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Releasing SuperBench v0.2

· One min read
Tingting Qin
SuperBench Team

We are very happy to announce that SuperBench 0.2.0 version is officially released today!

You can install and try superbench by following Getting Started Tutorial.

SuperBench 0.2.0 Release Notes#

SuperBench Framework#

  • Implemented a CLI to provide a command line interface.
  • Implemented Runner for nodes control and management.
  • Implemented Executor.
  • Implemented Benchmark framework.

Supported Benchmarks#

  • Supported Micro-benchmarks
    • GEMM FLOPS (GFLOPS, TensorCore, cuBLAS, cuDNN)
    • Kernel Launch Time (Kernel_Launch_Event_Time, Kernel_Launch_Wall_Time)
    • Operator Performance (MatMul, Sharding_MatMul)
  • Supported Model-benchmarks
    • CNN models (Reference: torchvision models)
      • ResNet (ResNet-18, ResNet-34, ResNet-50, ResNet-101, ResNet-152)
      • DenseNet (DenseNet-161, DenseNet-169, DenseNet-201)
      • VGG (VGG-11, VGG-13, VGG-16, VGG-19, VGG11_bn, VGG13_bn, VGG16_bn, VGG19_bn)
      • MNASNet (mnasnet0_5, mnasnet0_75, mnasnet1_0, mnasnet1_3)
      • AlexNet
      • GoogLeNet
      • Inception_v3
      • mobilenet_v2
      • ResNeXt (resnext50_32x4d, resnext101_32x8d)
      • Wide ResNet (wide_resnet50_2, wide_resnet101_2)
      • ShuffleNet (shufflenet_v2_x0_5, shufflenet_v2_x1_0, shufflenet_v2_x1_5, shufflenet_v2_x2_0)
      • SqueezeNet (squeezenet1_0, squeezenet1_1)
    • LSTM model
    • BERT models (BERT-Base, BERT-Large)
    • GPT-2 model (specify which config)

Examples and Documents#

  • Added examples to run benchmarks respectively.
  • Tutorial Documents (introduction, getting-started, developer-guides, APIs, benchmarks).
  • Built SuperBench website.