Progress on categories and reorder

PyTorchConference2025_GithubRepos.json

@@ -1,109 +1,126 @@
 [
     {
-        "github_repo_link": "https://github.com/pytorch/pytorch",
         "repo_name": "pytorch",
+        "github_repo_link": "https://github.com/pytorch/pytorch",
+        "category": "machine learning framework",
         "repo_description": "Tensors and Dynamic neural networks in Python with strong GPU acceleration",
         "homepage_link": "https://pytorch.org",
-        "github_topic_closest_fit": "machine-learning",
-        "category": "machine learning framework"
-    },
-    {
-        "github_repo_link": "https://github.com/vllm-project/vllm",
-        "repo_name": "vllm",
-        "repo_description": "A high-throughput and memory-efficient inference and serving engine for LLMs",
-        "homepage_link": "https://docs.vllm.ai",
-        "github_topic_closest_fit": "inference",
-        "category": "inference engine"
+        "github_topic_closest_fit": "machine-learning"
     },
     {
-        "github_repo_link": "https://github.com/ollama/ollama",
-        "repo_name": "ollama",
-        "repo_description": "Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.",
-        "homepage_link": "https://ollama.com",
-        "github_topic_closest_fit": "llms",
-        "category": "inference engine"
+        "repo_name": "triton",
+        "github_repo_link": "https://github.com/triton-lang/triton",
+        "category": "parallel computing dsl",
+        "repo_description": "Development repository for the Triton language and compiler",
+        "homepage_link": "https://triton-lang.org/",
+        "github_topic_closest_fit": "parallel-programming"
     },
     {
-        "github_repo_link": "https://github.com/sgl-project/sglang",
-        "repo_name": "sglang",
-        "repo_description": "SGLang is a fast serving framework for large language models and vision language models.",
-        "homepage_link": "https://docs.sglang.ai/",
-        "github_topic_closest_fit": "inference",
-        "category": "inference engine"
+        "repo_name": "cutlass",
+        "github_repo_link": "https://github.com/NVIDIA/cutlass",
+        "category": "parallel computing",
+        "repo_description": "CUDA Templates and Python DSLs for High-Performance Linear Algebra",
+        "homepage_link": "https://docs.nvidia.com/cutlass/index.html",
+        "github_topic_closest_fit": "parallel-programming"
     },
     {
-        "github_repo_link": "https://github.com/ggml-org/llama.cpp",
-        "repo_name": "llama.cpp",
-        "repo_description": "LLM inference in C/C++",
-        "github_topic_closest_fit": "ggml",
-        "category": "inference engine"
+        "repo_name": "tilelang",
+        "github_repo_link": "https://github.com/tile-ai/tilelang",
+        "category": "parallel computing dsl",
+        "repo_description": "Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels",
+        "homepage_link": "https://tilelang.com",
+        "github_topic_closest_fit": "parallel-programming"
     },
     {
-        "github_repo_link": "https://github.com/triton-lang/triton",
-        "repo_name": "triton",
-        "repo_description": "Development repository for the Triton language and compiler",
-        "homepage_link": "https://triton-lang.org/",
-        "category": "dsl"
+        "repo_name": "ThunderKittens",
+        "github_repo_link": "https://github.com/HazyResearch/ThunderKittens",
+        "category": "parallel computing",
+        "repo_description": "Tile primitives for speedy kernels",
+        "homepage_link": "https://hazyresearch.stanford.edu/blog/2024-10-29-tk2",
+        "github_topic_closest_fit": "parallel-programming"
     },
     {
-        "github_repo_link": "https://github.com/pytorch/helion",
         "repo_name": "helion",
+        "github_repo_link": "https://github.com/pytorch/helion",
+        "category": "parallel computing dsl",
         "repo_description": "A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.",
-        "category": "dsl"
+        "homepage_link": "https://helionlang.com",
+        "github_topic_closest_fit": "parallel-programming"
     },
     {
-        "github_repo_link": "https://github.com/microsoft/TileIR",
         "repo_name": "TileIR",
-        "category": "dsl"
-    },
-    {
-        "github_repo_link": "https://github.com/tile-ai/tilelang",
-        "repo_name": "tilelang",
-        "repo_description": "Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels",
-        "homepage_link": "https://tilelang.com/",
-        "category": "dsl"
+        "github_repo_link": "https://github.com/microsoft/TileIR",
+        "category": "parallel computing dsl",
+        "repo_description": "TileIR (tile-ir) is a concise domain-specific IR designed to streamline the development of high-performance GPU/CPU kernels (e.g., GEMM, Dequant GEMM, FlashAttention, LinearAttention). By employing a Pythonic syntax with an underlying compiler infrastructure on top of TVM, TileIR allows developers to focus on productivity without sacrificing the low-level optimizations necessary for state-of-the-art performance.",
+        "github_topic_closest_fit": "parallel-programming"
     },
     {
-        "github_repo_link": "https://github.com/NVIDIA/cutlass",
-        "repo_name": "cutlass",
-        "repo_description": "CUDA Templates and Python DSLs for High-Performance Linear Algebra",
-        "homepage_link": "https://docs.nvidia.com/cutlass/index.html",
-        "github_topic_closest_fit": "cuda"
-    },
+        "repo_name": "BitBLAS",
+        "github_repo_link": "https://github.com/microsoft/BitBLAS",
+        "repo_description": "BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment."
+    }, 
     {
-        "github_repo_link": "https://github.com/tensorflow/tensorflow",
         "repo_name": "tensorflow",
+        "github_repo_link": "https://github.com/tensorflow/tensorflow",
+        "category": "machine learning framework",
         "repo_description": "An Open Source Machine Learning Framework for Everyone",
         "homepage_link": "https://tensorflow.org",
-        "github_topic_closest_fit": "deep-learning",
-        "category": "machine learning framework"
+        "github_topic_closest_fit": "machine-learning"
     },
     {
-        "github_repo_link": "https://github.com/HazyResearch/ThunderKittens",
-        "repo_name": "ThunderKittens",
-        "repo_description": "Tile primitives for speedy kernels"
+        "repo_name": "vllm",
+        "github_repo_link": "https://github.com/vllm-project/vllm",
+        "category": "inference engine",
+        "repo_description": "A high-throughput and memory-efficient inference and serving engine for LLMs",
+        "homepage_link": "https://docs.vllm.ai",
+        "github_topic_closest_fit": "inference"
     },
     {
-        "github_repo_link": "https://github.com/pytorch/executorch",
-        "repo_name": "executorch",
-        "repo_description": "On-device AI across mobile, embedded and edge for PyTorch",
-        "homepage_link": "https://executorch.ai",
-        "github_topic_closest_fit": "mobile",
-        "category": "model compiler"
+        "repo_name": "ollama",
+        "github_repo_link": "https://github.com/ollama/ollama",
+        "category": "inference engine",
+        "repo_description": "Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.",
+        "homepage_link": "https://ollama.com",
+        "github_topic_closest_fit": "inference"
+    },
+    {
+        "repo_name": "llama.cpp",
+        "github_repo_link": "https://github.com/ggml-org/llama.cpp",
+        "category": "inference engine",
+        "repo_description": "LLM inference in C/C++",
+        "homepage_link": "https://ggml.ai",
+        "github_topic_closest_fit": "inference"
+    },
+    {
+        "repo_name": "sglang",
+        "github_repo_link": "https://github.com/sgl-project/sglang",
+        "category": "inference engine",
+        "repo_description": "SGLang is a fast serving framework for large language models and vision language models.",
+        "homepage_link": "https://docs.sglang.ai",
+        "github_topic_closest_fit": "inference"
     },
     {
-        "github_repo_link": "https://github.com/onnx/onnx",
         "repo_name": "onnx",
+        "github_repo_link": "https://github.com/onnx/onnx",
+        "category": "machine learning framework",
         "repo_description": "Open standard for machine learning interoperability",
         "homepage_link": "https://onnx.ai/",
-        "github_topic_closest_fit": "deep-learning"
+        "github_topic_closest_fit": "onnx"
+    },
+    {
+        "repo_name": "executorch",
+        "github_repo_link": "https://github.com/pytorch/executorch",
+        "category": "model compiler",
+        "repo_description": "On-device AI across mobile, embedded and edge for PyTorch",
+        "homepage_link": "https://executorch.ai",
+        "github_topic_closest_fit": "compiler"
     },
     {
         "github_repo_link": "https://github.com/ray-project/ray",
         "repo_name": "ray",
         "repo_description": "Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.",
         "homepage_link": "https://ray.io",
-        "github_topic_closest_fit": "deep-learning"
+        "github_topic_closest_fit": "machine-learning"
     },
     {
         "github_repo_link": "https://github.com/jax-ml/jax",
@@ -553,7 +570,7 @@
         "repo_name": "FTorch",
         "repo_description": "A library for directly calling PyTorch ML models from Fortran.",
         "homepage_link": "https://cambridge-iccs.github.io/FTorch/",
-        "github_topic_closest_fit": "deep-learning"
+        "github_topic_closest_fit": "machine-learning"
     },
     {
         "github_repo_link": "https://github.com/facebook/hhvm",