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Victor-JungVictor-Jung
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Adapt the pytest suite and CI for the new test structure
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‎.github/workflows/ci-platform-chimera.yml‎

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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "kernels"
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# test-names: |
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# Kernels/Integer/Add/Regular
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# simulators: |
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# gvsoc

‎.github/workflows/ci-platform-cortexm.yml‎

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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "kernels"
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# test-names: |
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# Kernels/Integer/Add/Regular
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# Kernels/Integer/Add/MultIO
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# Kernels/Integer/Pad/Regular_1D
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# Kernels/Integer/Pad/Regular_2D
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# Kernels/Integer/MatMul/Regular
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# Kernels/Integer/MatMul/Add
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# Kernels/Integer/MaxPool
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# Kernels/Integer/Conv/Regular_2D_RQ
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# Kernels/Integer/ReduceSum
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# Kernels/Integer/ReduceMean
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# Kernels/Integer/Slice
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cortexm-models:
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needs: select-env
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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "models"
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# test-names: |
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# Models/CNN_Linear2
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# Models/WaveFormer
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‎.github/workflows/ci-platform-generic.yml‎

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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "kernels"
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# test-names: |
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# Kernels/FP32/ReLU
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# Kernels/FP32/Softmax/Regular
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# Kernels/FP32/Add/Regular
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# Kernels/FP32/Conv/DW_2D_Bias
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# Kernels/FP32/Conv/DW_2D_NoBias
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# Kernels/FP32/Conv/DW_2D_ZeroValuedBias
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# Kernels/FP32/Conv/Regular_2D_Bias
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# Kernels/FP32/Conv/Regular_2D_NoBias
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# Kernels/FP32/Conv/Regular_2D_ZeroValuedBias
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# Kernels/FP32/Div
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# Kernels/FP32/GEMM/Regular
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# Kernels/FP32/MatMul
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# Kernels/FP32/MaxPool
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# Kernels/FP32/Mul
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# Kernels/FP32/LayerNorm
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# Kernels/FP32/RMSNorm
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# Kernels/FP32/Pow/Scalar
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# Kernels/FP32/Pow/Vector
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# Kernels/FP32/ReduceMean/KeepDims/Add_ReduceMean
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# Kernels/FP32/ReduceMean/KeepDims/Add_ReduceMean_Add
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# Kernels/FP32/ReduceMean/KeepDims/AllAxes
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# Kernels/FP32/ReduceMean/KeepDims/Axes1_2_3
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# Kernels/FP32/ReduceMean/KeepDims/Axes1_3
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# Kernels/FP32/ReduceMean/KeepDims/Axes2_1
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# Kernels/FP32/ReduceMean/KeepDims/Axis0
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# Kernels/FP32/ReduceMean/KeepDims/Axis2
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# Kernels/FP32/ReduceMean/KeepDims/ReduceMean_Add
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# Kernels/FP32/ReduceMean/NoKeepDims/Add_ReduceMean
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# Kernels/FP32/ReduceMean/NoKeepDims/Add_ReduceMean_Add
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# Kernels/FP32/ReduceMean/NoKeepDims/AllAxes
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# Kernels/FP32/ReduceMean/NoKeepDims/Axes1_2_3
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# Kernels/FP32/ReduceMean/NoKeepDims/Axes1_3
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# Kernels/FP32/ReduceMean/NoKeepDims/Axes2_1
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# Kernels/FP32/ReduceMean/NoKeepDims/Axis0
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# Kernels/FP32/ReduceMean/NoKeepDims/Axis2
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# Kernels/FP32/ReduceMean/NoKeepDims/ReduceMean_Add
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# Kernels/FP32/Reshape/SkipConnection
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# Kernels/FP32/Sqrt
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# Kernels/FP32/Transpose
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# Kernels/Integer/Softmax/Regular
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# Kernels/Integer/Add/MultIO
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# Kernels/Integer/Add/Regular
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# Kernels/Integer/Conv/DW_1D
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# Kernels/Integer/Conv/Regular_1D
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# Kernels/Integer/Conv/DW_2D
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# Kernels/Integer/Conv/Regular_2D
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# Kernels/Integer/GEMM/Regular
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# Kernels/Integer/MatMul/Add
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# Kernels/Integer/MatMul/Regular
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# Kernels/Integer/MaxPool
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# Kernels/Integer/Pad/Regular_1D
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# Kernels/Integer/Pad/Regular_2D
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# Kernels/Integer/ReduceMean
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# Kernels/Integer/ReduceSum
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# Kernels/Integer/Slice
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# Models/TinyViT/5M/Layers/FP32/ReduceMean
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# Kernels/Mixed/Dequant
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# Kernels/Mixed/Quant
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# Models/Transformer_DeepQuant
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# Kernels/Integer/Conv/DW_2D_RQ
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# Kernels/Integer/Conv/Regular_2D_RQ
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# Kernels/Integer/MatMul/Regular_RQ
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generic-models:
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needs: select-env
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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "models"
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# test-names: |
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# Models/Autoencoder1D
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# Models/CCT/FP32/CCT_1_16_16_8
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# Models/CCT/FP32/CCT_2_32_32_128_Opset20
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# Models/CCT/Int/ICCT
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# Models/CCT/Int/ICCT_8
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# Models/CCT/Int/ICCT_ITA
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# Models/CCT/Int/ICCT_ITA_8
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# Models/miniMobileNet
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# Models/miniMobileNetv2
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# Models/CNN_Linear1
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# Models/TinyViT/Demo
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# Models/WaveFormer
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# Models/CNN_Linear2
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‎.github/workflows/ci-platform-mempool.yml‎

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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "kernels"
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# test-names: |
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# Kernels/Integer/Add/MultIO
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# Kernels/Integer/Add/Regular
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# Kernels/Integer/Conv/DW_1D
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# Kernels/Integer/Conv/Regular_1D
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# Kernels/Integer/Conv/DW_2D
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# Kernels/Integer/Conv/Regular_2D
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# Kernels/Integer/GEMM/Regular
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# Kernels/Integer/MatMul/Add
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# Kernels/Integer/MatMul/Regular
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# Kernels/Integer/MaxPool
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# Kernels/Integer/Pad/Regular_1D
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# Kernels/Integer/Pad/Regular_2D
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# Kernels/Integer/ReduceMean
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# Kernels/Integer/ReduceSum
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# Kernels/Integer/Slice
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# Kernels/Integer/Conv/Regular_2D_RQ
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# Kernels/Integer/Conv/DW_2D_RQ
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# Kernels/Integer/GEMM/Regular_RQPerRow
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# Kernels/Integer/MatMul/Regular_RQ
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mempool-models:
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needs: select-env
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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "models"
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# test-names: |
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# Models/CCT/Int/ICCT
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# Models/CCT/Int/ICCT_8
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# Models/CCT/Int/ICCT_ITA
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# Models/miniMobileNet
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# Models/miniMobileNetv2
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# Models/CNN_Linear1
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# Models/CNN_Linear2

‎.github/workflows/ci-platform-siracusa-neureka-tiled.yml‎

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runner: ${{ needs.select-env.outputs.runner }}
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docker-image: ${{ needs.select-env.outputs.image }}
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pytest-marker: "kernels and singlebuffer and l2 and not wmem"
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# tests-config: |
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# [
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# {"name":"Kernels/Integer/GEMM/Regular_RQPerColumn","L1":[16000]},
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# {"name":"Kernels/Integer/Conv/PW_2D","L1":[32000]},
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# {"name":"Kernels/Integer/Conv/PW_2D_RQ/Regular_RQ","L1":[32000]},
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# {"name":"Kernels/Integer/Conv/PW_2D_RQ/Unsigned_RQ","L1":[32000]}
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# ]
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# num-cores: 8
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siracusa-neureka-kernels-tiled-doublebuffer-L2:
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needs: select-env
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siracusa-neureka-models-tiled-singlebuffer-L3:
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needs: select-env
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# tests-config: |
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# [
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# {"name":"Kernels/Integer/GEMM/Regular_RQPerColumn","L1":[16000]},
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# {"name":"Kernels/Integer/Conv/PW_2D","L1":[32000]},
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# {"name":"Kernels/Integer/Conv/PW_2D_RQ/Regular_RQ","L1":[32000]},
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# {"name":"Kernels/Integer/Conv/PW_2D_RQ/Unsigned_RQ","L1":[32000]}
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# ]
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# num-cores: 8
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# # double buffer enabled:
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# double-buffer: true
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# siracusa-neureka-models-tiled-singlebuffer-L3:
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# needs: select-env
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# strategy:
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# fail-fast: false
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# matrix:
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# test-data:
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# - { name: "Models/miniMobileNet", L1: [2000] } # LMACAN: 1000 leads to non-2d transfers in L3!
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# - { name: "Kernels/Integer/Attention", L1: [2500] }
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# - { name: "Models/Transformer", L1: [15000] }
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# - { name: "Models/microLlama/microLlama1", L1: [10000] }
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# num-cores: [8]
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# default-memory-level: ["L3"]
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uses: ./.github/workflows/_runner-siracusa-neureka-tiled.yml
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runner: ${{ needs.select-env.outputs.runner }}
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siracusa-neureka-models-tiled-doublebuffer-L3:
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needs: select-env
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# strategy:
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# fail-fast: false
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# matrix:
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# test-data:
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# - { name: "Models/miniMobileNet", L1: [2000] } # LMACAN note
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# - { name: "Kernels/Integer/Attention", L1: [5000] }
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# - { name: "Models/Transformer", L1: [30000] }
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# num-cores: [8]
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# double-buffer: [true]
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# default-memory-level: ["L3"]
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uses: ./.github/workflows/_runner-siracusa-neureka-tiled.yml
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with:
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runner: ${{ needs.select-env.outputs.runner }}
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siracusa-neureka-kernels-tiled-singlebuffer-L2-wmem:
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needs: select-env
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# uses: ./.github/workflows/_runner-siracusa-neureka-tiled-sequential.yml
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# with:
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# runner: ${{ needs.select-env.outputs.runner }}
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# docker-image: ${{ needs.select-env.outputs.image }}
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# tests-config: |
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# [
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# {"name":"Kernels/Integer/GEMM/Regular_RQPerColumn","L1":[16000]},
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# {"name":"Kernels/Integer/Conv/PW_2D","L1":[32000]},
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# {"name":"Kernels/Integer/Conv/PW_2D_RQ/Regular_RQ","L1":[32000]},
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# {"name":"Kernels/Integer/Conv/PW_2D_RQ/Unsigned_RQ","L1":[32000]}
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# ]
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# num-cores: 8
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# neureka-wmem: true
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# siracusa-neureka-models-tiled-doublebuffer-L3-wmem:
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# needs: select-env
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# strategy:
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# fail-fast: false
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# matrix:
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# test-data:
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# - { name: "Models/miniMobileNet", L1: [2000] } # LMACAN note
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# - { name: "Kernels/Integer/Attention", L1: [3500] }
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# # - { name: "Models/Transformer", L1: [30000] }
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# - { name: "Models/microLlama/microLlama1", L1: [10000] }
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# num-cores: [8]
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# double-buffer: [true]
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# default-memory-level: ["L3"]
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# neureka-wmem: [true]
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uses: ./.github/workflows/_runner-siracusa-neureka-tiled.yml
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with:
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runner: ${{ needs.select-env.outputs.runner }}

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