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[gsoc26] Add compiler-research and affiliated projects
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‎_gsocorgs/2026/compres.md‎

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---
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title: "Compiler Research"
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author: "Aaron Jomy"
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layout: default
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organization: CompRes
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logo: CompRes-logo.png
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description: |
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The Compiler Research Group is a group of programming language enthusiasts at Princeton University and CERN. It's primary goal is 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.
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Open projects beyond the following list can be found at https://compiler-research.org/open_projects
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In addition to reaching out to the mentors, prospective candidates are required to complete the following form:
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---
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{% include gsoc_proposal.ext %}

‎_gsocprojects/2026/project_Clad.md‎

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---
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project: Clad
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layout: default
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logo: Clad-logo.png
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description: |
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[Clad](https://clad.readthedocs.io/en/latest/) enables
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automatic differentiation (AD) for C++. It is based on LLVM compiler
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infrastructure and is a plugin for Clang compiler. Clad is based on
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source code transformation. Given C++ source code of a mathematical
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function, it can automatically generate C++ code for computing derivatives
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of the function.
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summary: |
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[Clad](https://clad.readthedocs.io/en/latest/) is an automatic differentiation (AD) tool for C++
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---
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{% include gsoc_project.ext %}

‎_gsocprojects/2026/project_CppInterOp.md‎

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---
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project: CppInterOp
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layout: default
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logo: InterOp-logo.png
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description: |
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[CppInterOp](https://github.com/compiler-research/CppInterOp) is a C++ Interoperability library, which leverages ROOT's Cling and LLVM's Clang-REPL C++ interpreters, to provide a minimalist and backward-compatible API facilitating seamless language interoperability. This provides downstream interactive C++ tools with the compiler as a service by embedding Clang and LLVM as libraries in their codebases. By enabling dynamic Python interactions with static C++ codebases, CppInterOp enhances computational efficiency and rapid development in high-energy physics. The library offers primitives enabling cppyy, an automatic, run-time, Python-C++ bindings generator. The CppInterOp library provides a minimalist approach for other languages to bridge C++ entities (variables, classes, etc.). This enables interoperability with C++ code, bringing the speed and efficiency of C++ to simpler, more interactive languages like Python.
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summary: |
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The [CppInterOp](https://github.com/compiler-research/CppInterOp) library provides a minimalist approach for other languages to bridge C++ entities (variables, classes, etc.). This enables interoperability with C++ code, bringing the speed and efficiency of C++ to simpler, more interactive languages like Python.
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---
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{% include gsoc_project.ext %}

‎_gsocprojects/2026/project_Xeus-Cpp.md‎

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---
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project: Xeus-Cpp
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layout: default
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logo: Xeus-Cpp-logo.png
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description: |
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[Xeus-Cpp](https://xeus-cpp.readthedocs.io/en/latest/index.html) is a Jupyter kernel
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for C++ based on the native implementation of the Jupyter protocol [xeus](https://github.com/jupyter-xeus/xeus).
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It provides users with an interactive execution environment for C++ in Jupyter notebooks, built on LLVM's
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[Clang-Repl](https://clang.llvm.org/docs/ClangRepl.html) C++ interpreter, provided by
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the [CppInterOp](https://github.com/compiler-research/CppInterOp/) interoperability library.
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This REPL (read-eval-print-loop) nature allows rapid prototyping and iterations without the overhead
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of compiling and running separate C++ programs, allowing users to write and execute C++ code interactively.
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summary: |
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[Xeus-Cpp](https://xeus-cpp.readthedocs.io/en/latest/index.html) is a Jupyter kernel for C++ based on the native implementation of the Jupyter protocol [xeus](https://github.com/jupyter-xeus/xeus).
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---
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{% include gsoc_project.ext %}

‎_gsocproposals/2026/proposal_CppInterop-API-ExposeMemory.md‎

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---
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title: Implement CppInterOp API exposing memory ownership and thread safety
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layout: gsoc_proposal
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project: CppInterOp
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year: 2025
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difficulty: medium
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duration: 350
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mentor_avail: June-October
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organization:
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- CompRes
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project_mentors:
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- email: [email protected]
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organization: CERN/CompRes
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first_name: Aaron
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last_name: Jomy
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is_preferred_contact: yes
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- email: [email protected]
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organization: CERN/Compres
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first_name: Vipul
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last_name: Cariappa
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- email: [email protected]
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organization: CompRes
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first_name: Vassil
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last_name: Vassilev
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---
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## Description
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Incremental compilation pipelines process code chunk-by-chunk by building an ever-growing translation unit. Code is then lowered into the LLVM IR and subsequently run by the LLVM JIT. Such a pipeline allows creation of efficient interpreters. The interpreter enables interactive exploration and makes the C++ language more user friendly. The incremental compilation mode is used by the interactive C++ interpreter, Cling, initially developed to enable interactive high-energy physics analysis in a C++ environment.
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Clang and LLVM provide access to C++ from other programming languages, but currently only exposes the declared public interfaces of such C++ code even when it has parsed implementation details directly. Both the high-level and the low-level program representation has enough information to capture and expose more of such details to improve language interoperability. Examples include details of memory management, ownership transfer, thread safety, externalized side-effects, etc. For example, if memory is allocated and returned, the caller needs to take ownership; if a function is pure, it can be elided; if a call provides access to a data member, it can be reduced to an address lookup. The goal of this project is to develop API for CppInterOp which are capable of extracting and exposing such information AST or from JIT-ed code and use it in cppyy (Python-C++ language bindings) as an exemplar. If time permits, extend the work to persistify this information across translation units and use it on code compiled with Clang.
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## Project Milestones
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* Collect and categorize possible exposed interop information kinds
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* Write one or more facilities to extract necessary implementation details
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* Design a language-independent interface to expose this information
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* Integrate the work in clang-repl and Cling
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* Implement and demonstrate its use in cppyy as an exemplar
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* Present the work at the relevant meetings and conferences.
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## Requirements
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* C++ programming
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* Python programming
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* Familiarity with Clang and LLVM IR
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## Links
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* [Repo](https://github.com/compiler-research/CppInterOp)

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