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کام کے بوجھ، میموری، درستگی، سافٹ ویئر سپورٹ، ملٹی ڈیوائس اوور ہیڈ، اور قابل تولید مفید کارکردگی کی پیمائش کے ذریعے AI ہارڈویئر کا اندازہ کریں۔

متعلقہ گائیڈ کے راستےاے آئی چپس
سوال 1 کی 8

What should a team define before comparing AI hardware?

ہر سوال کا جائزہ لیں۔8 سوالات

جب آپ کوئز دیتے ہیں تو جوابات اور وضاحتیں ظاہر ہوتی ہیں۔

  1. What should a team define before comparing AI hardware?
    • The workload, such as training, interactive inference, or on-device processing
    • Only the model parameter count
    • A vendor’s peak operation count
    • The model name
  2. Why does peak arithmetic performance alone not predict application speed?
    • Peak figures include monitor refresh rate
    • Memory movement, software, and other bottlenecks can dominate
    • All workloads are compute-bound
    • Arithmetic is unrelated to models
  3. What should be checked alongside compute capacity?
    • Only the published weight-file size
    • Only the arithmetic throughput at maximum utilization
    • Memory capacity and bandwidth, including buffers and cached state
    • Only the sum of memory across all devices
  4. What does the guide caution about memory spread across multiple devices?
    • It always becomes one seamless pool
    • It eliminates communication costs
    • It guarantees model quality
    • Aggregate memory is not automatically one simple pool
  5. What should a team evaluate when using lower-precision numerical formats?
    • Accuracy changes on the intended model and task
    • Only whether model files became smaller
    • Only whether the numerical format is advertised
    • The peak operation rate without running the model
  6. When is an advertised hardware capability actually used?
    • Whenever a chip has a high peak score
    • When hardware support, kernels, and the framework use it
    • Only when a benchmark says so
    • When listed in a brochure
  7. Which measurements does the guide recommend for reproducible hardware comparisons?
    • Only peak arithmetic
    • Only a vendor demo
    • Latency, throughput, power, and cost per useful task with stated settings
    • Processor count alone
  8. One billion parameters stored at 16 bits each takes about how much weight storage in the worked example?
    • 200 MB for the whole system
    • 20 GB including all runtime buffers
    • 2 GB including activations and cache
    • 2 GB for weights alone; other memory needs are excluded