Updates

PyTorchConference2025_GithubRepos.json

@@ -105,7 +105,10 @@
     "repo_name": "nvcc4jupyter",
     "repo_link": "https://github.com/andreinechaev/nvcc4jupyter",
     "category": "compiler",
-    "github_about_section": "A plugin for Jupyter Notebook to run CUDA C/C++ code"
+    "github_about_section": "A plugin for Jupyter Notebook to run CUDA C/C++ code",
+    "homepage_link": "https://nvcc4jupyter.readthedocs.io",
+    "github_topic_closest_fit": "compiler"
+
   },
   {
     "repo_name": "CU2CL",
@@ -113,21 +116,23 @@
     "category": "CUDA / OpenCL",
     "github_about_section": "A prototype CUDA-to-OpenCL source-to-source translator, built on the Clang compiler framework",
     "homepage_link": "http://chrec.cs.vt.edu/cu2cl",
-    "github_topic_closest_fit": "opencl"
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "cuda-python",
     "repo_link": "https://github.com/NVIDIA/cuda-python",
     "category": "CUDA / OpenCL",
     "github_about_section": "CUDA Python: Performance meets Productivity",
-    "homepage_link": "https://nvidia.github.io/cuda-python"
+    "homepage_link": "https://nvidia.github.io/cuda-python",
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "OpenCL-SDK",
     "repo_link": "https://github.com/KhronosGroup/OpenCL-SDK",
     "category": "CUDA / OpenCL",
     "github_about_section": "OpenCL SDK",
-    "github_topic_closest_fit": "opencl"
+    "homepage_link": "https://khronos.org/opencl/",
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "pocl",
@@ -135,21 +140,23 @@
     "category": "CUDA / OpenCL",
     "github_about_section": "pocl - Portable Computing Language",
     "homepage_link": "https://portablecl.org",
-    "github_topic_closest_fit": "opencl"
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "SYCL-Docs",
     "repo_link": "https://github.com/KhronosGroup/SYCL-Docs",
     "category": "CUDA / OpenCL",
     "github_about_section": "SYCL Open Source Specification",
-    "github_topic_closest_fit": "opencl"
+    "homepage_link": "https://khronos.org/sycl",
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "triSYCL",
     "repo_link": "https://github.com/triSYCL/triSYCL",
     "category": "CUDA / OpenCL",
     "github_about_section": "Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group",
-    "github_topic_closest_fit": "opencl"
+    "homepage_link": "https://trisycl.github.io/triSYCL/Doxygen/triSYCL/html/index.html",
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "ZLUDA",
@@ -157,7 +164,7 @@
     "category": "CUDA / OpenCL",
     "github_about_section": "CUDA on non-NVIDIA GPUs",
     "homepage_link": "https://vosen.github.io/ZLUDA",
-    "github_topic_closest_fit": "cuda"
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "llama.cpp",
@@ -460,13 +467,17 @@
   {
     "repo_name": "cudnn-frontend",
     "repo_link": "https://github.com/NVIDIA/cudnn-frontend",
-    "github_about_section": "cudnn_frontend provides a c++ wrapper for the cudnn backend API and samples on how to use it"
+    "category": "parallel computing",
+    "github_about_section": "cudnn_frontend provides a c++ wrapper for the cudnn backend API and samples on how to use it",
+    "homepage_link": "https://developer.nvidia.com/cudnn",
+    "github_topic_closest_fit": "parallel-programming"
   },
   {
     "repo_name": "cuJSON",
     "repo_link": "https://github.com/AutomataLab/cuJSON",
     "category": "library leveraging parallel compute",
     "github_about_section": "cuJSON: A Highly Parallel JSON Parser for GPUs",
+    "homepage_link": "https://dl.acm.org/doi/10.1145/3760250.3762222",
     "github_topic_closest_fit": "json-parser"
   },
   {
@@ -496,6 +507,7 @@
   {
     "repo_name": "FTorch",
     "repo_link": "https://github.com/Cambridge-ICCS/FTorch",
+    "category": "wrapper",
     "github_about_section": "A library for directly calling PyTorch ML models from Fortran.",
     "homepage_link": "https://cambridge-iccs.github.io/FTorch",
     "github_topic_closest_fit": "machine-learning"
@@ -546,7 +558,9 @@
   {
     "repo_name": "lapack",
     "repo_link": "https://github.com/Reference-LAPACK/lapack",
-    "github_about_section": "LAPACK development repository",
+    "category": "linear algebra",
+    "github_about_section": "LAPACK is a library of Fortran subroutines for solving the most commonly occurring problems in numerical linear algebra.",
+    "homepage_link": "https://netlib.org/lapack",
     "github_topic_closest_fit": "linear-algebra"
   },
   {
@@ -568,7 +582,9 @@
   {
     "repo_name": "lightning-thunder",
     "repo_link": "https://github.com/Lightning-AI/lightning-thunder",
-    "github_about_section": "PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own."
+    "category": "model compiler",
+    "github_about_section": "PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.",
+    "github_topic_closest_fit": "compiler"
   },
   {
     "repo_name": "LMCache",