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 7798ef499c Scheduler-test: adapt assertions to changes in load generation 
This amends test code, which was commented-out for some time,
and was affected by the changes in load-graph generation:

a983a506b

These changes typically lead to a simplified topology at the end
of the load graph, since open ends are no longer connected to a
single exit node. In the case here, level 27 is no longer generate,
and level 26 is now comprised of three nodes, two of them with load=2
2024-04-12 02:23:31 +02:00

551 lines
23 KiB
C++
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

/*
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/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() == 26);
// 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[24] == _uTicks(24ms));
CHECK (schedule[25] == _uTicks(25ms));
CHECK (schedule[26] == _uTicks(26ms));
// 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:32.200 schedule:16.100"_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:27.300 schedule:45.500"_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 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 the value
* computed 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 > 0.85);
}
/** @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{200};
testLoad.configure_isolated_nodes()
.buildTopology()
// .printTopologyDOT()
.printTopologyStatistics();
{
TRANSIENTLY(work::Config::COMPUTATION_CAPACITY) = 4;
BlockFlowAlloc bFlow;
EngineObserver watch;
Scheduler scheduler{bFlow, watch};
auto set1 = testLoad.setupSchedule(scheduler)
.withLevelDuration(200us)
.withJobDeadline(500ms)
.withUpfrontPlanning()
.withLoadTimeBase(2ms)
.withInstrumentation();
double runTime = set1.launch_and_wait();
auto stat = set1.getInvocationStatistic();
cout << "time="<<runTime/1000
<< " covered="<<stat.coveredTime / 1000
<< " avgconc="<<stat.avgConcurrency
<<endl;
}
return;
*/
struct Setup
: StressRig, bench::LoadPeak_ParamRange_Evaluation
{
uint CONCURRENCY = 8;
uint REPETITIONS = 80;
auto testLoad(Param nodes)
{
TestLoad testLoad{nodes};
return testLoad.configure_isolated_nodes();
}
auto testSetup (TestLoad& testLoad)
{
return StressRig::testSetup(testLoad)
.withLoadTimeBase(2ms);
}
};
auto results = StressRig::with<Setup>()
.perform<bench::ParameterRange> (20,200);
cout << "───═══───═══───═══───═══───═══───═══───═══───═══───═══───═══───"<<endl;
cout << Setup::renderGnuplot (results);
cout << "───═══───═══───═══───═══───═══───═══───═══───═══───═══───═══───"<<endl;
auto [socket,gradient,v1,v2,corr,maxDelta,stdev] = bench::linearRegression (results.param, results.time);
double avgConc = Setup::avgConcurrency (results);
cout << _Fmt{"Model: %3.2f·p + %3.2f corr=%4.2f Δmax=%4.2f σ=%4.2f ∅concurrency: %3.1f"}
% gradient % socket % corr % maxDelta % stdev % avgConc
<< endl;
}
/** @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