Idanwo ti o sopọ mọ itọsọna · Lile Ipele

Ọkọọkan Parallelism ati Oruka akiyesi adanwo

Practice Ring Attention block transfers, online softmax, and causal load balancing, including the limits of communication overlap across devices.

Jẹmọ itọsọna awọn ọnaỌkọọkan Parallelism Ati Oruka Akiyesi
Ibeere 1 ti 8

Lẹgbẹẹ iwọn wo ni afiwera ọkọọkan pin data naa?

Awotẹlẹ gbogbo ibeere8 ibeere

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

  1. Lẹgbẹẹ iwọn wo ni afiwera ọkọọkan pin data naa?
    • Iwọn ti o farasin / ẹya-ara
    • Iwọn tokini (ọkọọkan).
    • Iwọn ipele nikan
    • Awọn nọmba ti fẹlẹfẹlẹ
  2. Kini akiyesi Iwọn ṣe laarin awọn GPU ti a ṣeto sinu oruka kan?
    • Full awoṣe òṣuwọn
    • Awọn ipinlẹ Optimizer
    • Ik logits
    • Awọn bulọọki bọtini / iye
  3. How can Ring Attention combine partial attention blocks without approximating the full attention pattern?
    • Online softmax with a running maximum and normalizer
    • Randomly dropping unseen key blocks
    • Truncating every distant key
    • Replacing all attention scores with zeros
  4. Kilode ti Ifarabalẹ oruka ko nilo GPU kan ṣoṣo lati tọju K/V ni kikun?
    • O da ọpọlọpọ awọn bọtini
    • O nlo awoṣe ti o kere ju
    • K/V ti wa ni ṣiṣan ni awọn bulọọki ati pe awọn abajade apakan nikan ni a kojọpọ
    • Ifarabalẹ jẹ isunmọ, kii ṣe deede
  5. When can Ring Attention reduce the exposed time spent transferring K/V blocks?
    • Whenever the model has any number of parameters
    • Only when every device stores the full sequence
    • By eliminating all transfers between devices
    • When useful block computation overlaps those transfers
  6. Idilo wo ni o ṣe afihan iboju iparada fun iwọntunwọnsi fifuye Ifarabalẹ Iwọn?
    • O jẹ ki awoṣe kii ṣe iyatọ
    • Awọn ami atẹle wa si awọn bọtini diẹ sii, nfa iṣẹ aiṣedeede fun GPU
    • O yọ awọn nilo fun a oruka
    • O sekeji awọn paramita ka
  7. A new Ring Attention block has larger attention scores than previous blocks. Why rescale the earlier softmax sums?
    • To discard the earlier keys permanently
    • To replace all token embeddings
    • To keep accumulated terms consistent with the updated running maximum
    • Lati din awọn fokabulari iwọn
  8. Under causal masking with contiguous sequence shards, which tokens can require more attention work?
    • Later tokens that can attend to more preceding positions
    • All tokens require exactly one key
    • Only padding tokens at the start
    • Earlier tokens because they can see the future