|Version 4 (modified by ezyang, 4 years ago) (diff)|
This page describes a proposed resource limits capabilities for GHC. The idea is to give users the ability to create and utilize cost-centres inside programs (so that cost-centres do not necessarily have to be tied to source code locations), and then provide in-program access to heap census and other information. The end result is the ability to impose resource limits on space usage, as well as a side-effect of more precise profiling.
type CostCentreStack type CostCentre type Listener ccsDynamic :: CostCentreStack newCostCentre :: IO CostCentre pushCostCentre :: CostCentreStack -> CostCentre -> IO CostCentreStack setCostCentreStack :: CostCentreStack -> a -> IO () listenCostCentreStack :: CostCentreStack -> Int -> IO () -> IO Listener unlistenCostCentreStack :: Listener -> IO ()
The general usage of this API goes like:
f n = let xs = [1..n::Integer] in sum xs * product xs main = do m <- newEmptyMVar forkIO $ do x <- newCostCentreStack tid <- myThreadId l <- listenCostCentreStack x 2000 (putStrLn "Too much memory is being used" >> killThread tid) let thunk = f 20000 setCostCentreStack x thunk evaluate thunk unlistenCostCentreStack l putMVar m () takeMVar m
Another use-case is more fine-grained SCCs based on runtime properties, not source-level features.
I am planning on providing semantics, based on GHC’s current profiling semantics.
Some points to bikeshed:
- Naming: CostCentreStack/CostCentre or CCS/CC?
- Provide withCostCentreStack :: CostCentreStack -> a -> a which is simply a IND_PERM with the CCS set? In my testing, this had to be done very carefully, because if the inner value was a thunk, then this is a no-op
- Provide withCostCentre :: CostCentre -> (a -> b) -> (a -> b) which provides the equivalent of function entry (adds the CC to what ever the CCCS is). I don't have a good case for complicated cost-centre stacks and listeners and have not implemented it yet.
- Should listeners automatically deregister themselves when their event triggers? Active listeners are considered roots so they must be handled with care to avoid leaks.
- Another useful thing to measure, besides residency, is overall allocation. Provide an API for that too.
- Instead of the current interface, we could publish STM variables which are updated by the GC; listening is then just an ordinary STM transaction. This might be tricky to implement.
- A useful API would be one to just query what the residence of some cost centre is.
If we implement something like withCostCentre, we also need to adjust Core slightly. There are two choices:
- Modify Tick so that it can take an optional argument (cost-centre); modify the type-checker appropriately. This is not so great because we’re making an already ad hoc addition to the Core language even more complicated, even if the extra typing rules are not that complicated.
- Add a new Tickish type, which has no impact on code-generation but still appropriately modifies optimization behavior, and introduce new prim-ops to actually set cost-centers.
Note that ordinary (source-generated) ticks could also be converted into prim-ops; but while this sounds appealing, it gets complicated because true source-level SCCs need to be statically initialized (so the runtime system knows about them and can assign an integer ID to them), and moving them into hard-wired constants would complicate the late-stage STG passes. (It's possible, but probably loses out as far as overall complexity goes.)
- Listener is a new garbage collected object; we expect it can be implemented as a simple PRIM using techniques similar to StgMVarTSOQueue.
- Checks for listeners occur during heap census; you'll need to pass the -hc flag for this machinery to do anything. See also #7751 which will dramatically improve performance.
This is obviously fine to support if you are in IO; however, the situation is dicey when considering pure code; an expression currentCostCentre :: CostCentre is not referentially transparent. Rather, we want some semantics like implicit parameters, but no one really likes implicit parameters. Maybe it’s better just to note support it (and let someone unsafePerformIO if they reaaally care.)
Interaction with traditional profiling
Resource limits must be compiled with -prof; we’d like to treat profiling as semantics preserving but resource limits are anything but. In the long term, it is probably desirable to consider these distinctive systems which happen to share a common mechanism. As a first draft, we don’t intend on supporting profiling and resource limits simultaneously; the dynamic SCC machinery can be used for enhanced profiling or for marking resource limits, but not both. It may be possible to extend the resource limit machinery to handle “superfluous” cost-centres, but this would be more complicated and costly, since a costs will now be spattered over many CostCentre objects and need to be recombined. Currently, the profiling machinery can perform this calculation, but only calculates inherited resource usage at the very end, so this could be expensive.
Since non-dynamic SCCs can interfere with accurate cost attribution, we add a new flag -fprof-drop which drops all SCC pragmas.
One of the most important intended use-cases of resource limits is when you are rapidly loading and unloading large amounts of untrusted code (think http://tryhaskell.org/). So an important thing to get right is avoiding long term memory leakage, either from leftover objects from the untrusted code or related infrastructure.
On the unloading code front, one technique that could be employed is to replace all third-party closures with “error” frames upon unloading. Similar techniques are already being employed in GHC, and it is semantically sound even if another thread has already witnessed the full value of the data structure: one can imagine some supervisor process sending an asynchronous exception when some unloaded data is accessed. (XXX this may have bad interactions with mask and uninterruptibleMask).
On the cost centre front, the runtime currently assumes that cost centres are permanent and never deallocated. One technique for deallocating a cost-centre goes as follows. We first allocate a distinguished “catch-all” cost-centre which tracks all deallocated cost centres. When we would like to deallocate a cost centre, we mark the cost centre as killed, and upon the next major garbage collection, we look at the cost-centres pointed to by all of the heap objects and rewrite them if they correspond to a killed cost-centre. We also donate all of the cost-centre’s statistics to the catch-all. It is also necessary to rewrite any in-Haskell references to the cost-centre (so we need a new infotable to mark these references.) Once this is done, we’ve removed all references to the cost-centre and it can be dropped. (This is not quite true; CC_LIST and any cost-centre stacks also have to be updated.)
Callback triple fault
Finalizer could trigger a new finalizer, ad infinitum. Maybe we don't have to do anything.