引导式测验 · 中等 等级

GPU 与 TPU 的 AI 测验

在选择硬件之前，比较 GPU 和 TPU 架构、软件支持、系统限制以及团队所需的特定工作负载证据。

相关引导路径GPU 与 TPU 的 AI 比较
问题 1 的 8

Which frameworks does the guide list as supported for Cloud TPU workloads?

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  1. Which frameworks does the guide list as supported for Cloud TPU workloads?
    • JAX, TensorFlow, and PyTorch/XLA
    • CUDA C++ only
    • PyTorch CPU and ONNX Runtime only
    • TensorFlow Lite only
  2. TPU 是谁设计的？
    • NVIDIA
    • Google
    • 英特尔
    • Apple
  3. 哪种核心硬件结构使 TPU 在矩阵乘法方面高效？
    • 旋转的磁盘
    • 大型机械继电器组
    • 乘法累加单元的脉动数组
    • 单个超快核心
  4. Which system factors can affect a GPU-versus-TPU performance comparison?
    • Only the accelerator’s peak operation count
    • Only the number of parameters in the model
    • Only the cloud region name
    • Model support, software, interconnects, memory, utilization, and deployment cost
  5. What is a practical strength of GPUs relative to TPUs for many teams?
    • A broad ecosystem of CUDA libraries, tools, and existing GPU-supported workloads
    • A guarantee that every model is faster on a GPU
    • A requirement that all training use TensorFlow
    • A built-in advantage in every cost comparison
  6. Why does the guide recommend benchmarking the intended workload on the specific platform?
    • Peak operation counts always predict end-to-end speed exactly
    • Measured results depend on workload shape, kernels, input pipeline, memory, and system scaling
    • All workloads use the same hardware path and precision
    • A benchmark removes the need to check software support
  7. What should a team compare before choosing between a GPU and a TPU for training?
    • Peak FLOPS alone for an unrelated precision
    • The chip’s name and product launch date
    • End-to-end time and cost for its model, framework, input pipeline, and target scale
    • A benchmark from a different model and software stack
  8. How does Google describe a TPU pod?
    • A single GPU with no network
    • A CPU-only cluster
    • A model format
    • A group of TPU chips connected through a high-speed interconnect