FBGEMM and FBGEMM_GPU Documentation Homepage ============================================ Welcome to the documentation page for the **FBGEMM** and **FBGEMM_GPU** libraries! **FBGEMM** (Facebook GEneral Matrix Multiplication) is a low-precision, high-performance matrix-matrix multiplications and convolution library for server-side inference. This library is used as a backend of `Caffe2 `__ and `PyTorch `__ quantized operators on x86 machines. **FBGEMM_GPU** (FBGEMM GPU Kernels Library) is a collection of high-performance PyTorch GPU operator libraries for training and inference. This library is built on top of FBGEMM and provides efficient table batched embedding bag, data layout transformation, and quantization support. Table of Contents .. _home.docs.toc.general: .. toctree:: :maxdepth: 1 :caption: General Info general/Contributing.rst general/DocsInstructions.rst general/ContactUs.rst .. _fbgemm-gpu.toc.development: .. toctree:: :maxdepth: 1 :caption: FBGEMM_GPU Development fbgemm_gpu-development/BuildInstructions.rst fbgemm_gpu-development/InstallationInstructions.rst fbgemm_gpu-development/TestInstructions.rst .. _fbgemm-gpu.toc.overview: .. toctree:: :maxdepth: 1 :caption: FBGEMM_GPU Overview fbgemm_gpu-overview/jagged-tensor-ops/JaggedTensorOps.rst .. _fbgemm.toc.api.cpp: .. toctree:: :maxdepth: 1 :caption: FBGEMM C++ API fbgemm-cpp-api/QuantUtils.rst .. _fbgemm-gpu.toc.api.cpp: .. toctree:: :maxdepth: 1 :caption: FBGEMM_GPU C++ API fbgemm_gpu-cpp-api/sparse_ops.rst fbgemm_gpu-cpp-api/quantize_ops.rst fbgemm_gpu-cpp-api/merge_pooled_embeddings.rst fbgemm_gpu-cpp-api/split_table_batched_embeddings.rst fbgemm_gpu-cpp-api/jagged_tensor_ops.rst fbgemm_gpu-cpp-api/memory_utils.rst fbgemm_gpu-cpp-api/input_combine.rst fbgemm_gpu-cpp-api/layout_transform_ops.rst fbgemm_gpu-cpp-api/embedding_ops.rst .. _fbgemm-gpu.toc.api.python: .. toctree:: :maxdepth: 1 :caption: FBGEMM_GPU Python API fbgemm_gpu-python-api/table_batched_embedding_ops.rst fbgemm_gpu-python-api/jagged_tensor_ops.rst