diff --git a/ali/weaver_nightly_data/Ali_PerfTestsWeaver_11_11_2024.html b/ali/weaver_nightly_data/Ali_PerfTestsWeaver_11_11_2024.html deleted file mode 100644 index 9a26fe929..000000000 --- a/ali/weaver_nightly_data/Ali_PerfTestsWeaver_11_11_2024.html +++ /dev/null @@ -1,14658 +0,0 @@ - - - - - -Ali_PerfTestsWeaver - - - - - - - - - - - - - - - - - - - - - - - -
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ALI Performance Tests on Weaver

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Introduction

Currently testing the Greenland Ice Sheet (GIS) in Albany Land Ice (ALI) using Nvidia Tesla V100 GPUs on weaver. -Note: Waterman was moved to a different network and renamed weaver. The last waterman test was executed on 6/16/2020.

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Architectures:

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NameWeaver (P9/V100)
CPUDual-socket IBM POWER9
GPUNvidia Tesla V100
Cores/Node40
Threads/Core8
GPUs/Node4
Memory/Node319 GB
InterconnectMellanox EDR IB (100 GB/s)
Compilergcc 7.2.0
GPU Compilercuda 10.1.105
MPIopenmpi 4.0.1
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Cases:

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Case NameNumber of Processes (np)Description
green-3-20km_vel_fea_1ws4Unstructured 3-20km GIS, Velocity problem, finite element assembly only, no memoization
green-3-20km_vel_fea_mem4Unstructured 3-20km GIS, Velocity problem, finite element assembly only, memoization
green-3-20km_vel_muk4Unstructured 3-20km GIS, Velocity problem, MueLu w/ Kokkos
green-3-20km_ent_fea_1ws4Unstructured 3-20km GIS, Enthalpy problem, finite element assembly only, no memoization
green-3-20km_ent_fea_mem4Unstructured 3-20km GIS, Enthalpy problem, finite element assembly only, memoization
green-3-20km_ent_muk4Unstructured 3-20km GIS, Enthalpy problem, MueLu w/ Kokkos
humboldt-1-10km_cop_fea4Unstructured 1-10km Humboldt Glacier, Coupled problem, finite element assembly only
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Timers:

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Timer NameLevelDescription
Albany Total Time0Total wall-clock time of simulation
Albany: Setup Time1Preprocess
Albany: Total Fill Time1Finite element assembly
Albany Fill: Residual2Residual assembly
Albany Residual Fill: Evaluate3Compute the residual, local/global assembly
Albany Residual Fill: Export3Update global residual across MPI ranks
Albany Fill: Jacobian2Jacobian assembly
Albany Jacobian Fill: Evaluate3Compute the Jacobian, local/global assembly
Albany Jacobian Fill: Export3Update global Jacobian across MPI ranks
NOX Total Preconditioner Construction1Construct Preconditioner
NOX Total Linear Solve1Linear Solve
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Specifications

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Performance Timelines

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Plot of wall-clock times or memory for nightly runs

Changepoints are estimated using a generalized likelihood ratio method on each timer, and then merged over all timers for a given test case.

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Plot window controls

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Pollak, Moshe; Siegmund, D. Sequential Detection of a Change in a Normal Mean when the Initial Value is Unknown. Ann. Statist. 19 (1991), no. 1, 394--416. doi:10.1214/aos/1176347990. https://projecteuclid.org/euclid.aos/1176347990

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Siegmund, D.; Venkatraman, E. S. Using the Generalized Likelihood Ratio Statistic for Sequential Detection of a Change-Point. Ann. Statist. 23 (1995), no. 1, 255--271. doi:10.1214/aos/1176324466. https://projecteuclid.org/euclid.aos/1176324466

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Hawkins, D. M., & Zamba, K. D. (2005). Statistical Process Control for Shifts in Mean or Variance using a Change Point Formulation. Technometrics, 47, 164-173.

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Hawkins DM, Qiu P, Kang CW. The changepoint model for statistical process control. Journal of Quality Technology. 2003 Oct 1;35(4):355-366.

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ALI Performance Tests on Weaver

+
+
+
+
+

Introduction

Currently testing the Greenland Ice Sheet (GIS) and Antarctica Ice Sheet (AIS) in Albany Land Ice (ALI) using Nvidia Tesla V100 GPUs on weaver. +Note: Waterman was moved to a different network and renamed weaver. The last waterman test was executed on 6/16/2020.

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Architectures:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameWeaver
CPUDual-socket IBM POWER9
GPUNvidia Tesla V100
Cores/Node40
Threads/Core8
GPUs/Node4
Memory/Node319 GB
Compilergcc/8.3.1
GPU Compilercuda/11.2.2
MPIopenmpi/4.1.1
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Cases:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Case NameNumber of Processes (np)Description
ant-8-30km_veldep4Unstructured 8-30km AIS, Velocity depth integrated model
ant-8-30km_velopt4Unstructured 8-30km AIS, Velocity optimization
ant-8-30km_vel_cheby_fixt4Unstructured 8-30km AIS, Velocity problem, Chebyshev smoothers, Fixed Newton step
green-3-20km_vel_gpu4Unstructured 3-20km GIS, Velocity problem, GPU preconditioner
humboldt-1-10km_vel_gpu4Unstructured 1-10km Humboldt Glacier, Velocity problem, GPU preconditioner
humboldt-1-10km_ent_gpu4Unstructured 1-10km Humboldt Glacier, Enthalpy problem, GPU preconditioner
humboldt-1-10km_cop_fea4Unstructured 1-10km Humboldt Glacier, Coupled problem, Finite element assembly only
mali-ais8km_gpu4MALI, Unstructured 8-30km AIS, GPU preconditioner
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Timers:

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Timer NameLevelDescription
MALI Total Time0Total wall-clock time of MALI simulation
MALI Extrude Time1Setup Albany problem
Albany Total Time0Total wall-clock time of Albany simulation
Albany Setup Time1Setup Albany problem
Residual Fill1Residual assembly
Jacobian Fill1Jacobian assembly
DistParam Fill1Distributed parameter assembly
RespParamHesVec Fill1Response parameter Hessian-vector product assembly
RespDistParamHesVec Fill1Response distributed parameter Hessian-vector product assembly
ResDistParamHesVec Fill1Residual distributed parameter Hessian-vector product assembly
NOX Total Preconditioner Construction1Construct Preconditioner
NOX Total Linear Solve1Linear Solve
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Specifications

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+
+ +
+ +
+ + + + +
+ +
+
+
+

Performance Timelines

+
+
+ +
+ + + + +
+ +
+ +
+ + + + +
+ +
+
+
+

Plot of wall-clock times or memory for nightly runs

Changepoints are estimated using a generalized likelihood ratio method on each timer, and then merged over all timers for a given test case.

+ +

Plot window controls

+ +
+
+
+
+

Pollak, Moshe; Siegmund, D. Sequential Detection of a Change in a Normal Mean when the Initial Value is Unknown. Ann. Statist. 19 (1991), no. 1, 394--416. doi:10.1214/aos/1176347990. https://projecteuclid.org/euclid.aos/1176347990

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Siegmund, D.; Venkatraman, E. S. Using the Generalized Likelihood Ratio Statistic for Sequential Detection of a Change-Point. Ann. Statist. 23 (1995), no. 1, 255--271. doi:10.1214/aos/1176324466. https://projecteuclid.org/euclid.aos/1176324466

+

Hawkins, D. M., & Zamba, K. D. (2005). Statistical Process Control for Shifts in Mean or Variance using a Change Point Formulation. Technometrics, 47, 164-173.

+

Hawkins DM, Qiu P, Kang CW. The changepoint model for statistical process control. Journal of Quality Technology. 2003 Oct 1;35(4):355-366.

+ +
+
+ + + + + + + + + diff --git a/ali/weaver_nightly_data/html_entry b/ali/weaver_nightly_data/html_entry index b5fb81d44..9cb7a62e6 100644 --- a/ali/weaver_nightly_data/html_entry +++ b/ali/weaver_nightly_data/html_entry @@ -1 +1 @@ -

  • 11_11_2024.

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  • 12_06_2024.