At the heart of our mission is the commitment to foster innovation and excellence at the intersection of compiler research and data science. Our main focus areas include Interpretative C/C++/CUDA, Automatic Differentiation tools, and C++ Language Interoperability with Python. We aim to catalyze transformative advancements in scientific computing, fostering a community that thrives on shared knowledge and innovation.
Interpreting C++ in the web through Jupyter
7 Aug 2025
Differentiating RooFit likelihoods with Clad
5 Jun 2025
Accelerating simulation-based inference in RooFit at LHCb with Clad
15 May 2025
RAMTools - v0.1.0
14 Oct 2026
Clad - v2.5
28 Sep 2026
cppjit - v0.1.0a1
7 Sep 2026
Clad - v2.4
28 Jun 2026
Clad - v2.3
19 Apr 2026
Special meeting: NVIDIA at CERN organized by CR
23 Jul 2026
BLOG
More Than Just Code: Announcing the CppAlliance Fellowship
25 Mar 2026
BLOG
High School Internship Program 2026
27 Feb 2026
Google Season of Docs 2023 Concluded Successfully
31 Dec 2023
Try xeus-clang-repl in docker
27 Sep 2023
Clad as a First-Class Gradient Engine in LibTorch: GSoC 2026 Final Report
(Integrating Clad-generated derivatives with LibTorch, training an MNIST model, and investigating where compile-time differentiation saves time and where Tensor memory still remains live.)
We are partially funded by the
Princeton Department of Physics
and
Princeton Institute for Computational Science and Engineering
(PICSciE).
Contact: David Lange; Vassil Vassilev
This project is supported by the National Science Foundation under Grant OAC-1931408 (2020-2023) and OAC-2311471(2023-2026). Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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