test-chain-load.hpp File Reference

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Description

Generate synthetic computation load for Scheduler performance tests.

The Scheduler is a service to invoke Render Job instances concurrently in accordance to a time plan. To investigate the runtime and performance characteristics of the implementation, a well-defined artificial computation load is necessary, comprised of the invocation of an extended number of Jobs, each configured to carry out a reproducible computation. Data dependencies between jobs can be established to verify handling of dependent jobs and job completion messages within the scheduler.

Random computation structure

A system of connected hash values is used as computation load, akin to a blockchain. Each processing step is embodied into a node, with a hash value computed by combining all predecessor nodes. Connectivity is represented as bidirectional pointer links, each nodes knows its predecessors and successors (if any), while the maximum fan out or fan in and the total number of nodes is limited statically. All nodes are placed into a single pre-allocated memory block and always processed in ascending dependency order. The result hash from complete processing can thus be computed by a single linear pass over all nodes; yet alternatively each node can be scheduled as an individual computation job, which obviously requires that it's predecessor nodes have already been computed, otherwise the resulting hash will not match up with expectation. If significant per-node computation time is required, an artificial computational load can be generated, controlled by a weight setting computed for each node.

The topology of connectivity is generated randomly, yet completely deterministic through configurable control functions driven by each node's (hash)value. This way, each node can optionally fork out to several successor nodes, but can also reduce and combine its predecessor nodes; additionally, new chains can be spawned (to simulate the effect of data loading Jobs without predecessor) and chains can be deliberately pruned, possibly splitting the computation into several disjoint sub-graphs. Anyway, the computation always begins with the root node, establishes the node links and marks each open end as an exit node — until all the nodes in the pre-allocated node space were visited. Hash values of all exit nodes will be combined into one characteristic hash for the graph, The probabilistic rules controlling the topology can be configured using the lib::RandomDraw component, allowing either just to set a fixed probability or to define elaborate dynamic configurations based on the graph height or node connectivity properties.

• expansionRule: controls forking of the graph behind the current node
• reductionRule: controls joining of the graph into a combining successor node
• seedingRule: controls injection of new start nodes in the middle of the graph
• pruningRule: controls insertion of exit nodes to cut-off some chain immediately
• weightRule: controls assignment of a Node::weight to command the ComputationalLoad

Usage

A TestChainLoad instance is created with predetermined maximum fan factor and a fixed number of nodes, which are immediately allocated and initialised. Using builder notation, control functions can then be configured. The topology generation then traverses the nodes, starting with the seed value from the root node, and establishes the complete node connectivity. After this priming, the expected result hash should be retrieved. The node structure can then be traversed or scheduled as Render Jobs.

A special use case is not to build any topology, rather only #setWeight(). All nodes ** will then be at level-0 and scheduled at t=0, causing the scheduler to process best effort in arbitrary order.

Test support

A tool for generating roughly calibrated computational load is included, to be controlled by the Node::weight stepping. Load can either be generated by arithmetic (hash) computations, or by accessing and adding memory in a private allocated data block. To make this load controllable, the instance is configured with a time base setting, with sensible settings between 50µs to 100ms; moreover, a calibration run is necessary once per runtime (static variables); the actual invocation uses a multiple of this base setting, as determined by the Node::weight.

This allows to render individual steps in the calculation graph much more expensive than the associated organisational code and setup, and thus creates the foundation for building realistic test scenarios. For a given graph instance, a runtime weight can be estimated heuristically, expressed in multiples of the Node::weight ≡ 1, taking into account the possible parallelisation per level of nodes described by an idealised model.

For the actual test run, a ScheduleCtx is built, using an actual scheduler instance. Specialised render job functors are provided to perform incremental job planning and invocation of individual nodes in the graph as computation steps, optionally with a computation load. The scheduler is triggered by inserting the initial planning job in a pre roll phase, blocking the main thread until a callback job is invoked, which is set as final dependency behind the exit node of the complete graph, returning a observed runtime in microseconds from the nominal start point of the schedule.

Observation tools

The generated topology can be visualised as a graph, using the Graphviz-DOT language. Nodes are rendered from bottom to top, organised into strata according to the time-level and showing predecessor -> successor connectivity. Seed nodes are distinguished by circular shape.

The complete graph can be performed synchronously, allowing to watch a baseline run-time when execution all nodes consecutively, using the configured load but without any time gaps. The run time in µs can be compared to the timings observed when performing the graph through the Scheduler. Moreover, Statistics can be computed over the generated graph, allowing to draw some conclusions regarding node distribution and connectivity.

See also

TestChainLoad_test

SchedulerStress_test

random-draw.hpp

Definition in file test-chain-load.hpp.

#include "vault/common.hpp"
#include "lib/test/transiently.hpp"
#include "vault/gear/job.h"
#include "vault/gear/scheduler.hpp"
#include "vault/gear/special-job-fun.hpp"
#include "lib/uninitialised-storage.hpp"
#include "lib/test/microbenchmark.hpp"
#include "lib/incidence-count.hpp"
#include "lib/time/timevalue.hpp"
#include "lib/time/quantiser.hpp"
#include "lib/iter-explorer.hpp"
#include "lib/format-string.hpp"
#include "lib/format-cout.hpp"
#include "lib/random-draw.hpp"
#include "lib/dot-gen.hpp"
#include "lib/util.hpp"
#include <boost/functional/hash.hpp>
#include <functional>
#include <utility>
#include <future>
#include <memory>
#include <string>
#include <vector>
#include <tuple>
#include <array>

Classes
struct	TestChainLoad< maxFan >::NodeControlBinding::Adaptor< SIG >
	Adaptor to handle further mapping functions. More...
struct	TestChainLoad< maxFan >::NodeControlBinding::Adaptor< RES(double)>
	rules may also build solely on the (guessed) height. More...
struct	TestChainLoad< maxFan >::NodeControlBinding::Adaptor< RES(size_t)>
	allow simple rules directly manipulating the hash value More...
struct	TestChainLoad< maxFan >::NodeControlBinding::Adaptor< RES(size_t, double)>
	allow rules additionally involving the height of the graph, which also represents time. More...
class	ChainFunctor
	Baseclass: JobFunctor to invoke TestChainLoad. More...
class	ComputationalLoad
	A calibratable CPU load to be invoked from a node job functor. More...
struct	Indicator
	Distribution indicators for one kind of evaluation. More...
struct	LevelWeight
struct	TestChainLoad< maxFan >::Node
	Graph Data structure. More...
class	TestChainLoad< maxFan >::NodeControlBinding
	Policy/Binding for generation of random parameters by »drawing« based on the node-hash. More...
class	RandomChainCalcFunctor< maxFan >
	Render JobFunctor to invoke the calculation of a single Node. More...
class	RandomChainPlanFunctor< maxFan >
	Render JobFunctor to perform chunk wise planning of Node jobs to calculate a complete Chain-Load graph step by step. More...
class	TestChainLoad< maxFan >::ScheduleCtx
	Setup and wiring for a test run to schedule a computation structure as defined by this TestChainLoad instance. More...
struct	Statistic
	Statistic data calculated for a given chain-load topology. More...
struct	StatKey
struct	TestChainLoad< maxFan >::Node::Tab
	Table with connections to other Node records. More...
class	TestChainLoad< maxFan >
	A Generator for synthetic Render Jobs for Scheduler load testing. More...

Typedefs
using	LevelSums = std::array< uint, CAT >
using	VecU = std::vector< uint >

Functions
double	_uSec (microseconds ticks)
double	computeWeightFactor (LevelWeight const &lw, uint concurrency)
	simplified model for expense of a level of nodes, computed concurrently. More...
uint	defaultConcurrency ()
SpecialJobFun	onetimeCrunch (milliseconds runTime)
	a »throw-away« render-job
template<class NOD >
auto	prepareEvaluations ()

Variables
const uint	CAT = KEYS.size()
const size_t	DEFAULT_CHUNKSIZE = 64
	number of computation jobs to prepare in each planning round
const size_t	DEFAULT_FAN = 16
	default maximum connectivity per Node
const size_t	DEFAULT_SIZ = 256
	default node count for the complete load graph
const size_t	GRAPH_BENCHMARK_RUNS = 5
	repetition count for reference calculation of a complete node graph
const uint	IDX_SEED = 1
const std::array	KEYS = {STAT_NODE,STAT_SEED,STAT_EXIT,STAT_INNR,STAT_FORK,STAT_JOIN,STAT_LINK,STAT_KNOT,STAT_WGHT}
const size_t	LOAD_BENCHMARK_RUNS = 500
	repetition count for calibration benchmark for ComputationalLoad
const size_t	LOAD_DEFAULT_MEM_SIZE = 1000
	default allocation base size used if ComputationalLoad.useAllocation
const microseconds	LOAD_DEFAULT_TIME = 100us
	default time delay produced by ComputationalLoad at Node.weight==1
const double	LOAD_SPEED_BASELINE = 100
	initial assumption for calculation speed (without calibration)
const auto	SAFETY_TIMEOUT = 5s
	maximum time limit for test run, abort if exceeded
const bool	SCHED_DEPENDS = false
	explicitly schedule a dependent job (or rely on NOTIFY)
const bool	SCHED_NOTIFY = true
	explicitly set notify dispatch time to the dependency's start time.
const Duration	SCHEDULE_LEVEL_STEP {_uTicks(1ms)}
	time budget to plan for the calculation of each »time level« of jobs
const Duration	SCHEDULE_NODE_STEP {Duration::NIL}
	additional time step to include in the plan for each job (node).
const Duration	SCHEDULE_PLAN_STEP {_uTicks(100us)}
	time budget to reserve for each node to be planned and scheduled
const Offset	SCHEDULE_WAKE_UP {_uTicks(10us)}
	tiny offset to place the final wake-up job behind any systematic schedule
const auto	STANDARD_DEADLINE = 30ms
	deadline to use for each individual computation job
const StatKey	STAT_EXIT {2,"exit"}
	exit node
const StatKey	STAT_FORK {4,"fork"}
	forking node
const StatKey	STAT_INNR {3,"innr"}
	inner node
const StatKey	STAT_JOIN {5,"join"}
	joining node
const StatKey	STAT_KNOT {7,"knot"}
	knot (joins and forks)
const StatKey	STAT_LINK {6,"link"}
	1:1 linking node
const StatKey	STAT_NODE {0,"node"}
	all nodes
const StatKey	STAT_SEED {1,"seed"}
	seed node
const StatKey	STAT_WGHT {8,"wght"}
	node weight
const double	UPFRONT_PLANNING_BOOST = 2.6
	factor to increase the computed pre-roll to ensure up-front planning

Namespaces
	vault
	Vault-Layer implementation namespace root.
	vault::gear
	Active working gear and plumbing.

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Class Documentation

vault::gear::test::TestChainLoad::NodeControlBinding::Adaptor

struct vault::gear::test::TestChainLoad::NodeControlBinding::Adaptor

Collaboration diagram for TestChainLoad< maxFan >::NodeControlBinding::Adaptor< SIG >:

Function Documentation

computeWeightFactor()

double vault::gear::test::computeWeightFactor ( LevelWeight const &  lw, uint  concurrency  )

inline

simplified model for expense of a level of nodes, computed concurrently.

Remarks

assumptions of this model

• weight factor describes expense to compute a node
• nodes on the same level can be parallelised without limitation
• no consideration of stacking / ordering of tasks; rather the speed-up is applied as an average factor to the summed node weights for a level

Returns

guess for a compounded weight factor

Definition at line 237 of file test-chain-load.hpp.

References vault::gear::test::computeWeightFactor().

Referenced by TestChainLoad< maxFan >::calcExpectedCompoundedWeight(), vault::gear::test::computeWeightFactor(), and TestChainLoad< maxFan >::levelScheduleSequence().

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