Suchergebnisse - parallel programming environment CURA*

Leveling the Playing Field With AI: Special Olympics's Mary Davis von Ransbotham, Sam, Khodabandeh, Shervin

“… [...]we do that through using the power of sport and programming in other areas, like education that you mentioned, health, and leadership …”
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Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges von Zhao, Zhiming, Hellström, Margareta

“… This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 …”
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Cloud-enabled style-aware artwork composite recommendation based on correlation graph von Guo, Hongyuan, Anari, Maryam Saberi, Rezaee, Khosro

“… Recommending visually coherent and stylistically diverse sets of artworks is a challenging task in digital curation, interior design, and personalized visual content services …”
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RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/Bioconductor von Pallotta, Simone, Cascianelli, Silvia, Masseroli, Marco

“… Background Heterogeneous omics data, increasingly collected through high-throughput technologies, can contain hidden answers to very important and still …”
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Learning About and Over Networks: Optimized Designs for Network Tomography and Decentralized Learning von Chiu, Cho-Chun

“… Our four pieces of work focus on optimizing the designs of network tomography, data curation, and model …”
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GPU-accelerated algorithms for many-particle continuous-time quantum walks von Piccinini, Enrico, Benedetti, Claudia, Siloi, Ilaria, Paris, Matteo G.A., Bordone, Paolo

“…  Hamiltonians containing stochastic terms. To this aim, we suggest a parallel algorithm based on the Taylor series expansion of the evolution operator, and compare its performances with those of algorithms based on the exact diagonalization …”
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MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline von Moon, Joseph, Bremer, Peer-Timo, Mukherjee, Pratik, Markowitz, Amy J, Palacios, Eva M, Rodriguez, Alexis, Xiao, Yuaki, Manley, Geoffrey T, Madduri, Ravi K

“… We developed MaPPeRTrac, a diffusion MRI tractography pipeline that simplifies and vastly accelerates this process on a wide range of high performance computing environments …”
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Role of High-Performance Computing in Deep Learning von Wickramasinghe, Pulasthi Supun

“… When considering real-world deep learning applications, most are comprised of two major stages. The first stage is data pre-processing and curation, and the second is model training and inference …”
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eWaterCycle II von Hut, Rolf, Drost, Niels, Van Hage, Willem, Van De Giesen, Nick

“… output to make claims on the global state of the hydrological cycle [1], [2]. Parallel to this development …”
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Evaluating Hadoop for Data-Intensive Scientific Operations von Fadika, Z., Govindaraju, M., Canon, R., Ramakrishnan, L.

“… Emerging sensor networks, more capable instruments, and ever increasing simulation scales are generating data at a rate that exceeds our ability to effectively manage, curate, analyze, and share …”
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