Changes between Version 27 and Version 28 of GpuWorkFetch


Ignore:
Timestamp:
Jan 27, 2009, 12:45:43 PM (15 years ago)
Author:
davea
Comment:

--

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  • GpuWorkFetch

    v27 v28  
    151151
    152152Work-fetch state for a particular resource types.
     153There are instances for CPU ('''cpu_work_fetch''') and NVIDIA GPUs ('''cuda_work_fetch''').
    153154Data members:
    154155
     
    208209Overall work-fetch state.
    209210
    210 === Pseudo-code ===
    211 
    212 The top-level function is:
    213 {{{
    214 WORK_FETCH::choose_project()
    215 rr_simulation()
    216 
    217 if cuda_work_fetch.nidle
    218    cpu_work_fetch.shortfall = 0
    219    p = cuda_work_fetch.select_project()
    220    if p
    221       send_req(p)
    222       return
    223 if cpu_work_fetch.nidle
    224    cuda_work_fetch.shortfall = 0
    225    p = cpu_work_fetch.select_project()
    226    if p
    227       send_req(p)
    228       return
    229 if cuda_work_fetch.shortfall
    230    p = cuda_work_fetch.select_project()
    231    if p
    232       send_req(p)
    233       return
    234 if cpu_work_fetch.shortfall
    235    p = cpu_work_fetch.select_project()
    236    if p
    237       send_req(p)
    238       return
    239 
    240 void send_req(p)
    241    req.cpu_req_seconds = cpu_work_fetch.shortfall
    242    req.cpu_req_ninstances = cpu_work_fetch.nidle
    243    req.cuda_req_seconds = cuda_work_fetch.shortfall
    244    req.cuda_req_ninstances = cuda_work_fetch.nidle
    245    req.work_req_seconds = max(req.cpu_req_seconds, req.cuda_req_seconds)
    246 
    247 }}}
    248 
    249 {{{
    250 
    251 for each resource type R
    252    for each project P
    253       if P is not backed off for R
    254          P.R.LTD += share
    255    for each running job J, project P
    256       for each resource R used by J
    257          P.R.LTD -= share*dt
    258 }}}
    259 
    260 === RR simulation ===
    261 
    262 {{{
    263 cpu_work_fetch.rr_init()
    264 cuda_work_fetch.rr_init()
    265 
    266 compute initial assignment of jobs
    267 cpu_work_fetch.set_nidle();
    268 cuda_work_fetch.set_nidle();
    269 
    270 do simulation as current
    271 on completion of an interval dt
    272    cpu_work_fetch.accumulate_shortfall(dt)
    273    cuda_work_fetch.accumulate_shortfall(dt)
    274 }}}
    275 
    276 === Work fetch ===
    277 
    278 
    279 === Handling scheduler reply ===
    280 {{{
    281 if no jobs returned
    282    double backoff for each requested PRSC
    283 else
    284    clear backoff for the PRSC of each returned job
    285 }}}
     211 '''PROJECT* choose_project()''':: choose a project from which to fetch work.
     212
     213 * Do round-robin simulation
     214 * if a GPU is idle, choose a project to ask for that type of work (using RSC_WORK_FETCH::choose_project())
     215 * if a CPU is idle, choose a project to ask for CPU work
     216 * if GPU has a shortfall, choose a project to ask for GPU work
     217 * if CPU has a shortfall, choose a project to ask for CPU work
     218 In the case where a resource type was idle, ask for only that type of work.
     219Otherwise ask for all types of work for which there is a shortfall.
    286220
    287221== Scheduler changes ==
     222
    288223{{{
    289224global vars