To make an executable program, the GHC system compiles your code and then links it with a non-trivial runtime system (RTS), which handles storage management, thread scheduling, profiling, and so on.
The RTS has a lot of options to control its behaviour. For example, you can change the context-switch interval, the default size of the heap, and enable heap profiling. These options can be passed to the runtime system in a variety of different ways; the next section (Setting RTS options) describes the various methods, and the following sections describe the RTS options themselves.
There are four ways to set RTS options:
+RTS ... -RTS, when running the program (Setting RTS options on the command line)
-with-rtsopts(Setting RTS options at compile time)
GHCRTS(Setting RTS options with the GHCRTS environment variable)
When your Haskell program starts up, the RTS extracts command-line arguments bracketed between
-RTS as its own. For example:
$ ghc prog.hs -rtsopts [1 of 1] Compiling Main ( prog.hs, prog.o ) Linking prog ... $ ./prog -f +RTS -H32m -S -RTS -h foo bar
The RTS will snaffle
-H32m -S for itself, and the remaining arguments
-f -h foo bar will be available to your program if/when it calls
-RTS option is required if the runtime-system options extend to the end of the command line, as in this example:
% hls -ltr /usr/etc +RTS -A5m
If you absolutely positively want all the rest of the options in a command line to go to the program (and not the RTS), use a
As always, for RTS options that take ⟨size⟩s: If the last character of ⟨size⟩ is a K or k, multiply by 1000; if an M or m, by 1,000,000; if a G or G, by 1,000,000,000. (And any wraparound in the counters is your fault!)
-?RTS option option will print out the RTS options actually available in your program (which vary, depending on how you compiled).
Since GHC is itself compiled by GHC, you can change RTS options in the compiler using the normal
+RTS ... -RTS combination. For instance, to set the maximum heap size for a compilation to 128M, you would add
+RTS -M128m -RTS to the command line.
GHC lets you change the default RTS options for a program at compile time, using the
-with-rtsopts flag (Options affecting linking). A common use for this is to give your program a default heap and/or stack size that is greater than the default. For example, to set
-H128m -K64m, link with
-rtsopts flag is set to something other than
none when linking, RTS options are also taken from the environment variable
GHCRTS. For example, to set the maximum heap size to 2G for all GHC-compiled programs (using an
GHCRTS='-M2G' export GHCRTS
RTS options taken from the
GHCRTS environment variable can be overridden by options given on the command line.
Setting something like
GHCRTS=-M2G in your environment is a handy way to avoid Haskell programs growing beyond the real memory in your machine, which is easy to do by accident and can cause the machine to slow to a crawl until the OS decides to kill the process (and you hope it kills the right one).
GHC lets you exercise rudimentary control over certain RTS settings for any given program, by compiling in a “hook” that is called by the run-time system. The RTS contains stub definitions for these hooks, but by writing your own version and linking it on the GHC command line, you can override the defaults.
Owing to the vagaries of DLL linking, these hooks don’t work under Windows when the program is built dynamically.
You can change the messages printed when the runtime system “blows up,” e.g., on stack overflow. The hooks for these are as follows:
void OutOfHeapHook (unsigned long, unsigned long)
The heap-overflow message.
void StackOverflowHook (long int)
The stack-overflow message.
void MallocFailHook (long int)
The message printed if
Furthermore GHC lets you specify the way event log data (
-l) is written through a custom
EventLogWriter. This is optional.
bool writeEventLog(void *eventlog, size_t eventlog_size)
Hands buffered event log data to your event log writer. Required for a custom
Flush buffers (if any) of your custom
EventLogWriter. This is optional.
Called when event logging is about to stop. This is optional.
Sets the interval that the RTS clock ticks at. The runtime uses a single timer signal to count ticks; this timer signal is used to control the context switch timer (Using Concurrent Haskell) and the heap profiling timer RTS options for heap profiling. Also, the time profiler uses the RTS timer signal directly to record time profiling samples.
Normally, setting the
-V option directly is not necessary: the resolution of the RTS timer is adjusted automatically if a short interval is requested with the
-i options. However, setting
-V is required in order to increase the resolution of the time profiler.
Using a value of zero disables the RTS clock completely, and has the effect of disabling timers that depend on it: the context switch timer and the heap profiling timer. Context switches will still happen, but deterministically and at a rate much faster than normal. Disabling the interval timer is useful for debugging, because it eliminates a source of non-determinism at runtime.
If yes (the default), the RTS installs signal handlers to catch things like ctrl-C. This option is primarily useful for when you are using the Haskell code as a DLL, and want to set your own signal handlers.
Note that even with
--install-signal-handlers=no, the RTS interval timer signal is still enabled. The timer signal is either SIGVTALRM or SIGALRM, depending on the RTS configuration and OS capabilities. To disable the timer signal, use the
-V0 RTS option (see above).
This option is for working around memory allocation problems only. Do not use unless GHCi fails with a message like “
failed to mmap() memory below 2Gb”. If you need to use this option to get GHCi working on your machine, please file a bug.
On 64-bit machines, the RTS needs to allocate memory in the low 2Gb of the address space. Support for this across different operating systems is patchy, and sometimes fails. This option is there to give the RTS a hint about where it should be able to allocate memory in the low 2Gb of the address space. For example,
+RTS -xm20000000 -RTS would hint that the RTS should allocate starting at the 0.5Gb mark. The default is to use the OS’s built-in support for allocating memory in the low 2Gb if available (e.g.
MAP_32BIT on Linux), or otherwise
This option relates to allocation limits; for more about this see enableAllocationLimit. When a thread hits its allocation limit, the RTS throws an exception to the thread, and the thread gets an additional quota of allocation before the exception is raised again, the idea being so that the thread can execute its exception handlers. The
-xq controls the size of this additional quota.
There are several options to give you precise control over garbage collection. Hopefully, you won’t need any of these in normal operation, but there are several things that can be tweaked for maximum performance.
Set the allocation area size used by the garbage collector. The allocation area (actually generation 0 step 0) is fixed and is never resized (unless you use
Increasing the allocation area size may or may not give better performance (a bigger allocation area means worse cache behaviour but fewer garbage collections and less promotion).
With only 1 generation (e.g.
-A option specifies the minimum allocation area, since the actual size of the allocation area will be resized according to the amount of data in the heap (see
Sets the limit on the total size of “large objects” (objects larger than about 3KB) that can be allocated before a GC is triggered. By default this limit is the same as the
Large objects are not allocated from the normal allocation area set by the
-A flag, which is why there is a separate limit for these. Large objects tend to be much rarer than small objects, so most programs hit the
-A limit before the
-AL limit. However, the
-A limit is per-capability, whereas the
-AL limit is global, so as
-N gets larger it becomes more likely that we hit the
-AL limit first. To counteract this, it might be necessary to use a larger
-AL limit when using a large
To see whether you’re making good use of all the memory reseverd for the allocation area (
-N), look at the output of
+RTS -S and check whether the amount of memory allocated between GCs is equal to
-N. If not, there are two possible remedies: use
-n to set a nursery chunk size, or use
-AL to increase the limit for large objects.
Set the minimum size of the old generation. The old generation is collected whenever it grows to this size or the value of the
-F option multiplied by the size of the live data at the previous major collection, whichever is larger.
|Default:||4m with |
-n4m] When set to a non-zero value, this option divides the allocation area (
-A value) into chunks of the specified size. During execution, when a processor exhausts its current chunk, it is given another chunk from the pool until the pool is exhausted, at which point a collection is triggered.
This option is only useful when running in parallel (
-N2 or greater). It allows the processor cores to make better use of the available allocation area, even when cores are allocating at different rates. Without
-n, each core gets a fixed-size allocation area specified by the
-A, and the first core to exhaust its allocation area triggers a GC across all the cores. This can result in a collection happening when the allocation areas of some cores are only partially full, so the purpose of the
-n is to allow cores that are allocating faster to get more of the allocation area. This means less frequent GC, leading a lower GC overhead for the same heap size.
This is particularly useful in conjunction with larger
-A values, for example
-A64m -n4m is a useful combination on larger core counts (8+).
Use a compacting algorithm for collecting the oldest generation. By default, the oldest generation is collected using a copying algorithm; this option causes it to be compacted in-place instead. The compaction algorithm is slower than the copying algorithm, but the savings in memory use can be considerable.
For a given heap size (using the
-H option), compaction can in fact reduce the GC cost by allowing fewer GCs to be performed. This is more likely when the ratio of live data to heap size is high, say greater than 30%.
Compaction doesn’t currently work when a single generation is requested using the
Automatically enable compacting collection when the live data exceeds ⟨n⟩% of the maximum heap size (see the
-M option). Note that the maximum heap size is unlimited by default, so this option has no effect unless the maximum heap size is set with
This option controls the amount of memory reserved for the older generations (and in the case of a two space collector the size of the allocation area) as a factor of the amount of live data. For example, if there was 2M of live data in the oldest generation when we last collected it, then by default we’ll wait until it grows to 4M before collecting it again.
The default seems to work well here. If you have plenty of memory, it is usually better to use
-H ⟨size⟩ (see
-H) than to increase
-F setting will be automatically reduced by the garbage collector when the maximum heap size (the
-M ⟨size⟩ setting, see
-M) is approaching.
Set the number of generations used by the garbage collector. The default of 2 seems to be good, but the garbage collector can support any number of generations. Anything larger than about 4 is probably not a good idea unless your program runs for a long time, because the oldest generation will hardly ever get collected.
Specifying 1 generation with
+RTS -G1 gives you a simple 2-space collector, as you would expect. In a 2-space collector, the
-A option specifies the minimum allocation area size, since the allocation area will grow with the amount of live data in the heap. In a multi-generational collector the allocation area is a fixed size (unless you use the
Use parallel GC in generation ⟨gen⟩ and higher. Omitting ⟨gen⟩ turns off the parallel GC completely, reverting to sequential GC.
The default parallel GC settings are usually suitable for parallel programs (i.e. those using
par, Strategies, or with multiple threads). However, it is sometimes beneficial to enable the parallel GC for a single-threaded sequential program too, especially if the program has a large amount of heap data and GC is a significant fraction of runtime. To use the parallel GC in a sequential program, enable the parallel runtime with a suitable
-N option, and additionally it might be beneficial to restrict parallel GC to the old generation with
|Default:||1 for |
Use load-balancing in the parallel GC in generation ⟨gen⟩ and higher. Omitting ⟨gen⟩ disables load-balancing entirely.
Load-balancing shares out the work of GC between the available cores. This is a good idea when the heap is large and we need to parallelise the GC work, however it is also pessimal for the short young-generation collections in a parallel program, because it can harm locality by moving data from the cache of the CPU where is it being used to the cache of another CPU. Hence the default is to do load-balancing only in the old-generation. In fact, for a parallel program it is sometimes beneficial to disable load-balancing entirely with
|Default:||the value of |
By default, all of the capabilities participate in parallel garbage collection. If we want to use a very large
-N value, however, this can reduce the performance of the GC. For this reason, the
-qn flag can be used to specify a lower number for the threads that should participate in GC. During GC, if there are more than this number of workers active, some of them will sleep for the duration of the GC.
-qn flag may be useful when running with a large
-A value (so that GC is infrequent), and a large
-N value (so as to make use of hyperthreaded cores, for example). For example, on a 24-core machine with 2 hyperthreads per core, we might use
-N48 -qn24 -A128m to specify that the mutator should use hyperthreads but the GC should only use real cores. Note that this configuration would use 6GB for the allocation area.
This option provides a “suggested heap size” for the garbage collector. Think of
-Hsize as a variable
-A option. It says: I want to use at least ⟨size⟩ bytes, so use whatever is left over to increase the
This option does not put a limit on the heap size: the heap may grow beyond the given size as usual.
If ⟨size⟩ is omitted, then the garbage collector will take the size of the heap at the previous GC as the ⟨size⟩. This has the effect of allowing for a larger
-A value but without increasing the overall memory requirements of the program. It can be useful when the default small
-A value is suboptimal, as it can be in programs that create large amounts of long-lived data.
In the threaded and SMP versions of the RTS (see
-threaded, Options affecting linking), a major GC is automatically performed if the runtime has been idle (no Haskell computation has been running) for a period of time. The amount of idle time which must pass before a GC is performed is set by the
-I ⟨seconds⟩ option. Specifying
-I0 disables the idle GC.
For an interactive application, it is probably a good idea to use the idle GC, because this will allow finalizers to run and deadlocked threads to be detected in the idle time when no Haskell computation is happening. Also, it will mean that a GC is less likely to happen when the application is busy, and so responsiveness may be improved. However, if the amount of live data in the heap is particularly large, then the idle GC can cause a significant delay, and too small an interval could adversely affect interactive responsiveness.
This is an experimental feature, please let us know if it causes problems and/or could benefit from further tuning.
Set the initial stack size for new threads.
Thread stacks (including the main thread’s stack) live on the heap. As the stack grows, new stack chunks are added as required; if the stack shrinks again, these extra stack chunks are reclaimed by the garbage collector. The default initial stack size is deliberately small, in order to keep the time and space overhead for thread creation to a minimum, and to make it practical to spawn threads for even tiny pieces of work.
This flag used to be simply
-k, but was renamed to
-ki in GHC 7.2.1. The old name is still accepted for backwards compatibility, but that may be removed in a future version.
Set the size of “stack chunks”. When a thread’s current stack overflows, a new stack chunk is created and added to the thread’s stack, until the limit set by
-K is reached.
The advantage of smaller stack chunks is that the garbage collector can avoid traversing stack chunks if they are known to be unmodified since the last collection, so reducing the chunk size means that the garbage collector can identify more stack as unmodified, and the GC overhead might be reduced. On the other hand, making stack chunks too small adds some overhead as there will be more overflow/underflow between chunks. The default setting of 32k appears to be a reasonable compromise in most cases.
Sets the stack chunk buffer size. When a stack chunk overflows and a new stack chunk is created, some of the data from the previous stack chunk is moved into the new chunk, to avoid an immediate underflow and repeated overflow/underflow at the boundary. The amount of stack moved is set by the
Note that to avoid wasting space, this value should typically be less than 10% of the size of a stack chunk (
-kc), because in a chain of stack chunks, each chunk will have a gap of unused space of this size.
|Default:||80% of physical memory|
Set the maximum stack size for an individual thread to ⟨size⟩ bytes. If the thread attempts to exceed this limit, it will be sent the
StackOverflow exception. The limit can be disabled entirely by specifying a size of zero.
This option is there mainly to stop the program eating up all the available memory in the machine if it gets into an infinite loop.
Minimum % ⟨n⟩ of heap which must be available for allocation.
Set the maximum heap size to ⟨size⟩ bytes. The heap normally grows and shrinks according to the memory requirements of the program. The only reason for having this option is to stop the heap growing without bound and filling up all the available swap space, which at the least will result in the program being summarily killed by the operating system.
The maximum heap size also affects other garbage collection parameters: when the amount of live data in the heap exceeds a certain fraction of the maximum heap size, compacting collection will be automatically enabled for the oldest generation, and the
-F parameter will be reduced in order to avoid exceeding the maximum heap size.
If the program’s heap exceeds the value set by
-M, the RTS throws an exception to the program, and the program gets an additional quota of allocation before the exception is raised again, the idea being so that the program can execute its exception handlers.
-Mgrace= controls the size of this additional quota.
Enable NUMA-aware memory allocation in the runtime (only available with
-threaded, and only on Linux currently).
Background: some systems have a Non-Uniform Memory Architecture, whereby main memory is split into banks which are “local” to specific CPU cores. Accessing local memory is faster than accessing remote memory. The OS provides APIs for allocating local memory and binding threads to particular CPU cores, so that we can ensure certain memory accesses are using local memory.
--numa option tells the RTS to tune its memory usage to maximize local memory accesses. In particular, the RTS will:
--numa flag is typically beneficial when a program is using all cores of a large multi-core NUMA system, with a large allocation area (
-A). All memory accesses to the allocation area will go to local memory, which can save a significant amount of remote memory access. A runtime speedup on the order of 10% is typical, but can vary a lot depending on the hardware and the memory behaviour of the program.
Note that the RTS will not set CPU affinity for bound threads and threads entering Haskell from C/C++, so if your program uses bound threads you should ensure that each bound thread calls the RTS API
rts_setInCallCapability(c,1) from C/C++ before calling into Haskell. Otherwise there could be a mismatch between the CPU that the thread is running on and the memory it is using while running Haskell code, which will negate any benefits of
If given an explicit <mask>, the <mask> is interpreted as a bitmap that indicates the NUMA nodes on which to run the program. For example,
--numa=3 would run the program on NUMA nodes 0 and 1.
These options produce runtime-system statistics, such as the amount of time spent executing the program and in the garbage collector, the amount of memory allocated, the maximum size of the heap, and so on. The three variants give different levels of detail:
-T collects the data but produces no output
-t produces a single line of output in the same format as GHC’s
-s produces a more detailed summary at the end of the program, and
-S additionally produces information about each and every garbage collection.
The output is placed in ⟨file⟩. If ⟨file⟩ is omitted, then the output is sent to
If you use the
-T flag then, you should access the statistics using GHC.Stats.
If you use the
-t flag then, when your program finishes, you will see something like this:
<<ghc: 36169392 bytes, 69 GCs, 603392/1065272 avg/max bytes residency (2 samples), 3M in use, 0.00 INIT (0.00 elapsed), 0.02 MUT (0.02 elapsed), 0.07 GC (0.07 elapsed) :ghc>>
This tells you:
-hTRTS option (RTS options for profiling).
You can also get this in a more future-proof, machine readable format, with
[("bytes allocated", "36169392") ,("num_GCs", "69") ,("average_bytes_used", "603392") ,("max_bytes_used", "1065272") ,("num_byte_usage_samples", "2") ,("peak_megabytes_allocated", "3") ,("init_cpu_seconds", "0.00") ,("init_wall_seconds", "0.00") ,("mutator_cpu_seconds", "0.02") ,("mutator_wall_seconds", "0.02") ,("GC_cpu_seconds", "0.07") ,("GC_wall_seconds", "0.07") ]
If you use the
-s flag then, when your program finishes, you will see something like this (the exact details will vary depending on what sort of RTS you have, e.g. you will only see profiling data if your RTS is compiled for profiling):
36,169,392 bytes allocated in the heap 4,057,632 bytes copied during GC 1,065,272 bytes maximum residency (2 sample(s)) 54,312 bytes maximum slop 3 MB total memory in use (0 MB lost due to fragmentation) Generation 0: 67 collections, 0 parallel, 0.04s, 0.03s elapsed Generation 1: 2 collections, 0 parallel, 0.03s, 0.04s elapsed SPARKS: 359207 (557 converted, 149591 pruned) INIT time 0.00s ( 0.00s elapsed) MUT time 0.01s ( 0.02s elapsed) GC time 0.07s ( 0.07s elapsed) EXIT time 0.00s ( 0.00s elapsed) Total time 0.08s ( 0.09s elapsed) %GC time 89.5% (75.3% elapsed) Alloc rate 4,520,608,923 bytes per MUT second Productivity 10.5% of total user, 9.1% of total elapsed
SPARKSstatistic refers to the use of
Control.Parallel.parand related functionality in the program. Each spark represents a call to
par; a spark is “converted” when it is executed in parallel; and a spark is “pruned” when it is found to be already evaluated and is discarded from the pool by the garbage collector. Any remaining sparks are discarded at the end of execution, so “converted” plus “pruned” does not necessarily add up to the total.
Next there is the CPU time and wall clock time elapsed broken down by what the runtime system was doing at the time. INIT is the runtime system initialisation. MUT is the mutator time, i.e. the time spent actually running your code. GC is the time spent doing garbage collection. RP is the time spent doing retainer profiling. PROF is the time spent doing other profiling. EXIT is the runtime system shutdown time. And finally, Total is, of course, the total.
%GC time tells you what percentage GC is of Total. “Alloc rate” tells you the “bytes allocated in the heap” divided by the MUT CPU time. “Productivity” tells you what percentage of the Total CPU and wall clock elapsed times are spent in the mutator (MUT).
-S flag, as well as giving the same output as the
-s flag, prints information about each GC as it happens:
Alloc Copied Live GC GC TOT TOT Page Flts bytes bytes bytes user elap user elap 528496 47728 141512 0.01 0.02 0.02 0.02 0 0 (Gen: 1) [...] 524944 175944 1726384 0.00 0.00 0.08 0.11 0 0 (Gen: 0)
For each garbage collection, we print:
Most profiling runtime options are only available when you compile your program for profiling (see Compiler options for profiling, and RTS options for heap profiling for the runtime options). However, there is one profiling option that is available for ordinary non-profiled executables:
Generates a basic heap profile, in the file
prog.hp. To produce the heap profile graph, use hp2ps (see hp2ps – Rendering heap profiles to PostScript). The basic heap profile is broken down by data constructor, with other types of closures (functions, thunks, etc.) grouped into broad categories (e.g.
THUNK). To get a more detailed profile, use the full profiling support (Profiling). Can be shortened to
Sets the maximum length of the cost-centre names listed in the heap profile.
Log events in binary format. Without any ⟨flags⟩ specified, this logs a default set of events, suitable for use with tools like ThreadScope.
Per default the events are written to
program.eventlog though the mechanism for writing event log data can be overriden with a custom
For some special use cases you may want more control over which events are included. The ⟨flags⟩ is a sequence of zero or more characters indicating which classes of events to log. Currently these the classes of events that can be enabled/disabled:
s— scheduler events, including Haskell thread creation and start/stop events. Enabled by default.
g— GC events, including GC start/stop. Enabled by default.
p— parallel sparks (sampled). Enabled by default.
f— parallel sparks (fully accurate). Disabled by default.
u— user events. These are events emitted from Haskell code using functions such as
Debug.Trace.traceEvent. Enabled by default.
You can disable specific classes, or enable/disable all classes at once:
a— enable all event classes listed above
-⟨x⟩— disable the given class of events, for any event class listed above
-a— disable all classes
-l-ag would disable all event classes (
-a) except for GC events (
For spark events there are two modes: sampled and fully accurate. There are various events in the life cycle of each spark, usually just creating and running, but there are some more exceptional possibilities. In the sampled mode the number of occurrences of each kind of spark event is sampled at frequent intervals. In the fully accurate mode every spark event is logged individually. The latter has a higher runtime overhead and is not enabled by default.
The format of the log file is described by the header
EventLogFormat.h that comes with GHC, and it can be parsed in Haskell using the ghc-events library. To dump the contents of a
.eventlog file as text, use the tool
ghc-events show that comes with the ghc-events package.
Log events as text to standard output, instead of to the
.eventlog file. The ⟨flags⟩ are the same as for
-l, with the additional option
t which indicates that the each event printed should be preceded by a timestamp value (in the binary
.eventlog file, all events are automatically associated with a timestamp).
The debugging options
-Dx also generate events which are logged using the tracing framework. By default those events are dumped as text to stdout (
-v), but they may instead be stored in the binary eventlog file by using the
These RTS options might be used (a) to avoid a GHC bug, (b) to see “what’s really happening”, or (c) because you feel like it. Not recommended for everyday use!
Sound the bell at the start of each (major) garbage collection.
Oddly enough, people really do use this option! Our pal in Durham (England), Paul Callaghan, writes: “Some people here use it for a variety of purposes—honestly!—e.g., confirmation that the code/machine is doing something, infinite loop detection, gauging cost of recently added code. Certain people can even tell what stage [the program] is in by the beep pattern. But the major use is for annoying others in the same office…”
An RTS debugging flag; only available if the program was linked with the
-debug option. Various values of ⟨x⟩ are provided to enable debug messages and additional runtime sanity checks in different subsystems in the RTS, for example
+RTS -Ds -RTS enables debug messages from the scheduler. Use
+RTS -? to find out which debug flags are supported.
Debug messages will be sent to the binary event log file instead of stdout if the
-l option is added. This might be useful for reducing the overhead of debug tracing.
For more information on ticky-ticky profiling, see Using “ticky-ticky” profiling (for implementors).
(Only available when the program is compiled for profiling.) When an exception is raised in the program, this option causes a stack trace to be dumped to
This can be particularly useful for debugging: if your program is complaining about a
head  error and you haven’t got a clue which bit of code is causing it, compiling with
-prof -fprof-auto (see
-prof) and running with
+RTS -xc -RTS will tell you exactly the call stack at the point the error was raised.
The output contains one report for each exception raised in the program (the program might raise and catch several exceptions during its execution), where each report looks something like this:
*** Exception raised (reporting due to +RTS -xc), stack trace: GHC.List.CAF --> evaluated by: Main.polynomial.table_search, called from Main.polynomial.theta_index, called from Main.polynomial, called from Main.zonal_pressure, called from Main.make_pressure.p, called from Main.make_pressure, called from Main.compute_initial_state.p, called from Main.compute_initial_state, called from Main.CAF ...
The stack trace may often begin with something uninformative like
GHC.List.CAF; this is an artifact of GHC’s optimiser, which lifts out exceptions to the top-level where the profiling system assigns them to the cost centre “CAF”. However,
+RTS -xc doesn’t just print the current stack, it looks deeper and reports the stack at the time the CAF was evaluated, and it may report further stacks until a non-CAF stack is found. In the example above, the next stack (after
--> evaluated by) contains plenty of information about what the program was doing when it evaluated
Implementation details aside, the function names in the stack should hopefully give you enough clues to track down the bug.
See also the function
traceStack in the module
Debug.Trace for another way to view call stacks.
Turn off “update-frame squeezing” at garbage-collection time. (There’s no particularly good reason to turn it off, except to ensure the accuracy of certain data collected regarding thunk entry counts.)
It is possible to ask the RTS to give some information about itself. To do this, use the
--info flag, e.g.
$ ./a.out +RTS --info [("GHC RTS", "YES") ,("GHC version", "6.7") ,("RTS way", "rts_p") ,("Host platform", "x86_64-unknown-linux") ,("Host architecture", "x86_64") ,("Host OS", "linux") ,("Host vendor", "unknown") ,("Build platform", "x86_64-unknown-linux") ,("Build architecture", "x86_64") ,("Build OS", "linux") ,("Build vendor", "unknown") ,("Target platform", "x86_64-unknown-linux") ,("Target architecture", "x86_64") ,("Target OS", "linux") ,("Target vendor", "unknown") ,("Word size", "64") ,("Compiler unregisterised", "NO") ,("Tables next to code", "YES") ]
The information is formatted such that it can be read as a of type
[(String, String)]. Currently the following fields are present:
rts_thr(threaded runtime, i.e. linked using the
rts_p(profiling runtime, i.e. linked using the
-profoption). Other variants include
dyn(the RTS is linked in dynamically, i.e. a shared library, rather than statically linked into the executable itself). These can be combined, e.g. you might have
Target platformTarget architectureTarget OSTarget vendor
Build platformBuild architectureBuild OSBuild vendor
Host platformHost architectureHost OSHost vendor
"64", reflecting the word size of the target platform.
Tables next to code
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