmeyer , D. Munshi , J. A. Murphy , P. Naselsky , F. Nati , P. Natoli , C. B. Netterfield , H. U. Nørgaard-Nielsen , F. Noviello , D. Novikov , I. Novikov , C. A. Oxborrow , F. Paci , L. Pagano , F. Pajot , D. Paoletti , F. Pasian , G. Patanchon , H. V. Peiris , O. Perdereau , L. Perotto , F. Perrotta , V. Pettorino , F. Piacentini , M. Piat , E. Pierpaoli , D. Pietrobon , S. Plaszczynski , E. Pointecouteau , G. Polenta , L. Popa , G. W. Pratt , G. Prézeau , S. Prunet , J. -L. Puget , J. P. Rachen , B. Racine , R. Rebolo , M. Reinecke , M. Remazeilles , C. Renault , A. Renzi , I. Ristorcelli , G. Rocha , C. Rosset , M. Rossetti , G. Roudier , J. A. Rubiño-Martín , B. Rusholme , M. Sandri , D. Santos , M. Savelainen , G. Savini , D. Scott , M. D. Seiffert , E. P. S. Shellard , M. Shiraishi , K. Smith , L. D. Spencer , V. Stolyarov , R. Stompor , R. Sudiwala , R. Sunyaev , P. Sutter , D. Sutton , A. -S. Suur-Uski , J. -F. Sygnet , J. A. Tauber , L. Terenzi , L. Toffolatti , M. Tomasi , M. Tristram , A. Troja , M. Tucci , J. Tuovinen , L. Valenziano , J. Valiviita , F. Van Tent , P. Vielva , F. Villa , L. A. Wade , B. D. Wandelt , I. K. Wehus , D. Yvon , A. Zacchei , A. Zonca

Bayesian parameter inference is one of the key elements for model selection in cosmological research. However, the available inference tools require a large number of calls to simulation codes which can lead to high and sometimes even…

Cosmology and Nongalactic Astrophysics · Physics 2024-06-10 Sven Günther
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