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Updating Geekbench workload to support the latest versions of both the standard and corporate application

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scott 2018-02-07 15:27:50 +00:00 committed by Marc Bonnici
parent efc7dc9326
commit 6e946a53dd
3 changed files with 21 additions and 32 deletions
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36
wa/workloads/geekbench/__init__.py
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@ -29,33 +29,28 @@ class Geekbench(ApkUiautoWorkload):
description = """
Geekbench provides a comprehensive set of benchmarks engineered to quickly
and accurately measure processor and memory performance.
http://www.primatelabs.com/geekbench/
From the website:
Designed to make benchmarks easy to run and easy to understand, Geekbench
takes the guesswork out of producing robust and reliable benchmark results.
Geekbench scores are calibrated against a baseline score of 1,000 (which is
the score of a single-processor Power Mac G5 @ 1.6GHz). Higher scores are
better, with double the score indicating double the performance.
The benchmarks fall into one of four categories:
- integer performance.
- floating point performance.
- memory performance.
- stream performance.
Geekbench benchmarks: http://www.primatelabs.com/geekbench/doc/benchmarks.html
Geekbench scoring methedology:
http://support.primatelabs.com/kb/geekbench/interpreting-geekbench-scores
"""
summary_metrics = ['score', 'multicore_score']
versions = {
'4.2.0': {
'package': 'com.primatelabs.geekbench',
'activity': '.HomeActivity',
},
'4.0.1': {
'package': 'com.primatelabs.geekbench',
'activity': '.HomeActivity',
@ -85,7 +80,7 @@ class Geekbench(ApkUiautoWorkload):
Parameter('times', kind=int, default=1,
description=('Specfies the number of times the benchmark will be run in a "tight '
'loop", i.e. without performaing setup/teardown inbetween.')),
Parameter('timeout', kind=int, default=900,
Parameter('timeout', kind=int, default=3600,
description=('Timeout for a single iteration of the benchmark. This value is '
'multiplied by ``times`` to calculate the overall run timeout. ')),
Parameter('disable_update_result', kind=bool, default=False,
@ -118,6 +113,7 @@ class Geekbench(ApkUiautoWorkload):
self.gui.uiauto_params['version'] = self.version
self.gui.uiauto_params['times'] = self.times
self.gui.uiauto_params['is_corporate'] = self.is_corporate
self.gui.timeout = self.timeout
def initialize(self, context):
super(Geekbench, self).initialize(context)
@ -194,12 +190,12 @@ class Geekbench(ApkUiautoWorkload):
context.add_metric(namemify(section['name'] + '_' + workload_name + '_score', i),
workloads['score'])
update_result_5 = update_result_4
class GBWorkload(object):
"""
Geekbench workload (not to be confused with WA's workloads). This is a single test run by
geek bench, such as preforming compression or generating Madelbrot.
"""
# Index maps onto the hundreds digit of the ID.
@ -224,7 +220,6 @@ class GBWorkload(object):
Power Mac G5 running in a single thread.
:param pmac_g5_mt_score: Score achieved for this workload on 2003 entry-level
Power Mac G5 running in multiple threads.
"""
self.wlid = wlid
self.name = name
@ -247,15 +242,12 @@ class GBWorkload(object):
Returns a tuple (single-thraded score, multi-threaded score) for this workload.
Some workloads only have a single-threaded score, in which case multi-threaded
score will be ``None``.
Geekbench will perform four iterations of each workload in single-threaded and,
for some workloads, multi-threaded configurations. Thus there should always be
either four or eight scores collected for each workload. Single-threaded iterations
are always done before multi-threaded, so the ordering of the scores can be used
to determine which configuration they belong to.
This method should not be called before score collection has finished.
"""
no_of_results = len(self.collected_results)
if no_of_results == 4:
@ -281,7 +273,6 @@ class GBScoreCalculator(object):
"""
Parses logcat output to extract raw Geekbench workload values and converts them into
category and overall scores.
"""
result_regex = re.compile(r'workload (?P<id>\d+) (?P<value>[0-9.]+) '
@ -330,7 +321,6 @@ class GBScoreCalculator(object):
"""
Extract results from the specified file. The file should contain a logcat log of Geekbench execution.
Iteration results in the log appear as 'I/geekbench' category entries in the following format::
| worklod ID value units timing
| \------------- | ----/ ---/
| | | | |
@ -338,7 +328,6 @@ class GBScoreCalculator(object):
| | |
| | -----\
| label random crap we don't care about
"""
for wl in self.workloads:
wl.clear()
@ -352,17 +341,12 @@ class GBScoreCalculator(object):
def update_results(self, context):
"""
http://support.primatelabs.com/kb/geekbench/interpreting-geekbench-2-scores
From the website:
Each workload's performance is compared against a baseline to determine a score. These
scores are averaged together to determine an overall, or Geekbench, score for the system.
Geekbench uses the 2003 entry-level Power Mac G5 as the baseline with a score of 1,000
points. Higher scores are better, with double the score indicating double the performance.
Geekbench provides three different kinds of scores:
:Workload Scores: Each time a workload is executed Geekbench calculates a score based
on the computer's performance compared to the baseline
performance. There can be multiple workload scores for the
@ -371,18 +355,15 @@ class GBScoreCalculator(object):
workload is executed four times (single-threaded scalar code,
multi-threaded scalar code, single-threaded vector code, and
multi-threaded vector code) producing four "Dot Product" scores.
:Section Scores: A section score is the average of all the workload scores for
workloads that are part of the section. These scores are useful
for determining the performance of the computer in a particular
area. See the section descriptions above for a summary on what
each section measures.
:Geekbench Score: The Geekbench score is the weighted average of the four section
scores. The Geekbench score provides a way to quickly compare
performance across different computers and different platforms
without getting bogged down in details.
"""
scores_by_category = defaultdict(list)
for wkload in self.workloads:
@ -407,9 +388,8 @@ class GeekbenchCorproate(Geekbench):
is_corporate = True
requires_network = False
versions = ['4.1.0']
versions = ['4.1.0', '5.0.0']
# The activity name for this version doesn't match the package name
activity = 'com.primatelabs.geekbench.HomeActivity'
package = 'com.primatelabs.geekbench4.corporate'

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wa/workloads/geekbench/com.arm.wa.uiauto.geekbench.apk
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9
wa/workloads/geekbench/uiauto/app/src/main/java/com/arm/wa/uiauto/geekbench/UiAutomation.java
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@ -22,6 +22,7 @@ import android.support.test.runner.AndroidJUnit4;
import android.support.test.uiautomator.UiObject;
import android.support.test.uiautomator.UiObjectNotFoundException;
import android.support.test.uiautomator.UiSelector;
import android.support.test.uiautomator.UiScrollable;
import android.view.KeyEvent;
import com.arm.wa.uiauto.BaseUiAutomation;
@ -92,6 +93,7 @@ public class UiAutomation extends BaseUiAutomation {
}
break;
case 4:
case 5:
runCpuBenchmarks(isCorporate);
waitForResultsv3onwards();
break;
@ -134,6 +136,7 @@ public class UiAutomation extends BaseUiAutomation {
public void runCpuBenchmarks(boolean isCorporate) throws Exception {
// The run button is at the bottom of the view and may be off the screen so swipe to be sure
uiDeviceSwipe(Direction.DOWN, 50);
scrollPage();
String packageName = isCorporate ? "com.primatelabs.geekbench4.corporate"
: "com.primatelabs.geekbench";
@ -184,4 +187,10 @@ public class UiAutomation extends BaseUiAutomation {
shareButton.waitForExists(WAIT_TIMEOUT_5SEC);
shareButton.click();
}
public void scrollPage() throws Exception {
UiScrollable listView = new UiScrollable(new UiSelector().className("android.widget.ScrollView"));
listView.setMaxSearchSwipes(3);
listView.scrollTextIntoView("RUN CPU BENCHMARK");
}
}