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authorDuncan Coutts <duncan@well-typed.com>2011-06-01 19:48:15 +0100
committerDuncan Coutts <duncan@well-typed.com>2011-07-18 16:31:14 +0100
commitfa8d20e6d85212290b633159b6ef2d77fb1c4021 (patch)
tree0dd7f7926d2c3a482e451a691f794fde2cae9a38 /rts/Capability.c
parent556557ebee2758acade603e25a8a16266dea791d (diff)
downloadhaskell-fa8d20e6d85212290b633159b6ef2d77fb1c4021.tar.gz
Classify overflowed sparks separately
When you use `par` to make a spark, if the spark pool on the current capability is full then the spark is discarded. This represents a loss of potential parallelism and it also means there are simply a lot of sparks around. Both are things that might be of concern to a programmer when tuning a parallel program that uses par. The "+RTS -s" stats command now reports overflowed sparks, e.g. SPARKS: 100001 (15521 converted, 84480 overflowed, 0 dud, 0 GC'd, 0 fizzled)
Diffstat (limited to 'rts/Capability.c')
-rw-r--r--rts/Capability.c1
1 files changed, 1 insertions, 0 deletions
diff --git a/rts/Capability.c b/rts/Capability.c
index e12bf994f3..d93c9c1eda 100644
--- a/rts/Capability.c
+++ b/rts/Capability.c
@@ -234,6 +234,7 @@ initCapability( Capability *cap, nat i )
cap->inbox = (Message*)END_TSO_QUEUE;
cap->spark_stats.created = 0;
cap->spark_stats.dud = 0;
+ cap->spark_stats.overflowed = 0;
cap->spark_stats.converted = 0;
cap->spark_stats.gcd = 0;
cap->spark_stats.fizzled = 0;