Zobrazeno 1 - 10
of 33
pro vyhledávání: '"PENKE, CAROLIN"'
Autor:
Ali, Mehdi, Fromm, Michael, Thellmann, Klaudia, Ebert, Jan, Weber, Alexander Arno, Rutmann, Richard, Jain, Charvi, Lübbering, Max, Steinigen, Daniel, Leveling, Johannes, Klug, Katrin, Buschhoff, Jasper Schulze, Jurkschat, Lena, Abdelwahab, Hammam, Stein, Benny Jörg, Sylla, Karl-Heinz, Denisov, Pavel, Brandizzi, Nicolo', Saleem, Qasid, Bhowmick, Anirban, Helmer, Lennard, John, Chelsea, Suarez, Pedro Ortiz, Ostendorff, Malte, Jude, Alex, Manjunath, Lalith, Weinbach, Samuel, Penke, Carolin, Filatov, Oleg, Asaadi, Shima, Barth, Fabio, Sifa, Rafet, Küch, Fabian, Herten, Andreas, Jäkel, René, Rehm, Georg, Kesselheim, Stefan, Köhler, Joachim, Flores-Herr, Nicolas
We present two multilingual LLMs designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European Union. Trained on a dataset comprising around 60% non-English data and utilizing a custom multilingual tokenize
Externí odkaz:
http://arxiv.org/abs/2410.03730
The rapid advancement of machine learning (ML) technologies has driven the development of specialized hardware accelerators designed to facilitate more efficient model training. This paper introduces the CARAML benchmark suite, which is employed to a
Externí odkaz:
http://arxiv.org/abs/2409.12994
Autor:
Herten, Andreas, Achilles, Sebastian, Alvarez, Damian, Badwaik, Jayesh, Behle, Eric, Bode, Mathis, Breuer, Thomas, Caviedes-Voullième, Daniel, Cherti, Mehdi, Dabah, Adel, Sayed, Salem El, Frings, Wolfgang, Gonzalez-Nicolas, Ana, Gregory, Eric B., Mood, Kaveh Haghighi, Hater, Thorsten, Jitsev, Jenia, John, Chelsea Maria, Meinke, Jan H., Meyer, Catrin I., Mezentsev, Pavel, Mirus, Jan-Oliver, Nassyr, Stepan, Penke, Carolin, Römmer, Manoel, Sinha, Ujjwal, Vieth, Benedikt von St., Stein, Olaf, Suarez, Estela, Willsch, Dennis, Zhukov, Ilya
Publikováno v:
2024 SC24: International Conference for High Performance Computing, Networking, Storage and Analysis SC
Benchmarks are essential in the design of modern HPC installations, as they define key aspects of system components. Beyond synthetic workloads, it is crucial to include real applications that represent user requirements into benchmark suites, to gua
Externí odkaz:
http://arxiv.org/abs/2408.17211
We devise a spectral divide-and-conquer scheme for matrices that are self-adjoint with respect to a given indefinite scalar product (i.e. pseudosymmetic matrices). The pseudosymmetric structure of the matrix is preserved in the spectral division, suc
Externí odkaz:
http://arxiv.org/abs/2203.08900
We present methods for computing the generalized polar decomposition of a matrix based on the dynamically weighted Halley (DWH) iteration. This method is well established for computing the standard polar decomposition. A stable implementation is avai
Externí odkaz:
http://arxiv.org/abs/2104.06659
Autor:
Benner, Peter, Penke, Carolin
Optical properties of materials related to light absorption and scattering are explained by the excitation of electrons. The Bethe-Salpeter equation is the state-of-the-art approach to describe these processes from first principles (ab initio), i.e.
Externí odkaz:
http://arxiv.org/abs/2008.08825
Autor:
Benner, Peter, Penke, Carolin
For a given matrix, we are interested in computing GR decompositions $A=GR$, where $G$ is an isometry with respect to given scalar products. The orthogonal QR decomposition is the representative for the Euclidian scalar product. For a signature matri
Externí odkaz:
http://arxiv.org/abs/2006.06558
We present a high-performance solver for dense skew-symmetric matrix eigenvalue problems. Our work is motivated by applications in computational quantum physics, where one solution approach to solve the so-called Bethe-Salpeter equation involves the
Externí odkaz:
http://arxiv.org/abs/1912.04062
Publikováno v:
In Parallel Computing August 2020 96
Publikováno v:
ISC High Performance 2023, ISC23, Hamburg, Germany, 2023-05-21-2023-05-25
OpenGPT-X is a German initiative to build and train large language models (LLMs). The project aims at providing an open alternative to LLMs which are up to now private property, along with a platform for researching methods to train multilingual LLMs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3364::127c0af57616fa80004aed49fe5021b3
https://hdl.handle.net/2128/34532
https://hdl.handle.net/2128/34532