The SFT is part of CERN (European Organization for Nuclear Research).

Technologies
python, javascript, c++, clang
Topics
machine learning, cloud, numerical and data analysis software, simulation software
The SFT is part of CERN (European Organization for Nuclear Research).

The SFT (Software for Experiments) group is part of CERN (European Organization for Nuclear Research, http://www.cern.ch), and focuses on providing common software for its experiments. CERN is one of the world’s largest and most exciting centers for fundamental physics research. Experiments at CERN have probed the fundamental nature of matter and the forces which affect it. CERN is also the birthplace of the World Wide Web (http://info.cern.ch), invented by Tim Berners-Lee. The SFT group's efforts, like most of CERN's current activities, are directed towards the world’s highest-energy elementary particle accelerator - the Large Hadron Collider (LHC, http://public.web.cern.ch/public/en/lhc/lhc-en.html) and its experiments. There are four large experiments at the LHC, which seek to expand the frontiers of knowledge and complete our understanding of the constituents of matter and their interactions, of the conditions in the first instants after the Big Bang and of the differences between matter and anti-matter. During 2012, ATLAS and CMS announced the discovery of a new boson, which has been confirmed recently to have the properties of a Higgs boson - similar to the one required by the Standard Model of Particle Physics. The vast majority of our GSoC projects do not require any physics knowledge. Operating the LHC and running each experiment requires a large amount of software. A large part of this software is common and open source. The open source software spans the range from system software to more specialized physics-oriented tools and toolkits.

The projects to which students can contribute span several software projects: SixTrack, accelerator simulation; the Geant4/Geant-V detector simulation toolkit the ROOT software framework for storing and analyzing the data of the LHC experiments including machine learning software; CERNVM, a baseline Virtual Software Appliance for the participants of CERN LHC experiments. different computer platforms.

2016 Program

Successful Projects

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