azure_ndv5.yaml

# SuperBench Config
version: v0.12
superbench:
  enable:
  monitor:
    enable: true
    sample_duration: 1
    sample_interval: 10
  var:
    default_local_mode: &default_local_mode
      enable: true
      modes:
        - name: local
          proc_num: 8
          prefix: CUDA_VISIBLE_DEVICES={proc_rank}
          parallel: yes
    default_pytorch_mode: &default_pytorch_mode
      enable: true
      modes:
        - name: torch.distributed
          proc_num: 8
          node_num: 1
      frameworks:
        - pytorch
    common_model_config: &common_model_config
      duration: 0
      num_warmup: 128
      num_steps: 512
      sample_count: 8192
      batch_size: 128
      precision: [float32, float16]
      model_action: [train]
      pin_memory: yes
      num_workers: 0
  benchmarks:
    kernel-launch:
      <<: *default_local_mode
    gemm-flops:
      <<: *default_local_mode
      parameters:
        precision: ["fp64", "fp32", "fp16", "fp64_tc","tf32_tc", "bf16_tc", "fp16_tc", "int8_tc"]
    cublaslt-gemm:
      <<: *default_local_mode
      parameters:
          in_types: ['fp8e4m3', 'fp8e5m2', 'fp64', 'fp32', 'fp16', 'bf16', 'int8']
          shapes:
            - 4096,4096,4096
            - 8192,8192,8192
            - 16384,16384,16384
    gpu-burn:
      enable: false
      modes:
        - name: local
          proc_num: 1
          parallel: no
      parameters:
        time: 900
        doubles: true
        tensor_core: true
    nccl-bw:default:
      enable: true
      modes:
        - name: local
          proc_num: 1
          parallel: no
      parameters:
        ngpus: 8
    nccl-bw:gdr-only:
      enable: true
      modes:
        - name: local
          proc_num: 1
          parallel: no
          env:
            NCCL_IB_PCI_RELAXED_ORDERING: '1'
            NCCL_NET_GDR_LEVEL: '5'
            NCCL_P2P_DISABLE: '1'
            NCCL_SHM_DISABLE: '1'
            NCCL_MIN_NCHANNELS: '16'
            NCCL_IB_DISABLE: '0'
      parameters:
        ngpus: 8
    nccl-lat:default:
      enable: true
      modes:
        - name: mpi
          proc_num: 8
          node_num: 1
      parameters:
        maxbytes: 16M
        warmup_iters: 20
        iters: 1000
        graph_iters: 1
    ib-loopback:
      timeout: *default_timeout
      modes:
          - name: local
            proc_num: 4
            prefix: PROC_RANK={proc_rank} IB_DEVICES=0,2,4,6 NUMA_NODES=0,0,1,1
            parallel: yes
          - name: local
            proc_num: 4
            prefix: PROC_RANK={proc_rank} IB_DEVICES=1,3,5,7 NUMA_NODES=0,0,1,1
            parallel: yes
    cpu-memory-bw-latency:
      enable: false
      modes:
        - name: local
          proc_num: 1
          parallel: no
      parameters:
        tests:
          - bandwidth_matrix
          - latency_matrix
          - max_bandwidth
    mem-bw:
      enable: true
      modes:
        - name: local
          proc_num: 8
          prefix: CUDA_VISIBLE_DEVICES={proc_rank} numactl -N $(({proc_rank}/2))
          parallel: no
    disk-benchmark:
      enable: false
      modes:
        - name: local
          proc_num: 1
          parallel: no
      parameters:
        block_devices:
          - /dev/nvme0n1
          - /dev/nvme1n1
          - /dev/nvme2n1
          - /dev/nvme3n1
          - /dev/nvme4n1
          - /dev/nvme5n1
          - /dev/nvme6n1
          - /dev/nvme7n1
        seq_read_runtime: 60
        seq_write_runtime: 60
        seq_readwrite_runtime: 60
        rand_read_runtime: 60
        rand_write_runtime: 60
        rand_readwrite_runtime: 60
    gpu-copy-bw:correctness:
      enable: true
      modes:
        - name: local
          parallel: no
      parameters:
        mem_type: [htod, dtoh, dtod, one_to_all, all_to_one, all_to_all]
        copy_type: [sm, dma]
        size: 4096
        num_warm_up: 0
        num_loops: 1
        check_data: true
    gpu-copy-bw:perf:
      enable: true
      modes:
        - name: local
          parallel: no
      parameters:
        mem_type: [htod, dtoh, dtod, one_to_all, all_to_one, all_to_all]
        copy_type: [sm, dma]
    cudnn-function:
      <<: *default_local_mode
    cublas-function:
      <<: *default_local_mode
    matmul:
      <<: *default_local_mode
      frameworks:
        - pytorch
    sharding-matmul:
      <<: *default_pytorch_mode
    computation-communication-overlap:
      <<: *default_pytorch_mode
    dist-inference:
      enable: true
      timeout: 600
      modes:
          - name: mpi
            proc_num: 8
            node_num: 1
            env:
              NCCL_TOPO_FILE: '/opt/microsoft/ndv5-topo.xml'
      frameworks:
        - pytorch
      parameters:
        num_layers: 50
        num_warmup: 20
        num_steps: 100
        use_cuda_graph: true
        precision: float16
        hidden_size: 128
        input_size: 128
        batch_size: 1024
    ib-traffic:
      enable: false
      modes:
        - name: mpi
          proc_num: 8
      parameters:
        msg_size: 8388608
        ib_dev: mlx5_$LOCAL_RANK
        gpu_dev: $LOCAL_RANK
        numa_dev: $((LOCAL_RANK/2))
    gpcnet-network-test:
      enable: false
      modes:
        - name: mpi
          proc_num: 1
          mca:
            pml: ucx
            btl: ^uct
            btl_tcp_if_include: eth0
    gpcnet-network-load-test:
      enable: false
      modes:
        - name: mpi
          proc_num: 1
          mca:
            pml: ucx
            btl: ^uct
            btl_tcp_if_include: eth0
    tcp-connectivity:
      enable: false
      modes:
        - name: local
          parallel: no
      parameters:
        port: 22
    ort-inference:
      <<: *default_local_mode
    tensorrt-inference:
      <<: *default_local_mode
      parameters:
        pytorch_models:
          - resnet50
          - resnet101
          - resnet152
          - densenet169
          - densenet201
          - bert-base
          - bert-large
        seq_length: 224
        batch_size: 32
        precision: int8
    model-benchmarks:gpt:
      <<: *default_pytorch_mode
      models:
        - gpt2-small
        - gpt2-large
      parameters:
        <<: *common_model_config
        precision: [float32, float16, fp8_hybrid]
        batch_size: 32
        seq_len: 224
    model-benchmarks:bert:
      <<: *default_pytorch_mode
      models:
        - bert-base
        - bert-large
      parameters:
        <<: *common_model_config
        precision: [float32, float16, fp8_hybrid]
        seq_len: 224
    model-benchmarks:lstm:
      <<: *default_pytorch_mode
      models:
        - lstm
      parameters:
        <<: *common_model_config
        batch_size: 1024
        input_size: 224
        hidden_size: 1000
        seq_len: 32
        pin_memory: no
    model-benchmarks:resnet:
      <<: *default_pytorch_mode
      models:
        - resnet50
        - resnet101
        - resnet152
      parameters:
        <<: *common_model_config
        batch_size: 384
        num_steps: 512
    model-benchmarks:densenet:
      <<: *default_pytorch_mode
      models:
        - densenet169
        - densenet201
      parameters:
        <<: *common_model_config
        pin_memory: no
    model-benchmarks:vgg:
      <<: *default_pytorch_mode
      models:
        - vgg11
        - vgg13
        - vgg16
        - vgg19
      parameters:
        <<: *common_model_config
        pin_memory: no