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Compiler Research
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.
Open Projects
Enable GPU support and Python Interoperability via a Plugin System
Enhancing LLM Training with Clad for efficient differentiation
Integrate Clad in PyTorch and compare the gradient execution times
Enable automatic differentiation of C++ STL concurrency primitives in Clad
... see details
Project Meetings
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
... see details
Software Releases
Clad - v2.2
2 Nov 2025
Clad - v2.1
1 Oct 2025
Clad - v2.0
27 Jul 2025
CppInterOp - v1.7.0
22 May 2025
Clad - v1.10
26 Apr 2025
... see details
News
Google Season of Docs 2023 Concluded Successfully
31 Dec 2023
Try xeus-clang-repl in docker
27 Sep 2023
Welcome to QuillPusher who has joined for Google Season of Docs
9 May 2023
... see details
Recent Content
https://youtu.be/be89sF0WLrc
C++ as a service - rapid software development and dynamic interoperability with python and beyond
https://youtu.be/jc5oj8ooG7s
Multiline input and Windows support in clang-repl
https://youtu.be/3PWeLGrF41g
Finding the Higgs on RISC-V
https://youtu.be/_5_gm58sQIg
JITLink: Native Windows JITing in LLVM
https://youtu.be/l7KXd76ymVk
jank: A Clojure dialect on LLVM with gradual typing, a native runtime, and C++ interop
https://youtu.be/gKNxTeDBczk
ez-clang: experimental C++ REPL for bare metal
https://youtu.be/stMD7VDWlVU
Cppyy
https://youtu.be/bJiwjKIWgjM
A brief history of Cxx.jl
https://youtu.be/wberEoq-m38
GPU Acceleration of Automatic Differentiation in C++ with Clad
https://youtu.be/kx3wvKk4Qss
Deep dive into the Xeus-based Cling kernel for Jupyter
https://youtu.be/HEGDII5lAfo
Cling’s CUDA Backend: Interactive GPU development with CUDA C++
https://youtu.be/7teqrCNzrD8
Calling C++ libraries from a D-written DSL: A cling/cppyy-based approach
Latest Blog
RAMTools: Extending ROOT for Genomic Data Processing
(A GSoC 2025 project extending CERN's ROOT framework with the RNTuple format to efficiently process, store, and query large-scale genomic data.)
... see more posts
We are part of 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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