Maswali yanayounganishwa na mwongozo · Ngumu Kiwango

Usambamba wa Kitaalam kwa Maswali ya Kuhudumia ya MoE

Jaribio la uwekaji wa wataalamu wa MoE, utumaji tokeni na usawa wa kupakia, ikijumuisha jinsi wataalam waliochaguliwa na mawasiliano huathiri uelekezaji uliosambazwa.

Njia za mwongozo zinazohusianaUsambamba wa Kitaalam Kwa Kutumikia Moe
Swali 1 ya 8

Usambamba wa kitaalam unasambaza nini kwenye GPU zote?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. Usambamba wa kitaalam unasambaza nini kwenye GPU zote?
    • Nakala za muundo kamili wa kupunguzwa tena
    • Vichwa vya tahadhari ya mtu binafsi pekee
    • Wataalamu tofauti wa usambazaji wa safu ya MoE
    • Tabaka za meza ya kupachika
  2. Je, ni muundo gani wa mawasiliano ambao ni msingi wa usambamba wa wataalamu wa MoE?
    • Mabadilishano mawili ya yote kwa wote (tuma na kuchanganya)
    • Tangazo moja
    • Usawazishaji wa gradient wa uhakika hadi hatua
    • Hakuna mawasiliano inahitajika
  3. Kwa nini MoE huweka hesabu ya tokeni chini licha ya vigezo vikubwa?
    • Inabana uzito hadi 1 kidogo
    • Inaruka tabaka za tahadhari
    • Wataalam wanashiriki uzito wao wote
    • Wataalamu wa juu-k waliochaguliwa pekee ndio wanaoendesha kwa tokeni
  4. Ni shida gani inatokea kwa sababu uelekezaji unategemea data?
    • Mlipuko wa gradient
    • Ukosefu wa usawa wa mzigo, ambapo wataalam wengine hupata ishara nyingi zaidi
    • Router haiwezi kufundishwa
    • Ishara hupoteza upachikaji wa nafasi zao
  5. Why are capacity limits and padding used in some MoE implementations?
    • To control expert buffer sizes and make computation shapes more predictable
    • To require every expert to process every token
    • To eliminate all token routing
    • To guarantee that every MoE system drops tokens
  6. Mifumo hufichaje muda wa kusubiri wa hatua zote hadi zote?
    • Kwa kukimbia kwenye CPU badala yake
    • Kwa kuondoa hatua ya kuchanganya
    • Kwa kuongeza kiwango cha kujifunza
    • Kwa kuingiliana mawasiliano na hesabu ya kitaalam
  7. A routed token chooses two MoE experts on different devices. What must expert-parallel execution do?
    • Run every expert in the model regardless of routing
    • Dispatch its representation to the selected experts and combine their outputs
    • Replace both expert networks with an attention head
    • Drop the token solely because it selected two devices
  8. One MoE expert receives far more tokens than others. Why can the layer’s latency increase?
    • The total expert parameter count automatically doubles
    • The router’s outputs become attention positions
    • The overloaded expert becomes a straggler while other devices wait
    • All other experts are removed from memory