compute.dot

 digraph{    
      node[shape=plaintext]
        compound=true;
        keras->"tensorflow python"->"tensorflow graph"->"xla hlo"->"tpu ir"->tpu
        "tensorflow eager" -> "tensorflow graph" -> tflite -> "tflite interpreter"->{cpu gpu}
        keras->"plaid ml"->{cpu gpu}
        "tensorflow graph"-> "tensorRT(nvidia)"->gpu
        "tensorflow graph"-> "ngraph(intel)"->"plaid ml"
        subgraph cluster_llvm {
            llvm "xla runtime" "Glow Runtime" "ATen" "numpy capi" xnd
        }
        subgraph cluster_hardware {
            tpu vulcan opencl cpu gpu
        }

        subgraph cluster_mlir {
            label=mlir
            "tensorflow graph" "xla hlo" "tpu ir" "spir-v"
        }
        "xla hlo" -> "xla runtime"
        "spir-v"->{vulcan "opencl"}
        pytorch->"pytorch ir"-> ATen
        pytorch->"tensor comprehensions"->ATen
        pytorch->onnx->"ngraph(intel)"
        onnx->"Glow High-Level"->"Glow Low-Level"->"Glow Runtime"
        "dask array"-> numpy->"dask array"
        numpy->"numba-ir"
        "numba-ir"->llvm
        numpy->mxnet->llvm
        mxnet->onnx->mxnet
        onnx->{"plaid ml" "tensorRT(nvidia)"}
        numpy->chainer->llvm
        numpy->"numpy capi"
        "relay python"->"relay ir"-> tvm-> llvm
        mxnet -> tvm
        pandas->{numpy llvm "Gandiva(arrow)" ibis modin "dask dataframe" weld }
        weld->cpu
        "Gandiva(arrow)"->llvm
        ibis->sql->{"Gandiva(arrow)" modin}
        modin->"data dataframe"->pandas
        ibis->pandas
        
    }