.. blogpost::
    :title: Articles, liens, code efficaces
    :keywords: implémentation
    :date: 2021-03-24
    :categories: papers

    * `How to optimize GEMM on CPU
      <https://tvm.apache.org/docs/tutorials/optimize/opt_gemm.html#sphx-glr-tutorials-optimize-opt-gemm-py>`_
    * `HIGH PERFORMANCE CODE GENERATION IN MLIR: AN EARLY CASE STUDY WITH GEMM
      <https://arxiv.org/pdf/2003.00532v1.pdf>`_
    * `Fireiron: A Data-Movement-Aware Scheduling Language for GPUs
      <https://dl.acm.org/doi/pdf/10.1145/3410463.3414632>`_
    * `Linalg Dialect Rationale: The Case For Compiler-Friendly Custom Operations
      <https://mlir.llvm.org/docs/Rationale/RationaleLinalgDialect/>`_
    * `Robocode
      <https://robocode.sourceforge.io/>`_
    * `Introducing PyTorch Profiler - the new and improved performance tool
      <https://pytorch.org/blog/introducing-pytorch-profiler-the-new-and-improved-performance-tool/>`_