The proposed project involves the support for Spark parallelization in TMVA. Machine learning procedures like k-fold cross validation, hyper...
Integrating Machine Learning in Jupyter Notebooks
Attila Bagoly
Toolkit for Multivariate Data Analysis (TMVA) is a framework (part of data analysis framework ROOT) which contains ML packages, frequently used by...
GPU-accelerated Deep Neural Networks in TMVA
Simon Pfreundschuh
During recent years deep learning techniques haven proven extremely powerful in many different applications and have successfully been applied to...
BLonD code optimization strategy for parallel and concurrent architectures
Oleg.jakushkin
Our objective is to determine the best architectural and parallelization options for the BLonD future C++ code base. Project includes:
Existing...
Reflection-based Python-C++ language bindings: cppyy - Integrate the Cling backend into PyPy/cppyy
Aditi Dutta
For the purpose of High Energy Physics (HEP) Experiments, the framework required should be able to support the scale and complexity of HEP codes....
Implementation of task-based transport for GeantV
Joel Fuentes
The current parallelism model of GeantV is data-oriented where a static set of threads is predefined to perform the work, the set of transport...
New Physics Model in Sixtrack package
vikasnt
SixTrack is a 6D particle tracking code used to compute the trajectories of individual relativistic charged particles in circular accelerators. It...
Multistep methods for integrating trajectory in field
Dmitry Sorokin
Implementation of Adams multistep methods in Geant4
Performance 3D Web Graphics with Interactive Features for JSRoot
Peter Whidden
The ROOT project is developing a JavaScript library for reading and rendering ROOT objects in modern web browsers. The rendering of 3D objects is...
TMVA Project in Machine Learning
Abhinav Moudgil
Toolkit for Multivariate Data Analysis (TMVA), integrated into the ROOT framework hosts a variety of machine classification methods which have become...
