Kuiz berkaitan panduan · Sederhana Tahap

Penjadualan GPU dan Kuiz Orkestrasi Kluster

Amalkan permintaan sumber GPU, penjadualan kumpulan dan penempatan topologi, termasuk cara dasar preemption dan perkongsian saksama mempengaruhi kelompok latihan yang dikongsi.

Laluan panduan yang berkaitanPenjadualan GPU dan Orkestrasi Kluster
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Why coordinate resource admission for a fixed-size distributed training worker group?

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Jawapan dan penjelasan muncul semasa anda mengambil kuiz.

  1. Why coordinate resource admission for a fixed-size distributed training worker group?
    • To guarantee every process starts at exactly the same nanosecond
    • To guarantee the model converges
    • To remove all worker communication
    • To reduce partial-start situations where workers wait for unavailable peers
  2. How does Kubernetes normally express a device-plugin GPU resource request?
    • As arbitrary fractions of CPU clock cycles
    • As an integer count of advertised device resources
    • As a DNS hostname only
    • As a string of model output tokens
  3. Apakah yang cuba dioptimumkan oleh penjadualan sedar topologi?
    • Menyebarkan pekerjaan sejauh mungkin
    • Meminimumkan bilangan pengguna
    • Meletakkan kedudukan berkomunikasi pada sambungan pantas seperti NVLink
    • Memilih pembekal elektrik termurah
  4. Alat tambah manakah yang biasa digunakan dengan Kubernetes untuk penjadualan kelompok dan kumpulan kerja AI?
    • Gunung berapi
    • Apache Kafka
    • Redis
    • Grafana
  5. What must a training application provide if a preempted job should resume its previous progress?
    • A guarantee that preemption saves optimizer state automatically
    • A usable checkpoint and recovery procedure
    • A renamed pod with no saved state
    • A higher learning rate for its first resumed step
  6. Apakah peranan kuota perkongsian saksama dalam kelompok kongsi?
    • Untuk menjamin satu pasukan sentiasa menang
    • Untuk melumpuhkan penjadual
    • Untuk menghalang mana-mana pasukan tunggal daripada memonopoli semua GPU
    • Untuk mempercepatkan satu kerja
  7. A fixed worker group needs eight GPU resources but only four are available. What can group admission accomplish?
    • Keep the group pending until its configured minimum requirements can be met
    • Invent the missing four GPU devices
    • Turn every worker into a CPU process without configuration
    • Guarantee completion even with no admitted workers
  8. Two communicating GPU jobs fit the same resource counts on different nodes. Why consider topology as well?
    • The resource count alone fixes every transfer latency
    • Topology determines the training labels
    • Only node names affect all-reduce outputs
    • Interconnect placement affects communication costs between their workers