Using Dynamic Voltage Frequency Scaling and CPU Pinning for Energy Efficiency in Cloud Compu1ng. Jakub Krzywda Umeå University

Transcription

1 Using Dynamic Voltage Frequency Scaling and CPU Pinning for Energy Efficiency in Cloud Compu1ng Jakub Krzywda Umeå University

2 How to use DVFS and CPU Pinning to lower the power consump1on during periods of low traffic while fulfilling SLOs (throughput, response 1me) Influence of various configura1ons on: power consump1on (physical server) performance (VM / applica1on) 2

3 Our findings DVFS does not work for CPU intensive applica1on! CPU Pinning can be used to lower the power consump1on (at the cost of performance degrada1on) Power- performance tradeoff highly applica1on dependent! 3

4 Energy efficiency in cloud compu1ng by maximizing resource u=liza=on through workload coloca=on running at the high u1liza1on is more energy efficient (e.g., overbooking or mixing of latency sensi1ve services with batch processing tasks) by minimizing the power consump=on under a given workload fixing the energy propor1onality of a physical server (e.g., DVFS, CPU pinning, idle power states or power capping) 4

5 Energy propor1onality 5

6 Modern servers are not energy propor1onal! 6

7 DVFS impacts power consump1on power consumption [W] GHz 1.9GHz 1.7GHz 1.5GHz 1.4GHz Number of fully utilized CPU cores 7

8 DVFS impacts performance Average response time (200s only with success rate > 99%) response time [s] cores, 1.4 GHz 8 cores, 2.1 GHz 16 cores, 1.4 GHz 16 cores, 2.1 GHz # concurrent requests 8

9 DVFS and power consump1on again power consumption [W] cores, 1.4 GHz 8 cores, 2.1 GHz 16 cores, 1.4 GHz 16 cores, 2.1 GHz # concurrent requests 9

10 DVFS does not work for CPU intensive applica1on! Significant influence on performance Very small influence on power consump1on ~ 5-10 W (< 5%) 10

11 CPU Pinning Cores Cores Cores Cores (a) Setting 1 (b) Setting 2 (c) Setting 3 (d) Setting Cores Cores Cores Cores (e) Setting 5 (f) Setting 6 (g) Setting 7 (h) Setting 8 11

12 Pinning impacts power consump1on Power consumption vs. Setting Power consumption [W] s1 s2 s3 s4 s5 s6 s7 s8 Experiment setting

13 CPU pinning fixes server s energy propor1onality!? Power consumption [W] Unpinned measurements Unpinned quadratic model Pinned measurements Pinned linear model P=- 0.13c c P=4.72c Number of fully utilized CPU cores 13

14 Pinning impacts performance Response time [ms] unpinned 1 CPU 2 CPUs 4 CPUs 2 CPUs unpinned 4 CPUs 4 CPUs unpinned 8 VMs 16 VMs 30 VMs 14

15 CPU pinning and power consump1on Power consumption [W] CPUs unpinned 2 CPUs 1 CPU unpinned 2 CPUs 4 CPUs 4 CPUs unpinned 8 VMs 16 VMs 30 VMs 15

16 CPU Pinning looks promising CPU Pinning can be used to lower the power consump1on (~20 W in case of 8 cores) 16

17 Future work Perform experiments using different applica1ons (e.g. memory bounded) Construct models of power- performance tradeoffs Use these models to op1mize the placement (inter and intra physical servers) 17

18 THANK YOU! 18

19 Testbed Hardware: HP ProLiant DL165G7 server 32 CPU cores (AMD Opteron Processor 6272) DVFS levels: 1.4 GHz, 1.5 GHz, 1.7 GHz, 1.9 GHz, 2.1 GHz Power Distribu1on Unit (PDU) per- power- socket power usage measurements over Simple Network Management Protocol (SNMP) Sooware: Kernel- based Virtual Machine (KVM) hypervisor MediaWiki VM CPU intensive applica1on 19