M
Mads Ruben Burgdorff Kristensen
Researcher at University of Copenhagen
Publications - 27
Citations - 311
Mads Ruben Burgdorff Kristensen is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Python (programming language) & NumPy. The author has an hindex of 9, co-authored 27 publications receiving 257 citations. Previous affiliations of Mads Ruben Burgdorff Kristensen include Nvidia & Niels Bohr Institute.
Papers
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Journal ArticleDOI
DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping.
Steffen Bollmann,Kasper Gade Bøtker Rasmussen,Mads Ruben Burgdorff Kristensen,Rasmus Guldhammer Blendal,Lasse Riis Østergaard,Maciej Plocharski,Kieran O'Brien,Christian Langkammer,Andrew L. Janke,Markus Barth +9 more
TL;DR: DeepQSM can invert the magnetic dipole kernel convolution and delivers robust solutions to this ill-posed problem, enabling identification of deep brain substructures and provide information on their respective magnetic tissue properties.
Proceedings ArticleDOI
Exploring and analyzing the real impact of modern on-package memory on HPC scientific kernels
Ang Li,Weifeng Liu,Mads Ruben Burgdorff Kristensen,Brian Vinter,Hao Wang,Kaixi Hou,Andres Marquez,Shuaiwen Leon Song +7 more
TL;DR: A comprehensive evaluation for a wide spectrum of scientific kernels with a large amount of representative inputs on two Intel OPMs, guided by general optimization models, demonstrates OPM's effectiveness for easing programmers' tuning efforts to reach ideal throughput for both compute-bound and memory-bound applications.
Proceedings ArticleDOI
Bohrium: A Virtual Machine Approach to Portable Parallelism
TL;DR: Bohrium is a runtime-system for mapping vector operations onto a number of different hardware platforms, from simple multi-core systems to clusters and GPU enabled systems, and can be used for any programming language but for now, the supported languages are limited to Python, C++ and the Net framework.
Proceedings ArticleDOI
Numerical Python for scalable architectures
TL;DR: DistNumPy, a library for doing numerical computation in Python that targets scalable distributed memory architectures, is introduced and it is found that it is possible to obtain significant speedup from using the new array-backend without changing the original Python code.