diff --git a/dashboards/dashboard_fe2ti.py b/dashboards/dashboard_fe2ti.py
index a53f9edd894565ab74b467ef4fdc5d3b379ffca0..577ca307be2aca21cb2c23a273bbbd0a0baf9168 100644
--- a/dashboards/dashboard_fe2ti.py
+++ b/dashboards/dashboard_fe2ti.py
@@ -13,6 +13,7 @@ from dashboards.influx_queries import (Query,
join_variable_and,
show_tag_values)
from dashboards.legends import Units
+from collections import namedtuple
description_markdown = r"""
@@ -31,76 +32,84 @@ description_markdown = r"""
- Information about the different Hosts on the NHR@FAU [Testcluster](https://hpc.fau.de/systems-services/documentation-instructions/clusters/test-cluster/)
"""
+Filter = namedtuple("Filter", ("name", "multi", "default_value"), defaults=('', True, ''))
+PanelInfos = namedtuple("PanelInfos", ("name", "unit"))
+
+
+def get_dashboard_variable(filter: Filter, measurment_name: str, data_source: str):
+ query = show_tag_values(measurment_name, filter.name)
+ kwargs = {}
+ if filter.multi:
+ kwargs.update({'includeAll': True, 'multi': True, })
+ if filter.default_value:
+ kwargs.update({'default': filter.default_value})
+ return get_dashboard_variable_query(filter.name, query, data_source, **kwargs)
+
+
+def get_time_series_panel(field: PanelInfos,
+ data_source: str,
+ measurment_name: str,
+ *,
+ where=None,
+ group_by=None,
+ overrides=None):
+ query = Query(select_=field.name,
+ from_=measurment_name,
+ where_=where,
+ group_by=group_by)
+
+ return TimeSeries(
+ title=field.name,
+ dataSource=data_source,
+ targets=[get_influx_target(str(query))],
+ unit=field.unit,
+ pointSize=9,
+ overrides=overrides,
+ )
def dashboard_fe2ti():
data_source = "fe2ti"
measurment_name = "fe2ti"
row_repeat = "micro_problem_size"
- other_filters = ["branch",
- "benchmark_name",
- "compiler",
- "solver",
- "mpi_ranks",
- "omp_threads",
- "ksp_tol"]
- row_repeat_var = get_dashboard_variable_query(
- row_repeat, show_tag_values(measurment_name, row_repeat), data_source, default='8')
-
- host_var = get_dashboard_variable_query(
- 'host', show_tag_values(measurment_name, 'host'),
- data_source, includeAll=False, multi=False, default='skylakesp2')
-
- other_vars = [get_dashboard_variable_query(
- filter, show_tag_values(measurment_name, filter), data_source)
- for filter in other_filters
+ other_filters = [
+ Filter("micro_problem_size", True, '8'),
+ Filter("host", False, 'skylakesp2'),
+ Filter("branch"),
+ Filter("benchmark_name"),
+ Filter("compiler"),
+ Filter("solver"),
+ Filter("mpi_ranks"),
+ Filter("omp_threads"),
+ Filter("ksp_tol")
]
- other_filters.append('host')
- other_vars = [host_var, *other_vars]
-
- where = join_variable_and([row_repeat, *other_filters])
- fields = ["Time to solution",
- "DP [MFLOP/s] STAT Sum",
- "Operational intensity STAT Sum",
- 'AVX DP [MFLOP/s] STAT Sum" / "DP [MFLOP/s] STAT Sum',
- 'Memory bandwidth [MBytes/s] STAT Sum',
- 'Memory write bandwidth [MBytes/s] STAT Sum',
- 'Memory read bandwidth [MBytes/s] STAT Sum',
- 'Memory data volume [GBytes] STAT Sum',
- 'Memory read data volume [GBytes] STAT Sum',
- 'Memory write data volume [GBytes] STAT Sum',
- 'Energy [J] STAT Sum',
- 'Power [W] STAT Sum',
- 'Clock [MHz] STAT Avg',]
- units = [Units.seconds,
- Units.mflop_sec,
- Units.flop_per_byte,
- Units.percent,
- Units.mbytes_per_second,
- Units.mbytes_per_second,
- Units.mbytes_per_second,
- Units.gigabyte,
- Units.gigabyte,
- Units.gigabyte,
- Units.joule,
- Units.watt,
- Units.megahertz,
- ]
- queries = [Query(select_=field,
- from_=measurment_name,
- where_=where,
- group_by=[row_repeat, *other_filters]
- )
- for field in fields
- ]
+
+ other_vars = [get_dashboard_variable(filter, measurment_name, data_source) for filter in other_filters]
+ row_repeat_var = other_vars[0]
+
+ where = join_variable_and([f.name for f in other_filters])
+ fields = [PanelInfos("Time to solution", Units.seconds),
+ PanelInfos("DP [MFLOP/s] STAT Sum", Units.mflop_sec),
+ PanelInfos("Operational intensity STAT Sum", Units.flop_per_byte),
+ PanelInfos('AVX DP [MFLOP/s] STAT Sum" / "DP [MFLOP/s] STAT Sum', Units.percent),
+ PanelInfos('Memory bandwidth [MBytes/s] STAT Sum', Units.mbytes_per_second),
+ PanelInfos('Memory write bandwidth [MBytes/s] STAT Sum', Units.mbytes_per_second),
+ PanelInfos('Memory read bandwidth [MBytes/s] STAT Sum', Units.mbytes_per_second),
+ PanelInfos('Memory data volume [GBytes] STAT Sum', Units.gigabyte),
+ PanelInfos('Memory read data volume [GBytes] STAT Sum', Units.gigabyte),
+ PanelInfos('Memory write data volume [GBytes] STAT Sum', Units.gigabyte),
+ PanelInfos('Energy [J] STAT Sum', Units.joule),
+ PanelInfos('Power [W] STAT Sum', Units.watt),
+ PanelInfos('Clock [MHz] STAT Avg', Units.megahertz), ]
+
options = DashboardOptions(
title="FE2ti Benchmarks",
description="Benchmarks for fe2ti",
tags=['benchmark', 'fe2ti'],
timezone="browser",
)
- annotations = get_commit_annotation(data_source, "red", "commits",
- measurment_name)
+ annotations = get_commit_annotation(data_source, "red", "commits", measurment_name)
+
overrides = [*[
get_color_regex_override(f".*[Ss]olver.*: {solver}.*", color)
for solver, color in [("pardiso", "#56A64B"), ("umfpack", "#F2CC0C"), ("ilu", "#3274D9")]
@@ -111,23 +120,22 @@ def dashboard_fe2ti():
description_panel = pack_in_row("Legend", get_text_panel(description_markdown, title="FE2TI benchmarks"))
panels = [
- TimeSeries(
- title=field,
- dataSource=data_source,
- targets=[get_influx_target(str(query))],
- unit=unit,
- pointSize=9,
+ get_time_series_panel(
+ field,
+ data_source,
+ measurment_name,
+ where=where,
+ group_by=[f.name for f in other_filters],
overrides=overrides,
)
- for field, query, unit in zip(fields, queries, units)
- ]
+ for field in fields]
+
row = pack_in_row(
title=f"{row_repeat}: ${row_repeat_var.name}",
panels=[*panels],
repeat=Repeat('v', row_repeat_var.name),
-
)
return build_dashboard(options,
rows=[description_panel, row],
- templating=[row_repeat_var, *other_vars],
+ templating=[*other_vars],
annotations=annotations)