Topic: gemm Goto Github
Some thing interesting about gemm
Some thing interesting about gemm
gemm,The simplest but fast implementation of matrix multiplication in CUDA.
User: andylolu2
gemm,fast 2D convolution implementation benchmark
User: blackccpie
gemm,A Flexible and Energy Efficient Accelerator For Sparse Convolution Neural Network
User: boooc
gemm,Use tensor core to calculate back-to-back HGEMM (half-precision general matrix multiplication) with MMA PTX instruction.
User: bruce-lee-ly
gemm,Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
User: bruce-lee-ly
gemm,Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.
User: bruce-lee-ly
gemm,Tuned OpenCL BLAS
User: cnugteren
gemm,🔥🔥🔥 A collection of some awesome public CUDA, cuBLAS, TensorRT and High Performance Computing (HPC) projects.
User: codingonion
gemm,Serial and parallel implementations of matrix multiplication
User: coffeebeforearch
gemm,DBCSR: Distributed Block Compressed Sparse Row matrix library
Organization: cp2k
Home Page: https://cp2k.github.io/dbcsr/
gemm,🎉CUDA/C++ 笔记 / 大模型手撕CUDA / 技术博客,更新随缘: flash_attn、sgemm、sgemv、warp reduce、block reduce、dot product、elementwise、softmax、layernorm、rmsnorm、hist etc.
User: deftruth
Home Page: https://github.com/DefTruth/cuda-learn-notes
gemm,Generate optimized MatMul cuda kernel automatically using tvm auto schedule.
User: digital-nomad-cheng
gemm,Fast SGEMM emulation on Tensor Cores
User: enp1s0
Home Page: https://arxiv.org/abs/2303.08989
gemm,FP64 equivalent GEMM via Int8 Tensor Cores using the Ozaki scheme
User: enp1s0
Home Page: https://arxiv.org/abs/2306.11975
gemm,BLISlab: A Sandbox for Optimizing GEMM
Organization: flame
gemm,
Organization: flame
gemm,CUDA optimization samples including sgemm, reduce... To be continued.
User: foreverrookie
gemm,code for benchmarking GPU performance based on cublasSgemm and cublasHgemm
User: hma02
gemm,Fast Matrix Multiplication Implementation in C programming language. This matrix multiplication algorithm is similar to what Numpy uses to compute dot products.
User: ivishalr
gemm,Low Precision Arithmetic for Convolutional Neural Network Inference
User: kaiserklayton
gemm,Some common CUDA kernel implementations (Not the fastest).
User: karhoutam
gemm,Matrix Accelerator Generator for GeMM Operations based on SIGMA Architecture in CHISEL HDL
Organization: merledu
gemm,The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers
User: mratsim
gemm,The repository targets the OpenCL gemm function performance optimization. It compares several libraries clBLAS, clBLAST, MIOpenGemm, Intel MKL(CPU) and cuBLAS(CUDA) on different matrix sizes/vendor's hardwares/OS. Out-of-the-box easy as MSVC, MinGW, Linux(CentOS) x86_64 binary provided. 在不同矩阵大小/硬件/操作系统下比较几个BLAS库的sgemm函数性能,提供binary,开盒即用。
User: mz24cn
gemm,Fast inference engine for Transformer models
Organization: opennmt
Home Page: https://opennmt.net/CTranslate2
gemm,Learning notes of "flame/how-to-optimize-gemm".
User: pkucuipy
Home Page: https://zhuanlan.zhihu.com/p/557087291
gemm,XNOR-Net with binary conv2d kernels with XNOR GEMM op, support both CPU and GPU.
User: pminhtam
gemm,hipBLASLt is a library that provides general matrix-matrix operations with a flexible API and extends functionalities beyond a traditional BLAS library
Organization: rocm
Home Page: https://rocm.docs.amd.com/projects/hipBLASLt/en/latest/index.html
gemm,Fast multi-threaded matrix multiplication in C
User: salykova
Home Page: https://salykova.github.io/matmul-cpu
gemm,My experiments with convolution
User: scocoyash
Home Page: https://scocoyash.github.io/speeding-up-convolutions/
gemm,PyTorch bindings for openai-gemm
User: szagoruyko
gemm,The fastest Tropical number matrix multiplication on GPU
Organization: tensorbfs
gemm,CUDA Kernels on V100
User: xiaosong9905
gemm,DGEMM on KNL, achieve 75% MKL
User: xiaosong9905
gemm,CUDA kernel functions
User: yester31
gemm,CUDA Gemm Convolution implementation
User: yester31
gemm,Development of deep learning inference code by OpenCL kerenl function.
User: yester31
gemm,Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.
User: yzhaiustc
gemm,Manually optimize the GEMM (GEneral Matrix Multiply) operation. There is a long way to go.
User: zixuanweeei
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