benn/lumiera_
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions
lumiera_/tests/vault/gear/scheduler-stress-test.cpp
Ichthyostega 8e33194882 Scheduler-test: settle definition of specific test setup and data 
After a lot of further tinkering, seemingly arriving at a
somewhat satisfactory solution for the layout and arrangement of
test definitions and especially the table for measurement series.

While the complete setup remains fragile indeed, and complexity is more
hidden than reduced — the pragmatic compromise established yesterday
at least allows to reduce the amount of boilerplate in the test or
measurement setup to make the actual specifics stand out clearly.

----

As an aside, the usage of the `DataFile` type imported from Yoshimi-test
recently was re-shaped more towards a generic handling of tabular data with
CSV storage option; thus renaming the type now into `DataTable`.
Persistent storage is now just one option, while another usage pattern
compounds observation data into table rows, which are then directly
rendered into a CSV string, e.g. for visualisation as Gnuplot graph.
2024-04-08 03:58:15 +02:00

526 lines
22 KiB
C++
Raw Blame History

/*
SchedulerStress(Test) - verify scheduler performance characteristics
Copyright (C) Lumiera.org
2023, Hermann Vosseler <Ichthyostega@web.de>
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License as
published by the Free Software Foundation; either version 2 of
the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
* *****************************************************/
/** @file scheduler-usage-test.cpp
** unit test \ref SchedulerStress_test
*/
#include "lib/test/run.hpp"
#include "test-chain-load.hpp"
#include "stress-test-rig.hpp"
#include "vault/gear/scheduler.hpp"
#include "lib/time/timevalue.hpp"
#include "lib/format-string.hpp"
#include "lib/format-cout.hpp"
#include "lib/gnuplot-gen.hpp"
#include "lib/test/diagnostic-output.hpp"//////////////////////////TODO work in distress
//#include "lib/format-string.hpp"
#include "lib/test/transiently.hpp"
//#include "lib/test/microbenchmark.hpp"
//#include "lib/util.hpp"
//#include <utility>
//#include <vector>
#include <array>
using test::Test;
//using std::move;
//using util::isSameObject;
namespace vault{
namespace gear {
namespace test {
// using lib::time::FrameRate;
// using lib::time::Offset;
// using lib::time::Time;
using util::_Fmt;
// using std::vector;
using std::array;
namespace { // Test definitions and setup...
}
/***************************************************************************//**
* @test Investigate and verify non-functional characteristics of the Scheduler.
* @see SchedulerActivity_test
* @see SchedulerInvocation_test
* @see SchedulerCommutator_test
* @see stress-test-rig.hpp
*/
class SchedulerStress_test : public Test
{
virtual void
run (Arg)
{
//smokeTest();
// setup_systematicSchedule();
// verify_instrumentation();
// search_breaking_point();
watch_expenseFunction();
// investigateWorkProcessing();
walkingDeadline();
}
/** @test TODO demonstrate sustained operation under load
* - TODO this is a placeholder and works now, but need a better example
* - it should not produce so much overload, rather some stretch of steady-state processing
* @todo WIP 12/23 🔁 define ⟶ implement
*/
void
smokeTest()
{
MARK_TEST_FUN
TestChainLoad testLoad{512};
testLoad.configureShape_chain_loadBursts()
.buildTopology()
// .printTopologyDOT()
;
auto stats = testLoad.computeGraphStatistics();
cout << _Fmt{"Test-Load: Nodes: %d Levels: %d ∅Node/Level: %3.1f Forks: %d Joins: %d"}
% stats.nodes
% stats.levels
% stats.indicators[STAT_NODE].pL
% stats.indicators[STAT_FORK].cnt
% stats.indicators[STAT_JOIN].cnt
<< endl;
// while building the calculation-plan graph
// node hashes were computed, observing dependencies
size_t expectedHash = testLoad.getHash();
// some jobs/nodes are marked with a weight-step
// these can be instructed to spend some CPU time
auto LOAD_BASE = 500us;
testLoad.performGraphSynchronously(LOAD_BASE);
CHECK (testLoad.getHash() == expectedHash);
double referenceTime = testLoad.calcRuntimeReference(LOAD_BASE);
cout << "refTime(singleThr): "<<referenceTime/1000<<"ms"<<endl;
// Perform through Scheduler----------
BlockFlowAlloc bFlow;
EngineObserver watch;
Scheduler scheduler{bFlow, watch};
double performanceTime =
testLoad.setupSchedule(scheduler)
.withLoadTimeBase(LOAD_BASE)
.withJobDeadline(150ms)
.withPlanningStep(200us)
.withChunkSize(20)
.launch_and_wait();
cout << "runTime(Scheduler): "<<performanceTime/1000<<"ms"<<endl;
// invocation through Scheduler has reproduced all node hashes
CHECK (testLoad.getHash() == expectedHash);
}
/** @test build a scheme to adapt the schedule to expected runtime.
* - as in many other tests, use the massively forking load pattern
* - demonstrate how TestChainLoad computes an idealised level expense
* - verify how schedule times are derived from this expense sequence
* @todo WIP 12/23 ✔ define ⟶ ✔ implement
*/
void
setup_systematicSchedule()
{
TestChainLoad testLoad{64};
testLoad.configureShape_chain_loadBursts()
.buildTopology()
// .printTopologyDOT()
// .printTopologyStatistics()
;
auto LOAD_BASE = 500us;
ComputationalLoad cpuLoad;
cpuLoad.timeBase = LOAD_BASE;
cpuLoad.calibrate();
double micros = cpuLoad.invoke();
CHECK (micros < 550);
CHECK (micros > 450);
// build a schedule sequence based on
// summing up weight factors, with example concurrency ≔ 4
uint concurrency = 4;
auto stepFactors = testLoad.levelScheduleSequence(concurrency).effuse();
CHECK (stepFactors.size() == 1+testLoad.topLevel());
CHECK (stepFactors.size() == 27);
// Build-Performance-test-setup--------
BlockFlowAlloc bFlow;
EngineObserver watch;
Scheduler scheduler{bFlow, watch};
auto testSetup =
testLoad.setupSchedule(scheduler)
.withLoadTimeBase(LOAD_BASE)
.withJobDeadline(50ms)
.withUpfrontPlanning();
auto schedule = testSetup.getScheduleSeq().effuse();
CHECK (schedule.size() == testLoad.topLevel() + 2);
CHECK (schedule[ 0] == _uTicks(0ms));
CHECK (schedule[ 1] == _uTicks(1ms));
CHECK (schedule[ 2] == _uTicks(2ms));
// ....
CHECK (schedule[25] == _uTicks(25ms));
CHECK (schedule[26] == _uTicks(26ms));
CHECK (schedule[27] == _uTicks(27ms));
// Adapted Schedule----------
double stressFac = 1.0;
testSetup.withAdaptedSchedule (stressFac, concurrency);
schedule = testSetup.getScheduleSeq().effuse();
CHECK (schedule.size() == testLoad.topLevel() + 2);
CHECK (schedule[ 0] == _uTicks(0ms));
CHECK (schedule[ 1] == _uTicks(0ms));
// verify the numbers in detail....
_Fmt stepFmt{"lev:%-2d stepFac:%-6.3f schedule:%6.3f"};
auto stepStr = [&](uint i){ return string{stepFmt % i % stepFactors[i>0?i-1:0] % (_raw(schedule[i])/1000.0)}; };
CHECK (stepStr( 0) == "lev:0 stepFac:0.000 schedule: 0.000"_expect);
CHECK (stepStr( 1) == "lev:1 stepFac:0.000 schedule: 0.000"_expect);
CHECK (stepStr( 2) == "lev:2 stepFac:0.000 schedule: 0.000"_expect);
CHECK (stepStr( 3) == "lev:3 stepFac:2.000 schedule: 1.000"_expect);
CHECK (stepStr( 4) == "lev:4 stepFac:2.000 schedule: 1.000"_expect);
CHECK (stepStr( 5) == "lev:5 stepFac:2.000 schedule: 1.000"_expect);
CHECK (stepStr( 6) == "lev:6 stepFac:2.000 schedule: 1.000"_expect);
CHECK (stepStr( 7) == "lev:7 stepFac:3.000 schedule: 1.500"_expect);
CHECK (stepStr( 8) == "lev:8 stepFac:5.000 schedule: 2.500"_expect);
CHECK (stepStr( 9) == "lev:9 stepFac:7.000 schedule: 3.500"_expect);
CHECK (stepStr(10) == "lev:10 stepFac:8.000 schedule: 4.000"_expect);
CHECK (stepStr(11) == "lev:11 stepFac:8.000 schedule: 4.000"_expect);
CHECK (stepStr(12) == "lev:12 stepFac:8.000 schedule: 4.000"_expect);
CHECK (stepStr(13) == "lev:13 stepFac:9.000 schedule: 4.500"_expect);
CHECK (stepStr(14) == "lev:14 stepFac:10.000 schedule: 5.000"_expect);
CHECK (stepStr(15) == "lev:15 stepFac:12.000 schedule: 6.000"_expect);
CHECK (stepStr(16) == "lev:16 stepFac:12.000 schedule: 6.000"_expect);
CHECK (stepStr(17) == "lev:17 stepFac:13.000 schedule: 6.500"_expect);
CHECK (stepStr(18) == "lev:18 stepFac:16.000 schedule: 8.000"_expect);
CHECK (stepStr(19) == "lev:19 stepFac:16.000 schedule: 8.000"_expect);
CHECK (stepStr(20) == "lev:20 stepFac:20.000 schedule:10.000"_expect);
CHECK (stepStr(21) == "lev:21 stepFac:22.500 schedule:11.250"_expect);
CHECK (stepStr(22) == "lev:22 stepFac:24.167 schedule:12.083"_expect);
CHECK (stepStr(23) == "lev:23 stepFac:26.167 schedule:13.083"_expect);
CHECK (stepStr(24) == "lev:24 stepFac:28.167 schedule:14.083"_expect);
CHECK (stepStr(25) == "lev:25 stepFac:30.867 schedule:15.433"_expect);
CHECK (stepStr(26) == "lev:26 stepFac:31.867 schedule:15.933"_expect);
CHECK (stepStr(27) == "lev:27 stepFac:32.867 schedule:16.433"_expect);
// Adapted Schedule with lower stress level and higher concurrency....
stressFac = 0.3;
concurrency = 6;
stepFactors = testLoad.levelScheduleSequence(concurrency).effuse();
testSetup.withAdaptedSchedule (stressFac, concurrency);
schedule = testSetup.getScheduleSeq().effuse();
CHECK (stepStr( 0) == "lev:0 stepFac:0.000 schedule: 0.000"_expect);
CHECK (stepStr( 1) == "lev:1 stepFac:0.000 schedule: 0.000"_expect);
CHECK (stepStr( 2) == "lev:2 stepFac:0.000 schedule: 0.000"_expect);
CHECK (stepStr( 3) == "lev:3 stepFac:2.000 schedule: 3.333"_expect);
CHECK (stepStr( 4) == "lev:4 stepFac:2.000 schedule: 3.333"_expect);
CHECK (stepStr( 5) == "lev:5 stepFac:2.000 schedule: 3.333"_expect);
CHECK (stepStr( 6) == "lev:6 stepFac:2.000 schedule: 3.333"_expect);
CHECK (stepStr( 7) == "lev:7 stepFac:3.000 schedule: 5.000"_expect);
CHECK (stepStr( 8) == "lev:8 stepFac:5.000 schedule: 8.333"_expect);
CHECK (stepStr( 9) == "lev:9 stepFac:7.000 schedule:11.666"_expect);
CHECK (stepStr(10) == "lev:10 stepFac:8.000 schedule:13.333"_expect);
CHECK (stepStr(11) == "lev:11 stepFac:8.000 schedule:13.333"_expect);
CHECK (stepStr(12) == "lev:12 stepFac:8.000 schedule:13.333"_expect);
CHECK (stepStr(13) == "lev:13 stepFac:9.000 schedule:15.000"_expect);
CHECK (stepStr(14) == "lev:14 stepFac:10.000 schedule:16.666"_expect);
CHECK (stepStr(15) == "lev:15 stepFac:12.000 schedule:20.000"_expect);
CHECK (stepStr(16) == "lev:16 stepFac:12.000 schedule:20.000"_expect);
CHECK (stepStr(17) == "lev:17 stepFac:13.000 schedule:21.666"_expect);
CHECK (stepStr(18) == "lev:18 stepFac:16.000 schedule:26.666"_expect);
CHECK (stepStr(19) == "lev:19 stepFac:16.000 schedule:26.666"_expect);
CHECK (stepStr(20) == "lev:20 stepFac:18.000 schedule:30.000"_expect); // note: here the higher concurrency allows to process all 5 concurrent nodes at once
CHECK (stepStr(21) == "lev:21 stepFac:20.500 schedule:34.166"_expect);
CHECK (stepStr(22) == "lev:22 stepFac:22.167 schedule:36.944"_expect);
CHECK (stepStr(23) == "lev:23 stepFac:23.167 schedule:38.611"_expect);
CHECK (stepStr(24) == "lev:24 stepFac:24.167 schedule:40.277"_expect);
CHECK (stepStr(25) == "lev:25 stepFac:25.967 schedule:43.277"_expect);
CHECK (stepStr(26) == "lev:26 stepFac:26.967 schedule:44.944"_expect);
CHECK (stepStr(27) == "lev:27 stepFac:27.967 schedule:46.611"_expect);
// perform a Test with this low stress level (0.3)
double runTime = testSetup.launch_and_wait();
double expected = testSetup.getExpectedEndTime();
CHECK (fabs (runTime-expected) < 5000);
} // Scheduler should able to follow the expected schedule
/** @test verify capability for instrumentation of job invocations
* @see IncidenceCount_test
* @todo WIP 2/24 ✔ define ⟶ ✔ implement
*/
void
verify_instrumentation()
{
const size_t NODES = 20;
const size_t CORES = work::Config::COMPUTATION_CAPACITY;
auto LOAD_BASE = 5ms;
TestChainLoad testLoad{NODES};
BlockFlowAlloc bFlow;
EngineObserver watch;
Scheduler scheduler{bFlow, watch};
auto testSetup =
testLoad.setWeight(1)
.setupSchedule(scheduler)
.withLoadTimeBase(LOAD_BASE)
.withJobDeadline(50ms)
.withInstrumentation() // activate an instrumentation bracket around each job invocation
;
double runTime = testSetup.launch_and_wait();
auto stat = testSetup.getInvocationStatistic(); // retrieve observed invocation statistics
CHECK (runTime < stat.activeTime);
CHECK (isLimited (4900, stat.activeTime/NODES, 8000)); // should be close to 5000
CHECK (stat.coveredTime < runTime);
CHECK (NODES == stat.activationCnt); // each node activated once
CHECK (isLimited (CORES/2, stat.avgConcurrency, CORES)); // should ideally come close to hardware concurrency
CHECK (0 == stat.timeAtConc(0));
CHECK (0 == stat.timeAtConc(CORES+1));
CHECK (runTime/2 < stat.timeAtConc(CORES-1)+stat.timeAtConc(CORES));
} // should ideally spend most of the time at highest concurrency levels
using StressRig = StressTestRig<16>;
/** @test determine the breaking point towards scheduler overload
* - use the integrated StressRig
* - demonstrate how parameters can be tweaked
* - perform a run, leading to a binary search for the breaking point
* @remark this stress-test setup uses instrumentation internally note to deduce
* some systematic deviations from the theoretically established behaviour.
* For example, on my machine, the ComputationalLoad performs slower within the
* Scheduler environment compared to its calibration, which is done in a tight loop.
* This may be due to internals of the processor, which show up under increased
* contention combined with more frequent cache misses. In a similar vein, the
* actually observed concurrency turns out to be consistently lower than could
* be expected by accounting for the work units in isolation, without considering
* dependency constraints. These observed deviations are cast into an empirical
* »form factor«, which is then used to correct the applied stress factor.
* Only with taking these corrective steps, the observed stress factor at
* _breaking point_ comes close to the theoretically expected value of 1.0
* @see stress-test-rig.hpp
* @todo WIP 1/24 ✔ define ⟶ ✔ implement
*/
void
search_breaking_point()
{
MARK_TEST_FUN
struct Setup : StressRig
{
uint CONCURRENCY = 4;
bool showRuns = true;
auto testLoad()
{ return TestLoad{64}.configureShape_chain_loadBursts(); }
auto testSetup (TestLoad& testLoad)
{
return StressRig::testSetup(testLoad)
.withLoadTimeBase(500us);
}
};
auto [stress,delta,time] = StressRig::with<Setup>()
.perform<bench::BreakingPoint>();
CHECK (delta > 2.5);
CHECK (1.15 > stress and stress > 0.9);
}
/** @test TODO Investigate the relation of run time (expense) to input length.
* @see vault::gear::bench::ParameterRange
* @todo WIP 1/24 🔁 define ⟶ 🔁 implement
*/
void
watch_expenseFunction()
{
ComputationalLoad cpuLoad;
cpuLoad.timeBase = 200us;
cpuLoad.calibrate();
//////////////////////////////////////////////////////////////////TODO for development only
MARK_TEST_FUN
TestChainLoad testLoad{64};
testLoad.configure_isolated_nodes()
.buildTopology()
.printTopologyDOT()
.printTopologyStatistics();
struct Setup
: StressRig, bench::LoadPeak_ParamRange_Evaluation
{
uint CONCURRENCY = 4;
auto testLoad(Param nodes)
{
TestLoad testLoad{nodes};
return testLoad.configure_isolated_nodes();
}
auto testSetup (TestLoad& testLoad)
{
return StressRig::testSetup(testLoad)
.withLoadTimeBase(500us);
}
};
auto results = StressRig::with<Setup>()
.perform<bench::ParameterRange> (2,64);
auto csv = results.renderCSV();
cout << csv <<endl;
cout << "───═══───═══───═══───═══───═══───═══───═══───═══───═══───═══───"<<endl;
cout << lib::gnuplot_gen::scatterRegression(csv);
}
/** @test TODO
* @todo WIP 1/24 🔁 define ⟶ implement
*/
void
investigateWorkProcessing()
{
MARK_TEST_FUN
TestChainLoad<8> testLoad{256};
testLoad.seedingRule(testLoad.rule().probability(0.6).minVal(2))
.pruningRule(testLoad.rule().probability(0.44))
.setSeed(55)
.buildTopology()
// .printTopologyDOT()
// .printTopologyStatistics()
;
// ////////////////////////////////////////////////////////WIP : Run test directly for investigation of SEGFAULT....
// BlockFlowAlloc bFlow;
// EngineObserver watch;
// Scheduler scheduler{bFlow, watch};
auto LOAD_BASE = 500us;
// auto stressFac = 1.0;
// auto concurrency = 8;
//
ComputationalLoad cpuLoad;
cpuLoad.timeBase = LOAD_BASE;
cpuLoad.calibrate();
//
double loadMicros = cpuLoad.invoke();
// double refTime = testLoad.calcRuntimeReference(LOAD_BASE);
SHOW_EXPR(loadMicros)
//
// auto testSetup =
// testLoad.setupSchedule(scheduler)
// .withLoadTimeBase(LOAD_BASE)
// .withJobDeadline(50ms)
// .withUpfrontPlanning()
// .withAdaptedSchedule (stressFac, concurrency);
// double runTime = testSetup.launch_and_wait();
// double expected = testSetup.getExpectedEndTime();
//SHOW_EXPR(runTime)
//SHOW_EXPR(expected)
//SHOW_EXPR(refTime)
using StressRig = StressTestRig<8>;
struct Setup : StressRig
{
double UPPER_STRESS = 12;
//
double FAIL_LIMIT = 1.0; //0.7;
double TRIGGER_SDEV = 1.0; //0.25;
double TRIGGER_DELTA = 2.0; //0.5;
// uint CONCURRENCY = 4;
// bool SCHED_DEPENDS = true;
bool showRuns = true;
auto
testLoad()
{
TestLoad testLoad{256};
testLoad.seedingRule(testLoad.rule().probability(0.6).minVal(2))
.pruningRule(testLoad.rule().probability(0.44))
.weightRule(testLoad.value(1))
.setSeed(55);
return testLoad;
}
auto testSetup (TestLoad& testLoad)
{
return StressRig::testSetup(testLoad)
.withBaseExpense(200us)
.withLoadTimeBase(500us);
}
};
auto [stress,delta,time] = StressRig::with<Setup>()
.perform<bench::BreakingPoint>();
SHOW_EXPR(stress)
SHOW_EXPR(delta)
SHOW_EXPR(time)
}
/** @test TODO
* @todo WIP 1/24 🔁 define ⟶ implement
*/
void
walkingDeadline()
{
}
};
/** Register this test class... */
LAUNCHER (SchedulerStress_test, "unit engine");
}}} // namespace vault::gear::test
Reference in a new issue View git blame Copy permalink