YAO/YAO-scheduler
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update fair

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Newnius
2020-05-28 14:26:08 +08:00
parent f43f4e24ad
commit 10a46937c9
2 changed files with 70 additions and 14 deletions
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65
src/scheduler_fair.go
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@@ -107,9 +107,11 @@ func (scheduler *SchedulerFair) Start() {
if bestQueue != "" {
numberGPUtmp := 0
numberCPUtmp := 0
Memorytmp := 0
for _, task := range scheduler.queues[bestQueue][0].Tasks {
numberGPUtmp += task.NumberGPU
numberCPUtmp += task.NumberCPU
Memorytmp += task.Memory
}
log.Info("schedulingJobs are ", scheduler.schedulingJobs)
@@ -122,6 +124,7 @@ func (scheduler *SchedulerFair) Start() {
if quota, ok := scheduler.queuesQuota[bestQueue]; ok {
quota.NumberGPU -= numberGPUtmp * 100
quota.CPU -= numberCPUtmp * 100
quota.Memory -= Memorytmp
}
log.Info("After, ", scheduler.queuesQuota[bestQueue])
@@ -300,25 +303,35 @@ func (scheduler *SchedulerFair) UpdateQuota() {
/* phase 1: DRF */
usingGPU := 0
usingCPU := 0
usingMemory := 0
allocatedGPU := 0
allocatedCPU := 0
allocatedMemory := 0
scheduler.resourceAllocationsMu.Lock()
for _, quota := range scheduler.resourceAllocations {
usingGPU += quota.NumberGPU
usingCPU += quota.CPU
usingMemory += quota.Memory
}
scheduler.resourceAllocationsMu.Unlock()
for _, quota := range scheduler.queuesQuota {
allocatedGPU += quota.NumberGPU
allocatedCPU += quota.CPU
allocatedMemory += quota.Memory
}
pool := InstanceOfResourcePool()
available := pool.TotalGPU - usingGPU - allocatedGPU/100
availableGPU := pool.TotalGPU - usingGPU - allocatedGPU/100
availableCPU := pool.TotalCPU - usingCPU - allocatedCPU/100
availableMemory := pool.TotalMemory - usingMemory - allocatedMemory
/* <0 means some nodes exited */
if available <= 0 {
if availableGPU <= 0 {
return
}
log.Info("Can allocate ", available)
log.Info("Can allocate ", availableGPU)
log.Info("Before ")
for queue, quota := range scheduler.queuesQuota {
log.Info("Queue<->", queue)
@@ -326,20 +339,52 @@ func (scheduler *SchedulerFair) UpdateQuota() {
log.Info("CPU:", quota.CPU)
log.Info("Memory:", quota.Memory)
}
available *= 100
per := available / len(scheduler.queues)
for queue := range scheduler.queues {
availableGPU *= 100
availableCPU *= 100
var candidates []string
requests := map[string]ResourceCount{}
weights := 0
for queue, jobs := range scheduler.queues {
if len(jobs) > 0 {
candidates = append(candidates, queue)
}
weights += InstanceOfGroupManager().groups[queue].Weight
request := ResourceCount{}
for _, job := range jobs {
GPU := 0
CPU := 0
Memory := 0
for _, task := range job.Tasks {
GPU += task.NumberGPU
CPU += task.NumberCPU
Memory += task.Memory
}
request.NumberGPU += GPU
request.CPU += CPU
request.Memory += Memory
}
requests[queue] = request
}
per := availableGPU / weights
for _, queue := range candidates {
if _, ok := scheduler.queuesQuota[queue]; !ok {
scheduler.queuesQuota[queue] = &ResourceCount{}
}
weight := InstanceOfGroupManager().groups[queue].Weight
quota := scheduler.queuesQuota[queue]
quota.NumberGPU += per
available -= per
quota.NumberGPU += per * weight
availableGPU -= per * weight
quota.CPU += (requests[queue].CPU / requests[queue].NumberGPU) * per * weight
quota.Memory += (requests[queue].Memory / requests[queue].NumberGPU) * per * weight
}
if available > 0 {
if availableGPU > 0 {
for queue := range scheduler.queues {
quota := scheduler.queuesQuota[queue]
quota.NumberGPU += available
quota.NumberGPU += availableGPU
break
}
}