Treffer 1 - 20 von 45

1

Parallel Computing and Scaling with Dask
Petrelli, Maurizio ; Petrelli, Maurizio
Machine Learning for Earth Sciences : Using Python to Solve Geological Problems. :161-175

E-Book
2

Accelerating Python Applications with Dask and ProxyStore
Pauloski, J. Gregory ; Rydzy, Klaudiusz ; Hayot-Sasson, Valerie ; et al.

Computer Science - Distr...
Report
3

Scaling Deep Learning-Based Analysis of High-Resolution Satellite Imagery with Distributed Processing
Nguyen, Mai H. ; Li, Jiaxin ; Crawl, Daniel ; et al.
2019 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2019 IEEE International Conference on. :5437-5443 Dec, 2019

Konferenz
4

Dask & Numba: Simple libraries for optimizing scientific python code
Crist, James
2016 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2016 IEEE International Conference on. :2342-2343 Dec, 2016

Konferenz
5

STARE-based Integrative Analysis of Diverse Data Using Dask Parallel Programming Demo Paper
Rilee, Michael ; Griessbaum, Niklas ; Kuo, Kwo-Sen ; et al.
Proceedings of the 28th International Conference on Advances in Geographic Information Systems. :417-420

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6

Reshaping High Energy Physics Applications for Near-Interactive Execution Using TaskVine
Sly-Delgado, Barry ; Tovar, Ben ; Zhou, Jin ; et al.
SC24: International Conference for High Performance Computing, Networking, Storage and Analysis SC High Performance Computing, Networking, Storage and Analysis, SC24: International Conference for. :1-13 Nov, 2024

Konferenz
7

scores: A Python package for verifying and evaluating models and predictions with xarray
Leeuwenburg, Tennessee ; Loveday, Nicholas ; Ebert, Elizabeth E. ; et al.
Journal of Open Source Software, Volume 9, Issue 99, Page 6889, July 2024

Physics - Atmospheric an... Statistics - Application...
Report
9

A Pilot Analysis Facility at CERN: Architecture, Implementation and First Evaluation.
Castro, Diogo ; Delgado Peris, Antonio ; García García, Enrique ; et al.
EPJ Web of Conferences; 10/7/2025, Vol. 337, p1-8, 8p

Konferenz
11

Optimizing Scientific Simulations with Python-Driven Parallelism on Azure Batch: A Hybrid Cloud Architecture for High-Performance Computing
null Dheerendra Yaganti
International Journal of Advanced Research in Science, Communication and Technology. :980-985

Fachzeitschrift
12

Automating and Scaling Task-Level Parallelism of Tightly Coupled Models via Code Generation
Roozmeh, Mehdi ; Kondov, Ivan ; Goos, Gerhard, Founding Editor ; et al.
Computational Science – ICCS 2022 : 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV. 13353:69-82

E-Book
13
14

COMPARATIVE ANALYSIS OF METHODS FOR PREDICTION CONTINUOUS NUMERICAL FEATURES ON BIG DATASETS.
Kinshakov, Eduard ; Parfenenko, Yuliia ; Shendryk, Vira
Technology Audit & Production Reserves; 2021, Vol. 6 Issue 2, p15-17, 3p

BIG data DECISION trees COMPARATIVE method RANDOM forest algorithms PYTHON programming langu... COMPUTER engineering
Fachzeitschrift
15

NumS: Scalable Array Programming for the Cloud
Elibol, Melih ; Benara, Vinamra ; Yagati, Samyu ; et al.

E-Ressource
16

Comparative analysis of methods for prediction continuous numerical features on big datasets
Technology audit and production reserves; Vol. 6 No. 2(62) (2021): Information and control systems; 15-17; Technology audit and production reserves; 15-17; Technology audit and production reserves; 15-17; 2706-5448; 2664-9969

E-Ressource
17

holoviz/datashader: Version 0.17.0
James A. Bednar ; Joseph Crail ; Ian Thomas ; et al.

E-Ressource
18

Comparative analysis of methods for prediction continuous numerical features on big datasets
Technology audit and production reserves; Vol. 6 No. 2(62) (2021): Information and control systems; 15-17
Technology audit and production reserves; Том 6 № 2(62) (2021): Информационно-управляющие системы; 15-17
Technology audit and production reserves; Том 6 № 2(62) (2021): Інформаційно-керуючі системи; 15-17

великі дані аналіз даних data analysis випадковий ліс... машинне навчання... машинное обучение...
Fachzeitschrift
19

On the Realisation of a Workflow for Continuous Earth Observation of Forest Dynamics: A Performance Engineering Challenge
Herbst, Nikolas ; Jaggy, Niklas ; Dingel, David ; et al.

forest management satellite data forest dynamics performance
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