Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ludovico Bianchi"'
Autor:
Devarshi Ghoshal, Ludovico Bianchi, Abdelilah Essiari, Drew Paine, Sarah S. Poon, Michael Beach, Alpha T. N'Diaye, Patrick Huck, Lavanya Ramakrishnan
Workflows are increasingly processing large volumes of data from scientific instruments, experiments and sensors. These workflows often consist of complex data processing and analysis steps that might include a diverse ecosystem of tools and also oft
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97c03786b3ec19f0c86136f500be695e
https://escholarship.org/uc/item/2709n3mt
https://escholarship.org/uc/item/2709n3mt
Autor:
Lavanya Ramakrishnan, Michael Beach, Abdelilah Essiari, Ludovico Bianchi, Devarshi Ghoshal, Drew Paine
Science Capsule is a free open source software that allows researchers to automatically capture their end-to-end workflows including the scripts, data, and execution environment. Science Capsule monitors the workflow environment to capture the proven
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96900122fbaf284f43e7c5beda755b4b
Autor:
Lavanya Ramakrishnan, Shreyas Cholia, Lindsey J. Heagy, Ludovico Bianchi, Devarshi Ghoshal, Fernando Perez, Jon Hays, Drew Paine, Matthew L. Henderson
Publikováno v:
UrgentHPC@SC
The growth in scientific data volumes has resulted in a need to scale up processing and analysis pipelines using High Performance Computing (HPC) systems. These workflows need interactive, reproducible analytics at scale. The Jupyter platform provide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f08b129830980d908f9456b5414e2964
https://escholarship.org/uc/item/0sv9g4gn
https://escholarship.org/uc/item/0sv9g4gn
Autor:
Alina Lazar, Deb Agarwal, Lavanya Ramakrishnan, Ludovico Bianchi, Gilberto Pastorello, Payton Linton, Devarshi Ghoshal, William Melodia, Kesheng Wu
Publikováno v:
IEEE BigData
Today, scientific experiments and simulations produce massive amounts of heterogeneous data that need to be stored and analyzed. Given that these large datasets are stored in many files, formats and locations, how can scientists find relevant data, d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e13d0329ed6de78b90d3c5f72ade31ec
https://escholarship.org/uc/item/8193v6sm
https://escholarship.org/uc/item/8193v6sm