- decided to allow creating empty lib::Several;
no need to be overly rigid in this point,
since it is move-assignable anyway...
- populate with enough elements to provoke several reallocations
with copying over the existing elements
- precisely calculate and verify the expected allocation size
- verify the use-count due to dedicated allocator instances
being embedded into both the builder and hidden in the deleter
- move-assign data
- all checksums go to zero at end
The setup for `ArrayBucket` is special, insofar it shell de-allocate itself,
which creates the danger of re-entrant calls, or to the contrary, the danger
to invoke this clean-up function without actually invoking the destructor.
These problems become relevant once the destructor function itself is statefull,
as is the case when embedding a non-trivial, instance bound allocator
to be used for the clean-up work. Using the new `lib::TrackingAllocator`
highlighted this potential problem, since the allocator maintains a use-count.
Thus I decided to move the »destruction mechanics« one level down into
a dedicated and well encapsulated base class; invoking ArrayBucket's destructor
thereby becomes the only way to trigger the clean-up, and even ElementFactory::destroy()
can now safely check if the destructor was already invoked, and otherwise
re-invoke itself through this embedded destructor function. Moreover,
as an additional safety measure, the actual destructor function is now
moved into the local stack frame of the object's destructor call, removing
any possibility for the de-allocation to interfere with the destructor
invokation itself
part of the observed deviation stems form bugs in logging and checksum calculation;
but there seems to be a real problem hidden in the allocator usage of the
new component, since the use-cnt of the handle does not drop to zero
While there might be the possibility to use the magic of the standard library,
it seems prudent rather to handle this insidious problem explicitly,
to make clear what is going on here.
To allow for such explicit alignment handling, I have now changed the
scheme of the storage definition; the actual buffer now starts ''behind''
the `ArrayBucket<I>` object, which thereby becomes a metadata managing header.
__To summarise the problem__: since we are maintaining a dynamically sized buffer,
and since we do not want to expose the actual element type through the
front-end object, we're necessarily bound to perform a raw-memory allocation.
This is denoted in bytes, and thus the allocator can no longer manage
the proper alignment automatically. Rather, we get a storage buffer with
just ''some accidental'' alignment, and we must care to request a sufficient
overhead to be able to shift the actual storage area forward to the next
proper alignment boundary. Obviously this also implies that we must
store this individual padding adjustment somewhere in the metadata,
in order to be able to report the correct size of the block later
on de-allocation.
The solution implemented thus far turns out to be not sufficient
for ''over-aligned-data'', as the raw-allocator can not perform the
''magic work'' because we're exposing only `std::byte` data.
This adaptor works in concert with the generic allocator
building blocks (prospective ''Concepts'') and automatically
registers a either static or dynamic back-link to the factory
for clean-up.
Use this wrapper fore more in-depth test of the new `TrackingAllocator`
and verify proper behaviour through the `EventLog`
- ability to verify a hash-checksum
- ability to watch number of allocations and allotted bytes
- using either a common global pool or a separate dedicated pool
- log all operations into a common `EventLog` instance
- front-end adaptors for use as C++ custom allocator
...these features are now used quite regularly,
and so a dedicated documentation test seems indicated.
Actually my intention is to add a tracking allocator to these test helpers
(and then to use that to verify the custom allocator usage of `lib::Several`)
Phew... this was a tough one — and not sure yet if this even remotely works...
Anyway, the `lib::SeveralBuilder` is already prepared for collaboration with a
custom allocator, since it delegates all memory handling through a base policy,
which in turn relies on std::allocator_traits.
The challenge however is to find a way...
* to make this clear and easy to use
* to expose an extension point for specific tweaks
* and to make all this work without excessive header cross dependencies
This is a low-level interface to allow changing the size of
the currently latest allocation in `AllocationCluster`; a client
aware of this capability can perform a real »in-place re-alloc«,
assuming the very specific usage constraints can be met.
`lib::Several<X>` will use this feature when attached to an
`AllocationCluster`; with this special setup, an previously
unknown number of non-copyable objects can be built without
wasting any storage, as long as the storage reserve in the
current extent of the `AllocationCluster` is sufficient.
...use some pointer arithmetic for this test to verify
some important cases of object placement empirically.
Note: there is possibly a very special problematic case
when ''over aligned objects'' are not placed in accordance
to their alignment requirements. Fixing this problem would
be non-trivial, and thus I have only left a note in #1204
...including the interesting cases where objects are relocated
and the element spread is changed. With the help of the checksum
feature built into the test-dummy objects, the properly balanced
invocation of constructors can be demonstrated
PS: for historical context...
Last week the "Big F**cking Rocket" successfully performed the
test flight 4; both booster and Starship made it back to the
water surface and performed a soft splash-down after decelerating
to speed zero. The Starship was even able to maintain control
in spite of quite some heat damage on the steering flaps.
Yes ... all techies around the world are thrilled...
- spread change now retains the nominal element reserve
- `capacity()` and `capReserve()` now exposed on the builder API
- factor out the handling check safety functions
- rewrite the `resize()` builder function to be more generic
__Test now covers__ example with trivial data type, which can
indeed be resized and allows to grow buffer on-the fly without
requiring any knowledge of the actual type (due to using `memmove`)
building on the preceding analysis, we can now demonstrate that
the container is initially able to grow, but looses this capability
after accepting one element of unknown subclass type...
`lib::Several` is designed to be highly adaptable, allowing for
several quite distinct usage styles. On the downside, this requires
to perform some checks at runtime only, since the ability to handle
some element depends on specific circumstances.
This is a notable difference to `std::vector`, which is simply not capable
of handling ''non-copyable'' types, even if given an up-front memory reservation.
The last test case provided with the previous changeset did not trigger
an exception, but closer investigation revealed that this is correct,
since in this specific situation the container can accept this object type,
thereby just loosing the ability to move-relocate further objects.
A slightly re-arranged test scenario can be used to demonstrate this fine point.
- the test-dummy objects need a `noexcept` move ctor
- **bug** here: need an explicit check to prevent other types
than the known element type from ''sneaking in''
The `SeveralBuilder` is very flexible with respect to added elements,
but it will investigate the provided type information and reject any
further build operation that can not be carried out safely.
...turns out that we must ensure to pass a plain "object" type
to the standard allocator framework (no const, no references).
Here, ''object in C++ terminology'' means a scalar or record type,
but no functor, no references and no void,
Consider what (not) to support.
Notably I decided ''not to support'' moving out of an iterator,
since doing so would contradict the fundamental assumptions of
the »Lumiera Forward Iterator« Concept.
Start verifying some variations of element placement,
still focussing on the simple cases
Parts of the decision logic for element handling was packaged
as separate »strategy« class — but this turned out to be neither
a real abstraction, nor configurable in any way. Thus it is better
to simplify the structure and turn these type predicates into simple
private member functions of the SeveralBuilder itself
...and the nice thing is, the recently built `IterIndex` iteration wrapper
covers this functionality right away, simply because `lib::Several`
is a generic container with subscript operator.
...passes the simplest unit test
* create a Several<int>
* populate from `std::initializer_list`
* random-access to elements
''next step would be to implement iteration''
Some decisions
- use a single template with policy base
- population via separate builder class
- implemented similar to vector (start/end)
- but able to hold larger (subclass) objects
- basically works out-of-the-box now
- the hard wired fixed Extent size is a serious limitation
- however, this is not the intended primary use, rather complementary
...this is an important detail: quite commonly, a custom allocator
is actually implemented as monostate, to avoid bloating every client container
with a backlink pointer; by inheriting the `StdFactory` adapter from the
allocator, the empty-base optimisation can be exploited.
In the standard case thus LinkedElements is the same size as a single
pointer, which is already exploited at several places in the code base.
Notably `AllocationCluster` uses a »virtual overlay« to dress-up the
position pointer as `LinkedElements`, allowing to delegate most of the
administration and memory management to existing and verified code.
With this adjustments, `LinkedElements` pass the tests again
and the rework of `AllocationCluster` is considered complete.
This is the first validation of the new design:
the policy to take ownership can be reimplemented simply
by delegating to the adaptor for a C++ standard allocator
...what I've implemented yesterday is effectively the same functionality
as provided automatically by the C++ object system when using a virtual destructor.
Thus a much cleaner solution is to turn `Destructor` into a interface
and let C++ do all the hard work.
Verified in test: works as intended
This is the first draft, implementing the invocation explicitly
through a trampoline function. While it seems to work,
the formulation can probably be simplified....
- rather accept hard-wired limits than making the implementation excessively generic
- by exploiting the layout, the administrative overhead can be reduced significantly
- the trick with the "virtual managment overlay" allows to hand-off most of the
clean-up work to C++ destructor invocation
- it is important to verify these low-level arrangements explicitly by unit-test
...due to the decision to use a much simpler allocation scheme
to increase probability for actual savings, after switching the API
and removing all trading related aspects, a lot of further code is obsoleted
Notably this raises the difficult question,
whether to ensure **invocation of destructors**.
Not invoking dtors ''breaks one of the most fundamental contracts''
of the C++ language — yet the infrastructure to invoke dtors in such
a heterogeneous cluster of allocations creates a hugely significant
overhead and is bound to poison the caches (objects to be deallocated
typically sit in cold memory pages).
What makes this decision especially daunting is the fact that the
low-level-Model can be expected to be one of the largest systemic
data structures (letting aside the media buffers).
I am leaning towards a compromise: turn down this decision
towards the user of the `AllocationCluster`
At the time of the initial design attempts, I naively created a
classic interface to describe an fixed container allocated ''elsewhere.''
Meanwhile the C++ language has evolved and this whole idea looks
much more as if it could be a ''Concept'' (C++20). Moreover, having
several implementations of such a container interface is deemed inadequate,
since it would necessitate ''at least two indirections'' — while
going the Concept + Template route would allow to work without any
indirection, given our current understanding that the `ProcNode` itself
is ''not an interface'' — rather a building block.
- the starting point is the idea to build a dedicated ''turnout system''
- `StateAdapter`, `BuffTable` ⟶ `FeedManifold` and _Invocation_ will be fused
- actually, the `TurnoutSystem` will be ''pulled'' and orchestrate the invocation
- the structure is assumed to be recursive
The essence of the Node-Invocation, as developed 2009 / 2011 remains intact,
yet it will be organised along a clearer structure
Facing quite some difficulties here, since there are (at least)
two abandoned past efforts towards building a render node network
in the code base; the structure and architecture decisions from these
previous attempts seem largely valid still, yet on a technical level,
the style of construction evolved considerably in the meantime. Moreover,
these old fragments of code, written during the early stages of the
project, were lacking clear goals and anchor points at places;
the situation is quite different now in this respect.
Sticking to well proven practice, the rework will be driven by a test setup,
and will progress over three steps with increasing levels of integration.
The initial effort of building a Scheduler can now be **considered complete**
Reaching this milestone required considerable time and effort, including
an extended series of tests to weld out obvious design and implementation flaws.
While the assessment of the new Scheduler's limitation and traits is ''far from complete,''
some basic achievements could be confirmed through this extended testing effort:
* the Scheduler is able to follow a given schedule effectively,
until close up to the load limit
* the ''stochastic load management'' causes some latency on isolated events,
in the order of magnitude < 5ms
* the Scheduler is susceptible to degradation through Contention
* as mitigation, the Scheduler prefers to reduce capacity in such a situation
* operating the Scheduler effectively thus requires a minimum job size of 2ms
* the ability for sustained operation under full nominal load has been confirmed
by performing **test sequences with over 80 seconds**
* beyond the mentioned latency (<5ms) and a typical turnaround of 100µs per job
(for debug builds), **no further significant overhead** was found.
Design, Implementation and Testing were documented extensively in the [https://lumiera.org/wiki/renderengine.html#Scheduler%20SchedulerProcessing%20SchedulerTest%20SchedulerWorker%20SchedulerMemory%20RenderActivity%20JobPlanningPipeline%20PlayProcess%20Rendering »TiddlyWiki« #Scheduler]
This test completes the stress-testing effort
and summarises the findings
* Scheduler performs within relevant parameter range without significant overhead
* Scheduler can operate with full load in stable state, with 100% correct result
The behaviour seems consistent and the schedule breaks at the expected point.
At first sight, concurrency seems slightly to low; detailed investigation
however shows that this is due to the structure of the load graph,
and in fact the run time comes close to optimal values.
the `BreakingPoint` tool conducts a binary search to find the ''stress factor''
where a given schedule breaks. There are some known deviations related to the
measurement setup, which unfortunately impact the interpretation of the
''stress factor'' scale. Earlier, an attempt was made, to watch those factors
empirically and work a ''form factor'' into the ''effective stress factor''
used to guide this measurement method.
Closer investigation with extended and elastic load patters now revealed
a strong tendency of the Scheduler to scale down the work resources when not
fully loaded. This may be mistaken by the above mentioned adjustments as a sign
of a structural limiation of the possible concurrency.
Thus, as a mitigation, those adjustments are now only performed at the
beginning of the measurement series, and also only when the stress factor
is high (implying that the scheduler is actually overloaded and thus has
no incentive for scaling down).
These observations indicate that the »Breaking Point« search must be taken
with a grain of salt: Especially when the test load does ''not'' contain
a high degree of inter dependencies, it will be ''stretched elastically''
rather than outright broken. And under such circumstances, this measurement
actually gauges the Scheduler's ability to comply to an established
load and computation goal.
...this seems to be the last topic for this investigation of Scheduler behaviour;
the goal is to demonstrate readiness for stable-state operation over an extended period of time
