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Resource Limits for Haskell: PLDI'14 Artifact Evaluation

Warning: Since the PLDI artifact evaluation, development has progressed further and some bugs have been fixed. The VM image has not been updated for historical interest, but be aware!

This page describes the set of GHC patches and support libraries, as well as evaluation code, for the paper Resource Limits for Haskell. You can access our artifact via this 7 GB VM image (Warning: this is an SCS lab hosted machine. We have turned off logging though!). The VM is a minimal Arch Linux distribution with a complete build of GHC and associated libraries. There is a user 'lambda' with password 'rlimits'. (The root password is also the same).

lambda's home directory contains the following:

  • pldi14-rlimits-aec contains instructions on how to replicate all of the measurements seen in the evaluation section of the paper. There are three subfolders, and each contains a README with further instructions. You can also view the READMEs by browsing this Git repository.

  • ghc contains the build-tree of our patched version of GHC 7.8 with support for resource limits. It has been installed to /usr/local, so if you type ghc --version you will be using our copy of GHC. You can view the patchset that was applied using git log, but to run our software, you don't have to interact with this directory.

  • rlimits contains the primary auxiliary library support for resource limits, including the information-flow control monad Control.Monad.RLimits described in Section 3 of the paper. As with ghc, the library has already been installed, so you don't have to interact with this directory, except to look at the source code. This code is available at


This tutorial assumes some familiarity with Haskell.

Raw resource limits

A good start is to ensure that resource limits has been installed properly. Here is a short file 1.hs which imports our resource limits module.

-- 1.hs
import Control.RLimits

main = putStrLn "Hello World!"

You can build the file using ghc -O --make 1.hs, which results in an executable named 1.

Control.RLimits provides the low-level access to the resource-limits API as described in section 2. We can write a short program which creates a resource container (newRC), switches into it (withRC), and exhausts its space resources (for synthetic examples, this can be a little tricky; more on this later):

-- 2.hs
import Control.RLimits
import Control.Exception

main :: IO ()

main = do
    parent_rc <- getCurrentRC
    rc <- newRC 200 parent_rc
    withRC rc (loop [1])

loop n = do
    _ <- evaluate (length n)
    loop (n ++ n)

When you run this program, it exits with a heap overflow, as the loop repeatedly doubles the size of a list.

Differently from the paper, newRC accepts a number of blocks to be allocated to the resource container. The size of a block in GHC is 4 KB. You also have to provide a parent resource container to associate with the container; at the moment, this is only used internally, and has no effect on the semantics of resource containers.

When constructing synthetic examples, some care should be taken: the most common reasons for a limit to not be hit when you expect it to are (1) the program is time-bound, not space-bound (check top), and (2) the costs are not being charged to the container you think they are being charged to. These difficulties are closely related to the difficulty of performing microbenchmarks in Haskell: it can be quite difficult to tell when a computation is happening, and our paper does not introduce any new special forms to Haskell to make this easier. Usually, computation that is done by the IO monad will be attributed properly, but you still need to be careful. Here is a slightly tweaked version of the previous example:

loop n = do
    evaluate (length n)
    loop (n ++ n)

When compiled without optimizations, the cost of this loop is charged to the top-level, and not the most recently allocated resource container. What happened? It turns out these two different uses of do-notation compile differently: in the second case, the unoptimized Haskell program builds a tree of IO actions, before actually running the actions in the withRC. If you need to run a pure computation inside a container, use withRC1.

Something else you can do (not described in the paper) is the ability to receive callbacks when certain thresholds are met. This can be done with the listenRC function:

-- 3.hs
import Control.RLimits
import Control.Exception

main :: IO ()

main = do
    parent_rc <- getCurrentRC
    rc <- newRC 200 parent_rc
    listenRC rc 100 (putStrLn "Half way gone")
    withRC rc $ loop [1]

loop n = do
    _ <- evaluate (length n)
    loop (n ++ n)

Listeners are useful for applying soft limits, where a thread can be issued an advisory that it is running out of space before it hits a hard exception.

Resource limits monad

Using the raw resource limits API requires quite a bit of care,

We offer a resource limits monad CM, in Control.Monad.RLimits, for keeping track of what pointers threads have to various resource containers. You can start a computation in the CM monad using startCM:

-- 4.hs
import Control.Monad.RLimits

croak :: String -> CM ()
croak = liftIOTCB . putStrLn

main = startCM $ do
    croak "Hello"

The most important operation of the RC monad is rcFork, which is the mechanism by which you can enforce isolation between containers. In the following example, notice that while both access to the killed container fail, the main thread is able to proceed (and print fine) independent of the failure of the forked thread.

import Control.Monad.RLimits

croak :: String -> CM ()
croak = liftIOTCB . putStrLn

main = startCM $ do
    c <- getCurrentLabel
    rc <- newRC 100
    rcKill rc
    rcFork (ss rc `su` c) (withRC rc (croak "1"))
    croak "fine"
    withRC rc (croak "2")

What is the first argument to rcFork? This argument specifies what resource containers the thread may access (read as "the singleton set (ss) containing rc unioned (su) with the current set of accessible containers"). This same format is also used for RCRef and RCLMVar, which means of cross-thread communication.

For a full example, check out the prisoners subfolder in the evaluation folder.

Known infelicities

This resource limits system has been most strenously tested on a quick, single-threaded build, and the authors do not claim to have squashed all bugs, especially in other configurations.

Features which are known not to work:

  • 32-bit architectures

  • GHCi

  • Compacting garbage collection

Known bugs in the VM (all of these bugs have since been fixed in the Git repository, but I haven't updated the VM with the new software):

  • We leak a small amount of memory for every resource container allocated.

  • The raw resource limits interface has an unsafe function killRC (distinct from the killRC in the monadic interface). This function is advisory: when a container is killed, the user makes a promise that the container will no longer be used with withRC; behavior is undefined otherwise. We could probably make this interface a little less pointy.

  • Our HEAP_ALLOCED patch does not work with SplitObjs; thus be sure to compile GHC with that setting turned off, and to not use --split-objs when compiling libraries. See also:


Artifact evaluation for PLDI'14



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