chasingegg / Winconv

Related projects ⓘ

Alternatives and complementary repositories for Winconv

• dorthyluu / cs194-winograd
  ☆26Updated 7 years ago
• CSshengxy / MEC
  ICML2017 MEC: Memory-efficient Convolution for Deep Neural Network C++实现(非官方)
  ☆17Updated 5 years ago
• md2z34 / winograd_gpu
  GPU implementation of Winograd convolution
  ☆10Updated 7 years ago
• xuqiantong / CUDA-Winograd
  Fast CUDA Kernels for ResNet Inference.
  ☆168Updated 5 years ago
• csehydrogen / Winograd-OpenCL
  Winograd-based convolution implementation in OpenCL
  ☆28Updated 7 years ago
• xingyul / sparse-winograd-cnn
  Efficient Sparse-Winograd Convolutional Neural Networks (ICLR 2018)
  ☆190Updated 5 years ago
• tlc-pack / tophub
  tophub autotvm log collections
  ☆70Updated last year
• TaoHuUMD / Winograd_Convolution
  A Winograd based kernel for convolutions in deep learning framework
  ☆15Updated 7 years ago
• gplhegde / convolution-flavors
  Implementation of convolution layer in different flavors
  ☆67Updated 7 years ago
• pku-liang / FlexTensor
  Automatic Schedule Exploration and Optimization Framework for Tensor Computations
  ☆176Updated 2 years ago
• jafermarq / WinogradAwareNets
  Official implementation of "Searching for Winograd-aware Quantized Networks" (MLSys'20)
  ☆27Updated last year
• ceruleangu / Block-Sparse-Benchmark
  Benchmark for matrix multiplications between dense and block sparse (BSR) matrix in TVM, blocksparse (Gray et al.) and cuSparse.
  ☆24Updated 4 years ago
• lixiuhong / batched_gemm
  ☆38Updated 4 years ago
• quettabit / convolution_kernel
  Accelerating CNN's convolution operation on GPUs by using memory-efficient data access patterns.
  ☆14Updated 6 years ago
• andersy005 / tvm-in-action
  TVM stack: exploring the incredible explosion of deep-learning frameworks and how to bring them together
  ☆64Updated 6 years ago
• XiuYuLi / deepcore_source_code
  Subpart source code of of deepcore v0.7
  ☆27Updated 4 years ago
• UDC-GAC / openCNN
  A Winograd Minimal Filter Implementation in CUDA
  ☆23Updated 3 years ago
• YashasSamaga / ConvolutionBuildingBlocks
  GEMM and Winograd based convolutions using CUTLASS
  ☆25Updated 4 years ago
• limenghao / AdaTune
  This is the implementation for paper: AdaTune: Adaptive Tensor Program CompilationMade Efficient (NeurIPS 2020).
  ☆13Updated 3 years ago
• anony-sub / chameleon
  Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation
  ☆26Updated 5 years ago
• Leonardo-Ding / gpu_sgemm
  ☆17Updated 4 years ago
• istoony / winograd-convolutional-nn
  I'm going to use the Winograd’s minimal filtering algorithms to introduce a new class of fast algorithms for convolutional neural networks…
  ☆12Updated 6 years ago
• BoyuanFeng / APNN-TC
  ☆17Updated 3 years ago
• vinx13 / tvm-cuda-int8-benchmark
  Benchmark of TVM quantized model on CUDA
  ☆112Updated 4 years ago
• tlc-pack / TLCBench
  Benchmark scripts for TVM
  ☆73Updated 2 years ago
• UofT-EcoSystem / DietCode
  DietCode Code Release
  ☆62Updated 2 years ago
• masahi / tvm-cutlass-eval
  ☆35Updated 2 years ago
• atrifex / CNN-Acceleration
  Implementing CNN code in CUDA and OpenCL to evaluate its performance on NVIDIA GPUs, AMD GPUs, and an FPGA platform.
  ☆53Updated 7 years ago
• JunningWu / AIChip
  Aiming at an AI Chip based on RISC-V and NVDLA.
  ☆21Updated 6 years ago
• max2ma / shiftNet
  ☆13Updated 4 years ago