Group Members
Staff
Students
Garima Singh
Floating point error evaluation with Clad
email: garimasingh0028@gmail.com
Education: B. Tech in Information Technology, Manipal Institute of Technology, Manipal, India
Project description: Floating-point estimation errors have been a testament to the finite nature of computing. Moreover, the predominance of Floating-point numbers in real-valued computation does not help that fact. Float computations are highly dependent on precision, and in most cases, very high precision calculation is not only not possible but very inefficient. Here, one has no choice but to resort to lower precision computing, which in turn is quite prone to errors. These errors result in inaccurate and sometimes catastrophic results; hence, it is imperative to estimate these errors accurately. This project aims to use Clad, a source transformation AD tool for C++ implemented as a plugin for the C++ compiler Clang, to develop a generic error estimation framework that is not bound to a particular error approximation model. It will allow users to select their preferable estimation logic and automatically generate functions augmented with code for the specified error estimator.
Project Proposal: URL
Mentors: Vassil Vassilev, David Lange
Former students
Vaibhav Garg
Enable Modules on Windows, GSoC 2020
email: gargvaibhav64@gmail.com
Education: Computer Science, Birla Institute of Technology and Science, Pilani, India
Project description: ROOT has several features that interact with libraries and require implicit header inclusion. This can be triggered by reading or writing data on disk, or user actions at the prompt. Exposing the full shared library descriptors to the interpreter at runtime translates into an increased memory footprint. ROOT’s exploratory programming concepts allow implicit and explicit runtime shared library loading. It requires the interpreter to load the library descriptor. Re-parsing of descriptors’ content has a noticeable effect on runtime performance. C++ Modules are designed to minimize the reparsing of the same header content by providing an efficient on-disk representation of the C++ Code. C++ Modules have been implemented for Unix and OS X systems already and it is expected that with next release of ROOT, C++ modules will be default on OS X. This project aims to extend the C++ Modules support for Windows, by implementing compatible solutions to the UNIX baseline and also display corresponding performance results.
Final Report: GSoC 2020 Archive
Mentors: Vassil Vassilev, Bertrand Bellenot
Lucas Camolezi
Reduce boost dependence in CMSSW, GSoC 2020
email: camolezi@usp.br
Education: Computer Engineering, University of São Paulo, Brazil
Project description: This project has the goal to find and decrease boost dependencies in CMSSW. Modern C++ introduced a lot of new features that were only available through boost packages. Thus, some boost code can be replaced with similar C++ standard library features. Using standard features is a good practice, this project will move the CMSSW codebase in that direction.
Final Report: GSoC 2020 Archive
Mentors: Vassil Vassilev, David Lange
Roman Shakhov
Extend clad to compute Jacobians, GSoC 2020
email: r.intval@gmail.com
Education: Mathematics and Computer Science, Voronezh State University, Russia
Project description: In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to numerically evaluate the derivative of a function specified by a computer program. Automatic differentiation is an alternative technique to Symbolic differentiation and Numerical differentiation (the method of finite differences). CLAD is based on Clang which will provide the necessary facilities for code transformation. The AD library is able to differentiate non-trivial functions, to find a partial derivative for trivial cases and has good unit test coverage. Currently, clad does not provide an easy way to compute Jacobians.
Final Report: Poster
Mentors: Vassil Vassilev, Alexander Penev
