CERN SFT

Mentors: Student: Oleg.jakushkin

<p>Our objective is to determine the best architectural and parallelization options for the BLonD future C++ code base. Project includes:</p> <ul> <li>Existing simulations performance profile data and component interaction diagrams.</li> <li>Micro benchmark data selection for regional stress testing that can reveal of currently existing architectural pitfalls.</li> <li>Prototypes for potential architecture evolution that are exclusively designed for BLonD performance optimization covering wide amount of task and data parallelization technics: from local SMID optimizations and coprocessor kernels to cluster technics.</li> </ul> <p>Main project deliverable will be a report covering possible architecture directions rooted in profile data, performance tests and future possibilities. This report will include UML diagrams showing architectural blueprints for concurrency and parallelism directions, structured performance analysis of performed tests and created prototypes, a table comparing selected technologies in terms of:</p> <ul> <li>Top available simulation scale.</li> <li>Integration into current architectural model.</li> <li>Prototype testing results.</li> <li>Profiling tools.</li> <li>Publically available information and documentation.</li> <li>Hardware requirements.</li> </ul>

Mentors: Student: Peter Whidden

<p>The ROOT project is developing a JavaScript library for reading and rendering ROOT objects in modern web browsers. The rendering of 3D objects is done with the library THREE.js, and though much of the conversion has already been implemented, there are still many desirable features left to be added. These include interactively selecting particular model components, adjusting a cutting plane to view various cross sections, animation, camera tracks, and possibly an exploded view to more closely examine complex regions. In addition to creating these new features, the project will improve the rendering performance. The current implementation can handle several hundred volumes, but this figure will be increased as much as possible, and finally a method for pruning down geometries to manageable sizes will be devised.</p>

Mentors: Student: Dmitry Sorokin

<p>Implementation of Adams multistep methods in Geant4</p>

Mentors: Student: gdphys

<p>The proposed project involves the support for Spark parallelization in TMVA. Machine learning procedures like k-fold cross validation, hyper parameter tuning as well as many others can be parallelized to decrease computational time. The goal of the proposed project is to implement the existing C++ code in to PySpark.</p>

Mentors: Student: Joel Fuentes

<p>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 threads and distributor thread. In this model a concurrent queue data structure is used as a common source for threads. The main objective of this project is to adapt the steering of this work to a task-based approach using Thread Building Blocks (TBB).</p>