WRENCH 102
In WRENCH’s terminology, and execution controller is software that makes all decisions and takes all actions for executing some application workflow using cyberinfrastructure services. It is thus a crucial component in every WRENCH simulator. WRENCH does not provide any execution controller implementation, but provides the means for developing custom ones. This page is meant to provide high-level and detailed information about implementing an execution controller in WRENCH. Full API details are provided in the Developer API Reference.
Basic blueprint for an execution controller implementation
An execution controller implementation needs to use many WRENCH classes, which are accessed by including a single header file:
#include <wrench-dev.h>
An execution controller implementation must derive the
wrench::ExecutionController
class, which means that it must override
several the virtual main()
member function. A typical such
implementation of this function goes through a simple loop as follows:
// A) create/retrieve application workload to execute
// B) obtain information about running services
while (application workload execution has not completed/failed) {
// C) interact with services
// D) wait for an event and react to it
}
In the next three sections, we give details on how to implement the
above. To provide context, we make frequent references to the execution
controllers implemented as part of the example simulators in the
examples/
directory. Afterwards are a few sections that highlight
features and functionality relevant to execution controller development.
A) Finding out information about running services
Services that the execution controller can use are typically passed to
its constructor. Most service classes provide member functions to get
information about the capabilities and properties of the services. For
instance, a wrench::ComputeService
has a
wrench::ComputeService::getNumHosts()
member function that returns
how many compute hosts the service has access to in total. A
wrench::StorageService
has a
wrench::StorageService::getFreeSpace()
member function to find out
how many bytes of free space are available on it. And so on…
To take a concrete example, consider the execution controller
implementation in
examples/workflow_api/basic-examples/batch-bag-of-tasks/TwoTasksAtATimeBatchWMS.cpp
.
This WMS finds out the compute speed of the cores of the compute nodes
available to a wrench::BatchComputeService
as:
double core_flop_rate = (*(batch_service->getCoreFlopRate().begin())).second;
Member function wrench::ComputeService::getCoreFlopRate()
returns a
map of core compute speeds indexed by hostname (the map thus has one
element per compute node available to the service). Since the compute
nodes of a batch compute service are homogeneous, the above code simply
grabs the core speed value of the first element in the map.
It is important to note that these member functions actually involve
communication with the service, and thus incur overhead that is part of
the simulation (as if, in the real-world, you would contact a running
service with a request for information over the network). This is why
the line of code above, in that example execution controller, is
executed once and the core compute speed is stored in the
core_flop_rate
variable to be re-used by the execution controller
repeatedly throughout its execution.
B) Interacting with services
An execution controller can have many and complex interactions with services, especially with compute and storage services. In this section, we describe how WRENCH makes these interactions relatively easy, providing examples for each kind of interaction for each kind of service.
Job Manager and Data Movement Manager
As expected, each service type provides its own API. For instance, a network proximity service provides member functions to query the service’s host distance databases. The Developer API Reference provides all necessary documentation, which also explains which member functions are synchronous and which are asynchronous (in which case some event will occur in the future). However, the WRENCH developer will find that many member functions that one would expect are nowhere to be found. For instance, the compute services do not have (public) member functions for submitting jobs for execution!
The rationale for the above is that many member functions need to be asynchronous so that the execution controller can use services concurrently. For instance, an execution controller could submit a job to two distinct compute services asynchronously, and then wait for the service which completes its job first and cancel the job on the other service. Exposing this asynchronicity to the execution controller would require that the WRENCH developer use data structures to perform the necessary bookkeeping of ongoing service interactions, and process incoming control messages from the services on the (simulated) network or alternately register many callbacks. Instead, WRENCH provides managers. One can think of managers as separate threads that handle all asynchronous interactions with services, and which have been implemented for your convenience to make interacting with services easy.
There are two managers: a job manager
(class wrench::JobManager
) and a data movement manager (class
wrench::DataMovementManager
). The base
wrench::ExecutionController
class provides two member functions for
instantiating and starting these managers:
wrench::ExecutionController::createJobManager()
and
wrench::ExecutionController::createDataMovementManager()
.
Creating one or two of these managers typically is the first thing an
execution controller does. For instance, the execution controller in
examples/workflow_api/basic-examples/bare-metal-data-movement/DataMovementWMS.cpp
starts by doing:
auto job_manager = this->createJobManager();
auto data_movement_manager = this->createDataMovementManager();
Each manager has its own documented API, and is discussed further in sections below.
Interacting with storage services
Typical interactions between an execution controller and a storage service include locating, reading, writing, and copying files. Different storage service implementations may or not implement some of of these operations. Click on the following links to see concrete examples of interactions with the currently available storage service type:
Interacting with compute services
The Job abstraction
The main activity of an execution controller is to execute workflow tasks on compute services. Rather than submitting tasks directly to compute services, an execution controller must create “jobs”, which can comprise multiple tasks and involve data copy/deletion operations. The job abstraction is powerful and greatly simplifies the task of an execution controller while affording flexibility.
There are three kinds of jobs in WRENCH: wrench::CompoundJob
,
wrench::StandardJob
, and wrench::PilotJob
.
A Compound Job is simply set of actions to be performed, with
possible control dependencies between actions. It is the most generic,
flexible, and expressive kind of job. See the API documentation for the
wrench::CompoundJob
class and the examples in the
examples/action_api
directory. The other types of jobs below are
actually implemented internally as compound jobs. The Compound Job
abstraction is the most recent addition to the WRENCH API, and vastly
expands the list of possible things that an execution controller can do.
But because it is more recent, the reader will find that there are more
examples in these documents and in the examples
directory that use
standard jobs (described below). But all these examples could be easily
rewritten using the more generic compound job abstraction.
A Standard Job is a specific kind of job designed for workflow applications. In its most complete form, a standard job specifies:
A set (in fact a vector) of
std::shared_ptr<wrench::WorkflowTask>
to execute, so that each task without all its predecessors in the set is ready;A
std::map
of<std::shared_ptr<wrench::DataFile>>, std::shared_ptr<wrench::StorageService>>
pairs that specifies from which storage services particular input files should be read and to which storage services output files should be written;A set of file copy operations to be performed before executing the tasks;
A set of file copy operations to be performed after executing the tasks; and
A set of file deletion operations to be performed after executing the tasks and file copy operations.
Any of the above can actually be empty, and in the extreme a standard job can do nothing.
A Pilot Job (sometimes called a “placeholder job” in the literature)
is a concept that is mostly relevant for batch scheduling. In a
nutshell, it is a job that allows late binding of tasks to resources. It
is submitted to a compute service (provided that service supports pilot
jobs), and when it starts it just looks to the execution controller like
a short-lived wrench::BareMetalComputeService
to which compound
and/or standard jobs can be submitted.
All jobs are created via the job manager, which provides
wrench::JobManager::createCompoundJob()
,
wrench::JobManager::createStandardJob()
, and
wrench::JobManager::createPilotJob()
member functions (the job
manager is thus a job factory).
In addition to member functions for job creation, the job manager also provides the following:
wrench::JobManager::submitJob()
: asynchronous submission of a job to a compute service.wrench::JobManager::terminateJob()
: synchronous termination of a previously submitted job.
The next section gives examples of interactions with each kind of compute service.
Click on the following links to see detailed descriptions and examples of how jobs are submitted to each compute service type:
Interacting with file registry services
Interaction with a file registry service is straightforward and done by
directly calling member functions of the wrench::FileRegistryService
class. Note that often file registry service entries are managed
automatically, e.g., via calls to wrench::DataMovementManager
and
wrench::StorageService
member functions. So often an execution
controller does not need to interact with the file registry service.
Adding/removing an entry to a file registry service is done as follows:
std::shared_ptr<wrench::FileRegistryService> file_registry;
std::shared_ptr<wrench::DataFile> some_file;
std::shared_ptr<wrench::StorageService> some_storage_service;
[...]
file_registry->addEntry(wrench::FileLocation::LOCATION(some_storage_service, some_file));
file_registry->removeEntry(wrench::FileLocation::LOCATION(some_storage_service, some_file));
The wrench::FileLocation
class is a convenient abstraction for a
file that is available at some storage service (with optionally a directory
path at that service).
Retrieving all entries for a given file is done as follows:
std::shared_ptr<wrench::FileRegistryService> file_registry;
std::shared_ptr<wrench::DataFile> some_file;
[...]
std::set<std::shared_ptr<wrench::FileLocation>> entries;
entries = file_registry->lookupEntry(some_file);
If a network proximity service is running, it is possible to retrieve
entries for a file sorted by non-decreasing proximity from some
reference host. Returned entries are stored in a (sorted) std::map
where the keys are network distances to the reference host. For
instance:
std::shared_ptr<wrench::FileRegistryService> file_registry;
std::shared_ptr<wrench::DataFile> some_file;
std::shared_ptr<wrench::NetworkProximityService> np_service;
[...]
auto entries = fr_service->lookupEntry(some_file, "ReferenceHost", np_service);
See the documentation of wrench::FileRegistryService
for more API member functions.
Interacting with network proximity services
Querying a network proximity service is straightforward. For instance, to obtain a measure of the network distance between hosts “Host1” and “Host2”, one simply does:
std::shared_ptr<wrench::NetworkProximityService> np_service;
std::pair<double,double> distance = np_service->getHostPairDistance(std::make_pair("Host1", "Host2"));
This distance corresponds to half the round-trip-time, in seconds, between the two hosts. The second value of the pair is the timestamp of the oldest measurement uses to compute the proximity value. If the service is configured to use the Vivaldi coordinate-based system, as in our example above, this distance is actually derived from network coordinates, as computed by the Vivaldi algorithm. In this case, one can actually ask for these coordinates for any given host:
std::pair<std::pair<double,double>, double> coords = np_service->getHostCoordinate("Host1");
See the documentation of wrench::NetworkProximityService
for more API member functions.
C) Workflow execution events
Because the execution controller performs asynchronous operations, it
needs to wait for and re-act to events. This is done by calling the
wrench::ExecutionController::waitForAndProcessNextEvent()
member
function implemented by the base wrench::ExecutionController
class.
A call to this member function blocks until some event occurs and then
calls a callback member function. The possible event classes all derive
from the wrench::ExecutionEvent
class, and an execution controller
can override the callback member function for each possible event (the
default member function does nothing but print some log message). These
overridable callback member functions are:
wrench::ExecutionController::processEventCompoundJobCompletion()
: react to a compound job completionwrench::ExecutionController::processEventCompoundJobFailure()
: react to a compound job failurewrench::ExecutionController::processEventStandardJobCompletion()
: react to a standard job completionwrench::ExecutionController::processEventStandardJobFailure()
: react to a standard job failurewrench::ExecutionController::processEventPilotJobStart()
: react to a pilot job beginning executionwrench::ExecutionController::processEventPilotJobExpiration()
: react to a pilot job expirationwrench::ExecutionController::processEventFileCopyCompletion()
: react to a file copy completionwrench::ExecutionController::processEventFileCopyFailure()
: react to a file copy failure
Each member function above takes in an event object as parameter. In the
case of failure, the event includes a wrench::FailureCause
object,
which can be accessed to analyze (or just display) the root cause of the
failure.
Consider the execution controller in
examples/workflow_api/basic-examples/bare-metal-bag-of-tasks/TwoTasksAtATimeWMS.cpp
.
At each each iteration of its main loop it does:
// Submit some standard job to some compute service
job_manager->submitJob(...);
// Wait for and process next event
this->waitForAndProcessNextEvent();
In this simple example, only one of two events could occur at this point: a standard job completion or a standard job failure. As a result, this execution controller overrides the two corresponding member functions as follows:
void TwoTasksAtATimeWMS::processEventStandardJobCompletion(
std::shared_ptr<StandardJobCompletedEvent> event) {
// Retrieve the job that this event is for
auto job = event->standard_job;
// Print some message for each task in the job
for (auto const &task : job->getTasks()) {
std::cerr << "Notified that a standard job has completed task " << task->getID() << std::endl;
}
}
void TwoTasksAtATimeWMS::processEventStandardJobFailure(
std::shared_ptr<StandardJobFailedEvent> event) {
// Retrieve the job that this event is for
auto job = event->standard_job;
std::cerr << "Notified that a standard job has failed (failure cause: ";
std::cerr << event->failure_cause->toString() << ")" << std::endl;
// Print some message for each task in the job if it has failed
std::cerr << "As a result, the following tasks have failed:";
for (auto const &task : job->getTasks()) {
if (task->getState != WorkflowTask::COMPLETE) {
std::cerr << " - " << task->getID() << std::endl;
}
}
}
You may note some difference between the above code and that in
examples/workflow_api/basic-examples/bare-metal-bag-of-tasks/TwoTasksAtATimeWMS.cpp
.
This is for clarity purposes, and especially because we have not yet
explained how WRENCH does message logging. See an upcoming section
about logging.
While the above callbacks are convenient, sometimes it is desirable to
do things more manually. That is, wait for an event and then process it
in the code of the main loop of the execution controller rather than in
a callback member function. This is done by calling the
wrench::waitForNextEvent()
member function. For instance, the
execution controller in
examples/workflow_api/basic-examples/bare-metal-data-movement/DataMovementWMS.cpp
does it as:
// Initiate an asynchronous file copy
data_movement_manager->initiateAsynchronousFileCopy(...);
// Wait for an event
auto event = this->waitForNextEvent();
//Process the event
if (auto file_copy_completion_event = std::dynamic_pointer_cast<wrench::FileCopyCompletedEvent>(event)) {
std::cerr << "Notified of a file copy completion for file ";
std::cerr << file_copy_completion_event->file->getID()<< "as expected" << std::endl;
} else {
throw std::runtime_error("Unexpected event (" + event->toString() + ")");}
}
Exceptions
Most member functions in the WRENCH Developer API throw exceptions. In fact, most of the code fragments above should be in try-catch clauses, catching these exceptions.
Some exceptions correspond to failures during the simulated workflow
executions (i.e., errors that would occur in a real-world execution and
are thus part of the simulation). Each such exception contains a
wrench::FailureCause
object, which can be accessed to understand the
root cause of the execution failure. Other exceptions (e.g.,
std::invalid_arguments
, std::runtime_error
) are thrown as well,
which are used for detecting misuses of the WRENCH API or internal
WRENCH errors.
Finding information and interacting with hardware resources
The wrench::Simulation
class provides many member functions to
discover information about the (simulated) hardware platform and
interact with it. It also provides other useful information about the
simulation itself, such as the current simulation date. Some of these
member functions are static, but others are not. The
wrench::ExecutionController
class includes a simulation
object.
Thus, the execution controller can call member functions on the
this->simulation
object. For instance, this fragment of code shows
how an execution controller can figure out the current simulated date
and then check that a host exists (given a hostname) and, if so, set its
pstate
(power state) to the highest possible setting.
auto now = wrench::Simulation::getCurrentSimulatedDate();
if (wrench::Simulation::doesHostExist("SomeHost")) {
this->simulation->setPstate("SomeHost", wrench::Simulation::getNumberofPstates("SomeHost")-1);
}
See the documentation of the wrench::Simulation
class for all
details. Specifically regarding host pstates, see the example execution
controller in
examples/workflow_api/basic-examples/cloud-bag-of-tasks-energy/TwoTasksAtATimeCloudWMS.cpp
,
which interacts with host pstates (and the
examples/workflow_api/basic-examples/cloud-bag-of-tasks-energy/four_hosts_energy.xml
platform description file which defines pstates).
Logging
It is typically desirable for the execution controller to print log
output to the terminal. This is easily accomplished using the
wrench::WRENCH_INFO()
, wrench::WRENCH_DEBUG()
, and
wrench::WRENCH_WARN()
macros, which are used just like C’s
printf()
. Each of these macros corresponds to a different logging
level in SimGrid. See the SimGrid logging
documentation for all
details.
Furthermore, one can change the color of the log messages with the
wrench::TerminalOutput::setThisProcessLoggingColor()
member
function, which takes as parameter a color specification:
When inspecting the code of the execution controllers in the example
simulators you will find many examples of calls to
wrench::WRENCH_INFO()
. The logging is per .cpp
file, each of
which corresponds to a declared logging category. For instance, in
examples/workflow_api/basic-examples/batch-bag-of-tasks/TwoTasksAtATimeBatchWMS.cpp
,
you will find the typical pattern:
// Define a log category name for this file
WRENCH_LOG_CATEGORY(custom_wms, "Log category for TwoTasksAtATimeBatchWMS");
[...]
int TwoTasksAtATimeBatchWMS::main() {
// Set the logging color to green
TerminalOutput::setThisProcessLoggingColor(TerminalOutput::COLOR_GREEN);
[...]
// Print an info-level message, using printf-like format
WRENCH_INFO("Submitting the job, asking for %s %s-core nodes for %s seconds",
service_specific_arguments["-N"].c_str(),
service_specific_arguments["-c"].c_str(),
service_specific_arguments["-t"].c_str());
[...]
// Print a last info-level message
WRENCH_INFO("Workflow execution complete");
return 0;
}
The name of the logging category, in this case custom_wms
, can then
be passed to the --log
command-line argument. For instance, invoking
the simulator with additional argument
--log=custom_wms.threshold=info
will make it so that only those
WRENCH_INFO
statements in TwoTasksAtATimeBatchWMS.cpp
will be
printed (in green!).