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Removed Degree of Collocation logger.

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This commit is contained in:
Pradyumna Kaushik 2018-10-05 14:11:49 -04:00
parent 39ba273d1a
commit bcc2b4e4cc
10 changed files with 6 additions and 179 deletions
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42
powerCap/extrema.go
View file

@ -12,18 +12,14 @@ import (
"syscall"
"time"
"github.com/mesos/mesos-go/api/v0/scheduler"
"github.com/montanaflynn/stats"
elekLogDef "gitlab.com/spdf/elektron/logging/def"
"gitlab.com/spdf/elektron/pcp"
"gitlab.com/spdf/elektron/rapl"
"gitlab.com/spdf/elektron/schedulers"
)
func StartPCPLogAndExtremaDynamicCap(quit chan struct{}, logging *bool, hiThreshold, loThreshold float64,
logMType chan elekLogDef.LogMessageType, logMsg chan string, pcpConfigFile string, s scheduler.Scheduler) {
logMType chan elekLogDef.LogMessageType, logMsg chan string, pcpConfigFile string) {
baseSchedRef := s.(*schedulers.BaseScheduler)
var pcpCommand string = "pmdumptext -m -l -f '' -t 1.0 -d , -c " + pcpConfigFile
cmd := exec.Command("sh", "-c", pcpCommand, pcpConfigFile)
cmd.SysProcAttr = &syscall.SysProcAttr{Setpgid: true}
@ -50,9 +46,6 @@ func StartPCPLogAndExtremaDynamicCap(quit chan struct{}, logging *bool, hiThresh
headers := strings.Split(scanner.Text(), ",")
logMType <- elekLogDef.DEG_COL
logMsg <- "CPU Variance, CPU Task Share Variance, Memory Variance, Memory Task Share Variance"
powerIndexes := make([]int, 0, 0)
powerHistories := make(map[string]*ring.Ring)
indexToHost := make(map[int]string)
@ -91,39 +84,6 @@ func StartPCPLogAndExtremaDynamicCap(quit chan struct{}, logging *bool, hiThresh
logMType <- elekLogDef.PCP
logMsg <- text
memUtils := pcp.MemUtilPerNode(text)
memTaskShares := make([]float64, len(memUtils))
cpuUtils := pcp.CpuUtilPerNode(text)
cpuTaskShares := make([]float64, len(cpuUtils))
for i := 0; i < 8; i++ {
host := fmt.Sprintf("stratos-00%d.cs.binghamton.edu", i+1)
if slaveID, ok := baseSchedRef.HostNameToSlaveID[host]; ok {
baseSchedRef.TasksRunningMutex.Lock()
tasksRunning := len(baseSchedRef.Running[slaveID])
baseSchedRef.TasksRunningMutex.Unlock()
if tasksRunning > 0 {
cpuTaskShares[i] = cpuUtils[i] / float64(tasksRunning)
memTaskShares[i] = memUtils[i] / float64(tasksRunning)
}
}
}
// Variance in resource utilization shows how the current workload has been distributed.
// However, if the number of tasks running are not equally distributed, utilization variance figures become
// less relevant as they do not express the distribution of CPU intensive tasks.
// We thus also calculate `task share variance`, which basically signifies how the workload is distributed
// across each node per share.
cpuVariance, _ := stats.Variance(cpuUtils)
cpuTaskSharesVariance, _ := stats.Variance(cpuTaskShares)
memVariance, _ := stats.Variance(memUtils)
memTaskSharesVariance, _ := stats.Variance(memTaskShares)
logMType <- elekLogDef.DEG_COL
logMsg <- fmt.Sprintf("%f, %f, %f, %f", cpuVariance, cpuTaskSharesVariance, memVariance, memTaskSharesVariance)
totalPower := 0.0
for _, powerIndex := range powerIndexes {
power, _ := strconv.ParseFloat(split[powerIndex], 64)

42
powerCap/progressiveExtrema.go
View file

@ -13,13 +13,10 @@ import (
"syscall"
"time"
"github.com/mesos/mesos-go/api/v0/scheduler"
"github.com/montanaflynn/stats"
"gitlab.com/spdf/elektron/constants"
elekLogDef "gitlab.com/spdf/elektron/logging/def"
"gitlab.com/spdf/elektron/pcp"
"gitlab.com/spdf/elektron/rapl"
"gitlab.com/spdf/elektron/schedulers"
"gitlab.com/spdf/elektron/utilities"
)
@ -34,9 +31,8 @@ func getNextCapValue(curCapValue float64, precision int) float64 {
}
func StartPCPLogAndProgressiveExtremaCap(quit chan struct{}, logging *bool, hiThreshold, loThreshold float64,
logMType chan elekLogDef.LogMessageType, logMsg chan string, pcpConfigFile string, s scheduler.Scheduler) {
logMType chan elekLogDef.LogMessageType, logMsg chan string, pcpConfigFile string) {
baseSchedRef := s.(*schedulers.BaseScheduler)
var pcpCommand string = "pmdumptext -m -l -f '' -t 1.0 -d , -c " + pcpConfigFile
cmd := exec.Command("sh", "-c", pcpCommand, pcpConfigFile)
cmd.SysProcAttr = &syscall.SysProcAttr{Setpgid: true}
@ -64,9 +60,6 @@ func StartPCPLogAndProgressiveExtremaCap(quit chan struct{}, logging *bool, hiTh
headers := strings.Split(scanner.Text(), ",")
logMType <- elekLogDef.DEG_COL
logMsg <- "CPU Variance, CPU Task Share Variance, Memory Variance, Memory Task Share Variance"
powerIndexes := make([]int, 0, 0)
powerHistories := make(map[string]*ring.Ring)
indexToHost := make(map[int]string)
@ -110,39 +103,6 @@ func StartPCPLogAndProgressiveExtremaCap(quit chan struct{}, logging *bool, hiTh
logMType <- elekLogDef.PCP
logMsg <- text
memUtils := pcp.MemUtilPerNode(text)
memTaskShares := make([]float64, len(memUtils))
cpuUtils := pcp.CpuUtilPerNode(text)
cpuTaskShares := make([]float64, len(cpuUtils))
for i := 0; i < 8; i++ {
host := fmt.Sprintf("stratos-00%d.cs.binghamton.edu", i+1)
if slaveID, ok := baseSchedRef.HostNameToSlaveID[host]; ok {
baseSchedRef.TasksRunningMutex.Lock()
tasksRunning := len(baseSchedRef.Running[slaveID])
baseSchedRef.TasksRunningMutex.Unlock()
if tasksRunning > 0 {
cpuTaskShares[i] = cpuUtils[i] / float64(tasksRunning)
memTaskShares[i] = memUtils[i] / float64(tasksRunning)
}
}
}
// Variance in resource utilization shows how the current workload has been distributed.
// However, if the number of tasks running are not equally distributed, utilization variance figures become
// less relevant as they do not express the distribution of CPU intensive tasks.
// We thus also calculate `task share variance`, which basically signifies how the workload is distributed
// across each node per share.
cpuVariance, _ := stats.Variance(cpuUtils)
cpuTaskSharesVariance, _ := stats.Variance(cpuTaskShares)
memVariance, _ := stats.Variance(memUtils)
memTaskSharesVariance, _ := stats.Variance(memTaskShares)
logMType <- elekLogDef.DEG_COL
logMsg <- fmt.Sprintf("%f, %f, %f, %f", cpuVariance, cpuTaskSharesVariance, memVariance, memTaskSharesVariance)
totalPower := 0.0
for _, powerIndex := range powerIndexes {
power, _ := strconv.ParseFloat(split[powerIndex], 64)