It's typical for benchmarks that allocate a large data structure to spend a lot of time in the GC. The data gets copied twice - once in the young generation and then again when promoted to the old generation. You can make this kind of benchmark much faster by just using a bigger allocation area. There's nothing inherently costly about StgMutArrPtrs compared to other objects, except that they are variable size and therefore we can't unroll the copy loop, but I don't think that's a big effect. The actual copying is the major cost. The way to improve this kind of benchmark would be to add some heuristics for varying the nursery size based on the quantity of data retained, for example. I think there's a lot of room for improvement here, but someone needs to do some careful benchmarking and experimentation. Andrew Farmer did some work on this and allegedly got good results but we never saw the code (hint hint!). Cheers, Simon On 1 October 2013 06:43, Johan Tibell <johan.tibell@gmail.com> wrote:
The code for 'allocate' in rts/sm/Storage.c doesn't seem that expensive. An extra branch compared to inline allocation and allocation is done in the next nursery block (risking fragmentation?).
-- Johan
On Mon, Sep 30, 2013 at 9:50 PM, Johan Tibell <johan.tibell@gmail.com> wrote:
Hi,
When I benchmark Data.HashMap.insert from unordered-containers (inserting the keys [0..10000]) the runtime is dominated by GC:
$ cat Test.hs module Main where
import Control.DeepSeq import Control.Exception import Control.Monad import qualified Data.HashMap.Strict as HM import Data.List (foldl')
main = do let ks = [0..10000] :: [Int] evaluate (rnf ks) forM_ ([0..1000] :: [Int]) $ \ x -> do evaluate $ HM.null $ foldl' (\ m k -> HM.insert k x m) HM.empty ks
$ perf record -g ./Test +RTS -s 6,187,678,112 bytes allocated in the heap 3,309,887,128 bytes copied during GC 1,299,200 bytes maximum residency (1002 sample(s)) 118,816 bytes maximum slop 5 MB total memory in use (0 MB lost due to fragmentation)
Tot time (elapsed) Avg pause Max pause Gen 0 11089 colls, 0 par 1.31s 1.30s 0.0001s 0.0005s Gen 1 1002 colls, 0 par 0.49s 0.51s 0.0005s 0.0022s
INIT time 0.00s ( 0.00s elapsed) MUT time 1.02s ( 1.03s elapsed) GC time 1.80s ( 1.80s elapsed) EXIT time 0.00s ( 0.00s elapsed) Total time 2.82s ( 2.84s elapsed)
%GC time 63.7% (63.5% elapsed)
Alloc rate 6,042,264,963 bytes per MUT second
Productivity 36.3% of total user, 36.1% of total elapsed
$ perf report 41.46% Test Test [.] evacuate 15.47% Test Test [.] scavenge_block 11.04% Test Test [.] s3cN_info 8.74% Test Test [.] s3aZ_info 3.59% Test Test [.] 0x7ff5 2.83% Test Test [.] scavenge_mut_arr_ptrs 2.69% Test libc-2.15.so [.] 0x147fd9 2.51% Test Test [.] allocate 2.00% Test Test [.] s3oo_info 0.91% Test Test [.] todo_block_full 0.87% Test Test [.] hs_popcnt64 0.80% Test Test [.] s3en_info 0.62% Test Test [.] s3el_info
Is GC:ing StgMutArrPtrs and StgArrPtrs, which I create a lot of, more expensive than GC:ing normal heap objects (i.e. for standard data types)?
-- Johan