Comparing Cloud Computing Resources for Model Calibration with PEST

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1 Comparing Cloud Computing Resources for Model Calibration with PEST CWEMF Annual Meeting March 10, 2015 Charles Brush Modeling Support Branch, Bay-Delta Office California Department of Water Resources, Sacramento, CA

2 Outline Problem Statement Computing Options Performance Issues & Metrics Systems Tested Test Results Cost Comparison Conclusions

3 IWFM Parameters 3

4 IWFM Parameters Saturated Zone Conductivity (K h, K v ) Storage (S y, S s ) Subsidence (S e, S i ) Unsaturated Zone Porosity Conductivity Water Management Diversion losses Irrigation efficiency Re-use factors Land Surface Field capacity Porosity Recharge factor Curve Numbers River nodes Conductance Small Watersheds Field capacity Porosity Conductivity Recession coefficients

5 PEST Optimization Iteration Calculate Jacobian matrix (run model at least once for each adjustable parameter) Calculate several sets of new parameter values Select the parameter set with the lowest objective function value

6 Saturated Zone Conductivity (K h, K v ) Storage (S y, S s ) Subsidence (S e, S i ) Unsaturated Zone Porosity Conductivity Water Management Diversion losses Irrigation efficiency Re-use factors Pilot Points

7 137 Pilot Points

8 394 Pilot Points

9 1392 Model Nodes

10 Over 30,000 Fine Grid Nodes

11 One PEST Iteration Pilot Points PEST Parameters Compter Run Time Total 137 3, PCs 3 min 1 week 394 8, PCs 3 min 3 weeks 1,393 28, PCs 3 min 16 weeks 1,393 28,892 Carver 1.5 min 2 weeks

12 One PEST Iteration Pilot Points PEST Parameters Compter Run Time Total 137 3, PCs 3 min 1 week 394 8, PCs 3 min 3 weeks 1,393 28, PCs 3 min 16 weeks 1,393 28,892 Carver 1.5 min 2 weeks 30, ,708 Carver 1.5 hr years

13 Calibration Options Calibration Strategy Pilot Points Regularization SVD Assist Super-Parameters? More Robust Computers In-House Linux Cluster Cloud Computing

14 Cloud Computing Options Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS) Desktop as Service (DaaS) Backend as a Service (BaaS) Information Technology Management as a Service (ITMaaS) 14

15 Cloud Computing Options HyperVisor Software Kernel Hardware 15

16 Cloud Computing Options Computational Resources (IaaS) HyperVisor Software Kernel Hardware 16

17 Cloud Computing Options Software Environment (PaaS) Computational Resources (IaaS) HyperVisor Software Kernel Hardware 17

18 Cloud Computing Options Cloud Applications (SaaS) Software Environment (PaaS) Computational Resources (IaaS) HyperVisor Software Kernel Hardware 18

19 Cloud Computing Options Cloud Applications (SaaS) Software Environment (PaaS) Computational Resources (IaaS) HyperVisor Software Kernel Hardware 19

20 Computing Options Multiple Office PCs Private Cluster USDOE NERSC Cluster Cloud Computer Systems Commodity Cloud System Proprietary Cloud System

21 Office PC System 21

22 In-House Cluster

23 USDOE Carver System

24 Cloud Systems

25 Amazon EC2

26 Windstream HS

27 Performance Issues Contention Two or more processes attempting to use one resource at the same time Latency Time interval between signal and response 27

28 Hardware Contention 28

29 Hardware Contention 29

30 Hardware Contention 30

31 Hardware Contention 31

32 Performance Issues Contention No CPU sharing: Guarantee only one App per core. 32

33 Data Center Servers To Network Network Interface Servers 33

34 Data Center Servers 34

35 Data Center Servers Grouped Into Network Subnets 35

36 Servers Subnet 36

37 Network Latency 37

38 Network Latency 38

39 Network Latency 39

40 Performance Issues Contention No CPU sharing, guarantee only one App per core. Latency All allocated servers must be on the same physical subnet. 40

41 Performance Metrics Wall Time CPU Time Speedup Scaling Efficiency t c = t * n s = t 1 / t n η = c 1 / c n Ignoring setup time and queuing latency 41

42 Systems Tested BeoPEST on Office PCs MPEST on USDOE super computers PPEST on Amazon EC2 PPEST on Windstream HS

43 Systems Tested System Processor Cores RAM (GB) OS Storage Network Office PC BDOHY-034 Intel Xeon CPU 2.9 GHz 8 16 Windows 7 64-bit Hard disk DWR BDOHY-024/025 BDOHY-027 Intel Xeon CPU 2.33 GHz Intel Xeon CPU 3.0 GHz 4 4 Windows 7 64-bit Hard disk DWR 4 4 Windows 7 64-bit Hard disk DWR Windstream VM Windstream VM unknown 8/VM 32 Windows 2012 Server 40GB HD Cisco Nexus Amazon AWS VM c3.8xlarge unknown 32/VM 60 Windows 2012 Server 2x320GB SSD 10 Gigabit NERSC Carver Intel Xeon 2.67 GHz 8/node 24/node Scientific Linux (Red Hat) FS 4X QDR InfiniBand, 32 GB/s

44 Test Problem C2VSim-CG calibration exercise 100 hydraulic conductivity parameters Two parameter estimation iterations Run PEST with master plus 1 to 64 clients Record Wall Time and CPU Time 44

45 Wall Time NERSC Carver Windstream Office PCs Amazon EC Wall time (hr) Number of CPUs

46 CPU Time NERSC Carver Windstream Office PCs Amazon EC Computation time (hr) Number of CPUs

47 Speedup NERSC Carver Windstream Office PCs Amazon EC Speedup Number of CPUs

48 Scaling Efficiency NERSC Carver Windstream Office PCs Amazon EC2 100% 90% 80% 70% Scaling Efficiency 60% 50% 40% 30% 20% 10% 0% Number of CPUs

49 Costs - AWS Item Description Unit Quantity Total ELASTIC COMPUTE CLOUD US East (Northern Virginia) Region EBS $0.095 per GB-Month of snapshot data stored - US East $ $0.05 US West (Northern California) Region ECC Windows $0.752 per On Demand Windows c3.2xlarge Instance Hour $ $4, EBS $0.08 per GB-month of Magnetic provisioned storage - US West $ $8.00 $0.105 per GB-Month of snapshot data stored - US West $ $10.50 $0.12 per GB-month of General Purpose SSD storage - US West $ $12.00 DATA TRANSFER US West (Northern California) Region AWS Data Transfer USW1-CloudFront-Out-Bytes $0.02 per GB data transfer out of US West to CloudFront $ $0.00 AWS Data Transfer USW1-EU-AWS-Out-Bytes $0.02 per GB - US West data transfer to EU (Ireland) $ $0.00 AWS Data Transfer USW1-USE1-AWS-Out-Bytes $0.02 per GB - US West data transfer to US East $ $0.02 AWS Data Transfer USW1-USW2-AWS-Out-Bytes $0.02 per GB - US West (CA) data transfer to US West (OR) $ $0.20 Bandwidth $0.000 per GB - data transfer in per month $ $0.00 $0.000 per GB - first 1 GB of data transferred out per month $ $0.00 $0.010 per GB - regional data transfer - in/out/between EC2 AZs $ $0.01 TOTAL $4, Appx. Cost per CPU-Hour: $

50 Costs Windstream HS Item Description Unit Quantity Total SETUP WCS Enterprise Virtual Data Center Setup Fee $ $ WCS Anti-virus/Anti-malware Setup fee $ $ WCA SAN Storage Setup fee $ $0.00 RECURRING WCS Enterprise Virtual Data Center Virtual firewall, private VLAN, secure VPN capability, $ $ secure SSL, 600GB data transfer WCS Enterprise Virtual Data Center Data transfer >600GM/mo, per GB $ $0.00 WCS Compute vcpu w/2.5gb RAM, base 32 vcpus $ $2, WCS Compute vcpu w/2.5gb RAM, additional resources per vcpu-hour $ $0.00 WCS Anti-virus/Anti-malware Base $ $ WCS Anti-virus/Anti-malware Additional VMs >32 $ $0.00 WCS SAN Storage Primary storage for VMs, including daily backups w/30- $ $ day retention SETUP $ RECURRING $2, Monthly Base Cost per CPU-Hour: $

51 Costs - AWS 32 vcpus/1 mo 64 CPUs/1 mo 96 vcpus/1mo BASE 0 vcpus base 0 vcpus base 0 vcpus base ADDITIONAL 32 vcpus 64 vcpus 96 vcpus 30 days 30 days 30 days US East Storage 0.5 $ $ $0.05 US West Instance-hrs 5,760 $4, ,520 $8, ,280 $12, Storage 100 $ $ $ $ $ $ $ $ $12.00 US West Data 0.1 $ $ $ $ $ $ $ $ $ $ $ $0.20 Bandwidth 2 $ $ $ $ $ $ $ $ $0.01 Cost/Mo $4, $8, $13, Cost per CPU-Hour: $0.19 $0.19 $

52 Costs - Windstream HS 32 vcpus/1 mo 64 CPUs/1 mo 96 vcpus/1mo BASE 32 vcpus base 32 vcpus base 32 vcpus base Additional 0 vcpus 32 vcpus 64 vcpus 0 days/mo 30 days/mo 30 days/mo CPU-Hours 23,040 CPU-hours 46,080 CPU-hours 69,120 CPU-hours VDC/data 1 $ $ $ Compute 32 $2, $2, $2, Compute 0 $ $2, $4, Anti-virus 16 $ $ $ Anti-virus 0 $ $ $ Storage 500 $ $ $ Cost/Mo $2, $5, $7, Cost per CPU-Hour: $0.12 $0.11 $

53 Scale-Up Costs $160,000 AWS EC2 Windsream CS $140,000 $120,000 Estimated Cost $100,000 $80,000 $60,000 $40,000 $20,000 $ PEST Parameter Estimation Iterations 53

54 Conclusion Cloud Computing Advantages - Nearly Infinite Scalability - No Capital Cost, Immediate Availability - Fast, Flexible Cloud Computing Challenges - Reduce Contention and Latency - Payment Mechanisms - Initial Set-Up

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