Guide-yakabatana mibvunzo · Pakati Nhanho

GPU Kuronga uye Cluster Orchestration Quiz

Dzidzira zvikumbiro zveGPU zvikumbiro, kuronga kwechikwata uye topology kuiswa, kusanganisira maitiro ekuregererwa uye kugovanisa-kugovana marongero zvinokanganisa masumbu ekudzidzisa akagovaniswa.

Nzira dzekutungamira dzinoenderanaGPU Kuronga uye Cluster Orchestration
Mubvunzo 1 ye 8

Why coordinate resource admission for a fixed-size distributed training worker group?

Tarisa mubvunzo wese8 mibvunzo

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

  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. Chii chinonzi topology-inoziva kuronga inoedza kukwirisa?
    • Kuparadzira mabasa kure kure sezvinobvira
    • Kuderedza kuwanda kwevashandisi
    • Kuisa marenji ekutaurirana pane inokurumidza kusanganisa seNVLink
    • Kusarudza mupi wemagetsi anochipa
  4. Ndeipi yekuwedzera-inowanzo shandiswa neKubernetes kune batch uye kuronga kwezvikwata zveAI mabasa?
    • Volcano
    • 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. Nderipi basa refair-share quotas muchikwata chakagovaniswa?
    • Kuvimbisa chimwe chikwata chinokunda nguva dzose
    • Kudzima iyo scheduler
    • Kudzivirira chero timu imwe chete kubva pakubata maGPU ese
    • Kuti rikurumidze basa rimwechete
  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