Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Jadwalka GPU iyo Kediska Orchestration Kooxda

Ku celceli codsiyada kheyraadka GPU, jadwalka baandooyinka iyo meelaynta topology, oo ay ku jiraan sida horudhac iyo siyaasada wadaagga cadaalad ah u saameeyaan kooxaha tababarka la wadaago.

Wadooyinka haga ee la xidhiidhaJadwalka GPU iyo Orchestration-ka Cluster-ka
Su'aal 1 ee 8

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

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  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. Muxuu jadwalka ogaanshaha topology isku dayo inuu hagaajiyo?
    • Faafinta shaqooyinka sida ugu fog ee suurtogalka ah
    • Yaraynta tirada isticmaalayaasha
    • Ku dhejinta darajooyinka wada xidhiidhka isku xidhka degdega ah sida NVLink
    • Doorashada bixiyaha korontada ugu jaban
  4. Ku-darkee ayaa inta badan loo isticmaalaa Kubernetes ee loogu talagalay jadwalka iyo qorsheynta baandooyinka ee shaqooyinka AI?
    • 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. Waa maxay doorka kootada saami-qaybsiga cadaaladda ah ee kutlada la wadaago?
    • Si loo dammaanad qaado hal koox ayaa mar walba guulaysata
    • Si aad u joojiso jadwalaha
    • Si looga hortago in koox kasta ay keli ku noqoto dhammaan GPU-yada
    • Si loo dedejiyo hal shaqo
  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