Add personal and project details for GSoC 2025

Author: Errant404

.github/actions/spelling/allow/names.txt

@@ -1,5 +1,5 @@
-Abdulrasool
 Abdelrhman
+Abdulrasool
 Abhigyan
 Abhinav
 Aditi
@@ -32,13 +32,15 @@ Ikarashi
 Ilieva
 Isemann
 JLange
+Jiayang
 Jomy
 Joshi
 Jurgaityt
 Kyiv
 LBNL
 Lattner
 Lavrijsen
+Li
 Liegeois
 Linev
 Mabille
@@ -146,6 +148,7 @@ isaacmoralessantana
 izvekov
 jacklqiu
 jeaye
+jiayang
 joshi
 junaire
 kausik
@@ -159,6 +162,7 @@ ksunhokim
 kundu
 kundubaidya
 lange
+li
 lucas
 maksym
 manasi

.github/actions/spelling/allow/terms.txt

@@ -1,9 +1,9 @@
 AARCH
 AIML
 BGZF
-Caa
 CINT
 CMSSW
+Caa
 Cppyy
 Debian
 EPC
@@ -15,12 +15,15 @@ HSF
 IIT
 JIT'd
 Jacobians
+Jurgaityt
 LLMs
 LLVM
 LULESH
 NVIDIA
 NVMe
+OpenMP
 PTX
+Resugaring
 SBO
 Slib
 Softsusy
@@ -29,23 +32,24 @@ TBR
 TFormula
 TTree
 aarch
+biodynamo
 bioinformatics
 blogs
 consteval
 cppyy
 cytokine
 cytokines
 gitlab
+gpu
 gridlay
 gsoc
-gpu
 jit
 jthread
+linkedin
 llm
 llvm
-pushforward
-linkedin
 microenvironments
+pushforward
 pythonized
 ramview
 reoptimize
@@ -67,9 +71,3 @@ xplugin
 youtu
 youtube
 zenodo
-biodynamo
-Caa
-Jurgaityt
-Resugaring
-superbuilds
-TBR

_data/contributors.yml

@@ -299,6 +299,29 @@
         and only the location of where they were called should be preserved.
       proposal: /assets/docs/petro_mozil_promosal_GSoC_2025.pdf
       mentors: Martin Vassilev, David Lange
+
+- name: Jiayang Li
+  photo: 
+  info: "Google Summer of Code 2025 Contributor"
+  email: [email protected]
+  education: "Bachelor of Computer Science, Shanghai University, China"
+  github: "https://github.com/Errant404"
+  active: 1
+  linkedin: "https://www.linkedin.com/in/errant404/"
+  projects:
+    - title: "Enable automatic differentiation of OpenMP programs with Clad"
+      status: Ongoing
+      description: |
+        This project aims to extend Clad, a Clang-based automatic differentiation
+        tool for C++, to support OpenMP programs. By enabling Clad to parse and
+        differentiate OpenMP directives such as parallel for, reduction, and atomic,
+        we will allow gradient computation in multi-threaded environments.
+        The implementation will include enhancements to Clad’s AST parsing,
+        variable scope analysis, and differentiation logic for both forward and
+        reverse modes. Deliverables include robust OpenMP AD support, comprehensive
+        tests, and user documentation.
+      proposal: /assets/docs/Jiayang_Li_Proposal_2025.pdf
+      mentors: Vassil Vassilev, Martin Vassilev
 
 - name: Salvador de la Torre Gonzalez
   photo: salva_de_la_torre_gonzalez.jpg

_pages/team/jiayang-li.md

@@ -0,0 +1,10 @@
+---
+title: "Compiler Research - Team - Jiayang Li"
+layout: gridlay
+excerpt: "Compiler Research: Team members"
+sitemap: false
+permalink: /team/JiayangLi
+email: [email protected]
+---
+
+{% include team-profile.html %}

_posts/2025-05-26-enable-automatic-differentiation-of-openmp-programs-with-clad.md

@@ -0,0 +1,47 @@
+---
+title: "Enable Automatic Differentiation of OpenMP Programs with Clad"
+layout: post
+excerpt: "This project introduces OpenMP support to Clad, enabling automatic differentiation of multi-threaded C++ programs."
+sitemap: false
+author: Jiayang Li
+permalink: blogs/gsoc25_jiayangli_intro_blog/
+banner_image: /images/blog/gsoc-banner.png
+date: 2025-05-26
+tags: gsoc llvm clad openmp automatic-differentiation
+---
+
+## About me
+
+Hi! I’m Jiayang Li, a third-year undergraduate student majoring in Computer Science at Shanghai University. I'm participating in Google Summer of Code 2025, working on enabling automatic differentiation of OpenMP programs in Clad. I have a strong background in high-performance computing and previous experience contributing to open-source projects.
+
+## Project Overview
+
+Clad is a Clang-based plugin for automatic differentiation (AD) of C++ code. It transforms mathematical functions into derivative forms, which is critical in applications like scientific computing, machine learning, and optimization.
+
+However, current Clad capabilities do not fully support multi-threaded programs using OpenMP. This project aims to bridge that gap by adding OpenMP support to Clad's differentiation capabilities. By enabling AD of OpenMP programs, developers can write performant, parallel code without sacrificing derivative information—unlocking new possibilities in physics simulations and large-scale computations.
+
+## Objectives
+
+The main goals of this project include:
+
+* **Parsing OpenMP Directives:** Enhance Clad’s AST visitors to recognize and handle directives like `#pragma omp parallel for`, `reduction`, `critical`, and `atomic`.
+* **Scope Analysis:** Properly handle `shared`, `private`, and `reduction` variables and handle their gradients appropriately.
+* **Forward and Reverse Mode Support:** Design strategies for AD under both modes. For example, reverse mode must synchronize gradients across threads—similar to [Enzyme](http://enzyme.mit.edu/)'s fork/sync model.
+
+## Implementation Strategy
+
+* **AST Extension:** Extend Clad's AST visitor to recognize and capture OpenMP constructs such as OMPParallelForDirective.
+
+* **Variable Scope Analysis:** Track and manage shared, private, and reduction variables. This ensures correctness in derivative computations across parallel threads.
+
+* **Differentiation Strategy:** Support both Forward Mode and Reverse Mode AD, inspired by how tools like Enzyme handle fork/sync transformations at the LLVM level.
+
+## Conclusion
+A a result of this project, Clad will support differentiation of OpenMP programs, significantly increasing its utility in high-performance computing domains. This work not only expands Clad’s technical capabilities but also makes AD more accessible and practical for real-world scientific applications.
+
+## Related links
+
+* [LLVM Project](https://github.com/llvm/llvm-project)
+* [Clad Repository](https://github.com/vgvassilev/clad)
+* [My GitHub](https://github.com/Errant404)
+* [Enzyme](http://enzyme.mit.edu/)