Search Results - "Schneidenbach, Lars"

Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET by Müller, Detlef, Böckmann, Christine, Kolgotin, Alexei, Schneidenbach, Lars, Chemyakin, Eduard, Rosemann, Julia, Znak, Pavel, Romanov, Anton

“…We present a summary on the current status of two inversion algorithms that are used in EARLINET (European Aerosol Research Lidar Network) for the inversion of…”
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STRonG: System Topology Risk Analysis on Graphs by Schneidenbach, Lars, Koteshwara, Sandhya, Ohmacht, Martin, Mohan, Apoorve, Lee, Eun Kyung

“…Production systems run complex stacks comprising constantly-evolving hardware and software components. Vulnerabilities in such stacks continuously pose…”
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Parallel software for retrieval of aerosol distribution from LIDAR data in the framework of EARLINET-ASOS by Osterloh, Lukas, Pérez, Carlos, Böhme, David, Baldasano, José Maria, Böckmann, Christine, Schneidenbach, Lars, Vicente, David

“…We present new software for the retrieval of the volume distribution – and thus, other relevant microphysical properties such as the effective radius – of…”
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The infrastructure powering IBM's Gen AI model development by Gershon, Talia, Seelam, Seetharami, Belgodere, Brian, Bonilla, Milton, Hoang, Lan, Barnett, Danny, Chung, I-Hsin, Mohan, Apoorve, Luo, Lixiang, Walkup, Robert, Salaria, Shweta, Dombrowa, Marc, Park, Yoonho, Alim, Alim, Maniotis, Pavlos, Schares, Laurent, Karacali-Akyamac, Bengi, Wen, Sophia, Choochotkaew, Sunyanan, Yoshimura, Takeshi, Misale, Claudia, Elengikal, Tonia, Connor, Kevin O, Liu, Zhuoran, Molina, Richard, Laibinis, Christopher, Tarasov, Vasily, Guthridge, Scott, Cohn, Jeremy, Eshel, Marc, Muench, Paul, Pointer, William, Wyskida, Drew, Krull, Bob, Cornejo, William, Walter, John, Malone, Colm, Hinds, Nigel, Calio, Bob, Druyan, Pavel, Kilduff, Robert, Kienle, John, McStay, Connor, Figueroa, Andrew, Fost, Edie, Roma, Gina, Fonseca, Jake, Levy, Ido, Malki, Amir, Schneider, Lion, Moshref, Shekeba, Dodin, Olga, Rippon, Bill, Wrieth, Henry, Ganci, John, Colino, Johnny, Habeger-Rose, Donna, Gidh, Aditya, Varma, Rambilas, Rumana, Rumana, Sharma, Shubham, Mishra, Mayank, Panda, Rameswar, Prasad, Aditya, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Cox, David, Agrawal, Dakshi, Thorstensen, Drew, Belog, Joel, Tang, Brent, Biswas, Amitabha, Maheshwari, Anup, Gampel, Eran, Van Patten, Jason, Bogin, Yigal, Reitz, Brian, Welp, Rick, Arvelo, Amilcar, Chu, King, Seminaro, Ed, Schram, Andrew, Eickhoff, Felix, Hanson, William, Joseph, Dinakaran, Chaudhary, Piyush, Jones, Wesley, Guthrie, Robert, Bostic, Chris, Islam, Rezaul, Sawdon, Wayne, Lewars, John, Klos, Matthew, Spriggs, Michael, McMillan, Bill, Gao, George, Katarki, Tushar, Shi, Zenghui, Malleni, Sai Sindhur

“…AI Infrastructure plays a key role in the speed and cost-competitiveness of developing and deploying advanced AI models. The current demand for powerful AI…”
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Key/Value-Enabled Flash Memory for Complex Scientific Workflows with On-Line Analysis and Visualization by Eilemann, Stefan, Delalondre, Fabien, Bernard, Jon, Planas, Judit, Schuermann, Felix, Biddiscombe, John, Bekas, Costas, Curioni, Alessandro, Metzler, Bernard, Kaltstein, Peter, Morjan, Peter, Fenkes, Joachim, Bellofatto, Ralph, Schneidenbach, Lars, Ward, T. J. Christopher, Fitch, Blake G.

“…Scientific workflows are often composed of compute-intensive simulations and data-intensive analysis and visualization, both equally important for…”
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Challenges of MPI over IPv6 by Knoth, A., Kauhaus, C., Fey, D., Schneidenbach, L., Schnor, B.

“…The message passing interface (MPI) [17] is the most widely used message passing library for parallel applications on compute clusters. Here, we present our…”
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Loaded: Server Load Balancing for IPv6 by Friedrich, S., Krahmer, S., Schneidenbach, L., Schnor, B.

“…With the next generation Internet protocol IPv6 at the horizon, it is time to think about how applications can migrate to IPv6. Web traffic is currently one of…”
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