Abdelrhman Elrawy
• Nov 04, 2025 • 5 min read
A comprehensive wrap-up of my Google Summer of Code 2025 project on enabling automatic differentiation of GPU-accelerated code through Thrust API support in Clad.
Salvador de la Torre Gonzalez
• Oct 31, 2025 • 6 min read
CARTopiaX is an agent-based model developed using BioDynaMo to simulate CAR-T cell dynamics and interactions within the solid tumor microenvironment. It provides researchers with a tool to efficiently evaluate therapy efficacy and identify strategies to improve treatment outcomes.
Vassil Vassilev
• Oct 08, 2025 • 2 min read
Congratulations to Rohan Timmaraju and the NEO-FLOOD team for their success in NASA's Beyond the Algorithm Challenge. This win highlights the strength of cross‑disciplinary thinking, where foundational research technologies enable solutions to high‑stakes problems.
nasa neo-flood rohan-timmaraju compiler-research neuromorphic-computing satellite-ai earth-observation flood-prediction research-award space-technology
Galin Bistrev
• Sep 25, 2025 • 4 min read
A CERN Summer Student 2025 project aiming at the support of automatic differentiation (AD) for likelihood scans in the CMS Combine tool to accelerate statistical inference by leveraging RooFit's AD support and LLVM-based gradient generation.
Petro Zarytskyi
• Jul 31, 2025 • 1 min read
A GSoC 2025 contributor project aiming to enhance Clad's ability to differentiate through OOP and STL constructs by supporting functions with side-effects.
Maksym Andriichuk
• Jul 14, 2025 • 1 min read
A GSoC 2025 contributor project aiming to implement Activity Analysis for (CUDA) GPU kernels
Galin Bistrev
• Jul 05, 2025 • 2 min read
A CERN Summer Student 2025 project aiming at the integration of automatic differentiation (AD) into the CMS Combine tool to accelerate statistical inference by leveraging RooFit's AD support and LLVM-based gradient generation.
Jiayang Li
• May 26, 2025 • 1 min read
This project introduces OpenMP support to Clad, enabling automatic differentiation of multi-threaded C++ programs.
Abhinav Kumar
• May 22, 2025 • 3 min read
A GSoC 2025 project aiming at integration of debugger into the xeus-cpp kernel for Jupyter using LLDB and its Debug Adapter Protocol (lldb-dap).
Aditi Milind Joshi
• May 22, 2025 • 4 min read
A GSoC 2025 project focussing on optimizing Clad's tape data structure for reverse-mode automatic differentiation, introducing slab-based memory, thread safety, multilayer storage, and future support for CPU-GPU transfers.
Rohan Timmaraju
• May 21, 2025 • 3 min read
This GSoC project leverages Clad to optimize LLM training in C++, aiming to boost efficiency by developing a custom tensor library and integrating Clad for compiler-level gradient calculations.
Abdelrhman Elrawy
• May 18, 2025 • 1 min read
This summer, I am working on adding support for Thrust API in Clad, enabling automatic differentiation of GPU-accelerated code. This work bridges the gap between high-performance CUDA parallelism and source-to-source AD transformation.
Petro Mozil
• May 18, 2025 • 2 min read
Support for STL concurrency features in CLAD is a useful feature for applications utilizing cpu threads. Many applications of autodifferentiation benefit from parallel or concurrent processing, and support for some STL concurrency primitives such as threads and basic synchronization primitives may considerably simplify the user's design.
Sahil Patidar
• May 18, 2025 • 3 min read
Advanced symbol resolution and re-optimization for Clang-Repl is a Google Summer of Code 2025 project. It aims to improve Clang-Repl and ORC JIT by adding support for automatically loading dynamic libraries when symbols are missing. This removes the need for users to load libraries manually and makes things work more...
Salvador de la Torre Gonzalez
• May 14, 2025 • 2 min read
This GSoC 2025 project, Agent-Based Simulation of CAR-T Cell Therapy, aims to develop a BioDynaMo-based model to simulate CAR-T cell dynamics and interactions. The goal is to provide researchers with a tool to evaluate therapy efficacy and identify strategies to enhance treatment outcomes.
Aditya Pandey
• May 13, 2025 • 3 min read
A GSoC 2025 project aiming to advance genomic data management by implementing ROOT's next-generation RNTuple format for sequence alignment storage.
Learn about jank, the native Clojure dialect on LLVM, and how it uses Clang and CppInterOp to stand out from the pack. Discover how Clojure users develop and how jank brings that to the native world.
Pavlo Svirin
• Nov 05, 2024 • 3 min read
A GSoC 2024 project aimed to introduce superbuilds into ROOT
Christina Koutsou
• Nov 05, 2024 • 33 min read
A not-very-short description of the challenges faced and my overall experience
Chaitanya Shahare
• Nov 04, 2024 • 3 min read
The LLVM.org website redesign project, part of GSoC 2024, aimed to modernize and enhance usability of llvm.org website for its community of developers. This initiative will streamline navigation, improve accessibility, and update content, transforming LLVM.org into a more user-friendly resource.
Atell Yehor Krasnopolski
• Oct 30, 2024 • 3 min read
A GSoC 2024 project aimed at implementing the differentiation of the Kokkos framework into Clad
Tharun Anandh
• Oct 17, 2024 • 5 min read
Integrate a Large Language Model with the xeus-cpp Jupyter kernel, part of Google Summer of Code 2024, aims to integrate a large langauge model into the xeus kernel for users to interactively generate and execute code.
Isaac Morales Santana
• Oct 17, 2024 • 4 min read
This project, part of Google Summer of Code 2024, aims to reduce the header parsing in BioDynaMo using the ROOT C++ Modules
Sahil Patidar
• Oct 14, 2024 • 5 min read
Out of Process Execution for Clang-Repl project, part of Google Summer of Code 2024, aims to enhance Clang-Repl by implementing out-of-process execution. This will address issues of high resource consumption and instability, making Clang-Repl more suitable for low-power devices and more stable for developers
Sahil Patidar
• Jul 18, 2024 • 3 min read
Out of Process Execution for Clang-Repl project, part of Google Summer of Code 2024, aims to enhance Clang-Repl by implementing out-of-process execution. This will address issues of high resource consumption and instability, making Clang-Repl more suitable for low-power devices and more stable for developers
Maksym Andriichuk
• Jun 25, 2024 • 2 min read
IRIS-HEP project aimed to optimize automatic differentiation using activity analysis
Max Aehle
• Jun 07, 2024 • 2 min read
Report on our work to apply algorithmic differentiation to the simulation codes G4HepEm/HepEmShow
Mihail Mihov
• Jun 05, 2024 • 2 min read
A GSoC 2024 project with the goal of adding support for constant expressions to Clad
Pavlo Svirin
• May 31, 2024 • 2 min read
A GSoC 2024 project with goal to split ROOT into separate components and thus speed up its compilation
Tharun Anandh
• May 30, 2024 • 2 min read
Integrate a Large Language Model with the xeus-cpp Jupyter kernel, part of Google Summer of Code 2024, aims to integrate a large langauge model into the xeus kernel for users to interactively generate and execute code.
Riya Bisht
• May 30, 2024 • 6 min read
Enable CUDA Compilation on Cppyy-Numba generated IR project, part of Google Summer of Code 2024, aims to demonstrate Cppyy's capability to provide CUDA paradigms to Python users without any compromise in performance.
Atell Yehor Krasnopolski
• May 26, 2024 • 2 min read
A GSoC 2024 project aimed at implementing the differentiation of the Kokkos framework into Clad
Christina Koutsou
• May 18, 2024 • 7 min read
Nowadays, the rise of General Purpose GPU programming has caused more and more tools used by the scientific community to adjust to GPU's architecture. This project aims to allow `Clad` to ride that tide and broaden its use-range by enabling reverse-mode automatic differentiation of CUDA kernels.
Chaitanya Shahare
• May 11, 2024 • 3 min read
The LLVM.org website redesign project, part of Google Summer of Code 2024, aims to modernize and enhance usability for its community of developers. This initiative will streamline navigation, improve accessibility, and update content, transforming LLVM.org into a more user-friendly resource.
Yuquan (Fred) Fu
• Sep 18, 2023 • 4 min read
Clang-Repl, featuring a REPL(Read-Eval-Print-Loop) environment, allows developers to program in C++ interactively. It is a C++ interpreter built upon the Clang and LLVM incremental compilation pipeline. One of the missing upstream features in Clang-Repl is the ability to propose options for automatically completing user input or code completion. Sometimes, C++...
QuillPusher
• May 10, 2023 • 2 min read
A review of the documentation efforts in 2023, powered by Google's Season of Docs initiative. An audit of the existing documentation was done to identify gaps and potential areas of improvement. Our main areas of focus were: Automatic Differentiation applications (using Clad, e.g. in RooFit and Floating-Point Error Estimation), and...
Anubhab Ghosh
• Dec 07, 2022 • 5 min read
LLVM JIT APIs include JITLink, a just-in-time linker that links together objects code units directly in memory and executes them. It uses the JITLinkMemoryManager interface to allocate and manage memory for the generated code. When the generated code is run in the same process as the linker, memory is directly...
Jun Zhang
,
Purva Chaudhari
• Dec 02, 2022 • 5 min read
Incremental C++ enables exploratory programming by considering the translation unit to be an ever-growing entity. This allows implementation of interpreter-like tools such as Cling and Clang-Repl, which consume C++ code piece by piece and use the JIT infrastructure to run each piecewise. One of the challenges of Incremental C++ is...
Matheus Izvekov
• Nov 30, 2022 • 3 min read
Clang is an LLVM native C/C++/Objective-C compiler, which aims to deliver amazingly fast compiles, extremely useful error and warning messages and to provide a platform for building great source level tools. The Clang Static Analyzer and clang-tidy are tools that automatically find bugs in your code, and are great examples...
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.
© 2019 Princeton University. Site made with Jekyll; Credit to Allan lab for this site template.
