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Criterion benchmarks for the different haskell concurrent channel implementations in base and stm and elsewhere, as well as simple var read/write benchmarks for MVar, IORef, and TVar and others.

These benchmarks were originally taken from bench/chanbench.hs in the stm package, ported to criterion with some additions. To run them on your machine:

cabal sandbox init
cabal install
# For HTML reports:
./.cabal-sandbox/bin/chan-benchmarks -g -o Benchmarks.html +RTS -N

Feel free to send pull requests with new or improved benchmarks.

Sample Results

Nice HTML output for a sample run performed on:

$ lscpu 
Architecture:          i686
CPU op-mode(s):        32-bit, 64-bit
Byte Order:            Little Endian
CPU(s):                4
On-line CPU(s) list:   0-3
Thread(s) per core:    2
Core(s) per socket:    2
Socket(s):             1
Vendor ID:             GenuineIntel
CPU family:            6
Model:                 58
Stepping:              9
CPU MHz:               1400.000
BogoMIPS:              4988.38
Virtualization:        VT-x
L1d cache:             32K
L1i cache:             32K
L2 cache:              256K
L3 cache:              4096K

...are at Benchmarks.chans_sample.html and Benchmarks.vars_sample.html.

Some analysis of primitive operations

forkIO           309.ns
context switch  2975.ns

getNumCapabilities    4.1ns
myThreadId            4.7ns

newIORef      7.19
readIORef     3.74ns
writeIORef    7.02ns
modifyIORef'  7.02ns  -- even though this is implemented as read+write??
atomicModifyIORef'   22.43ns
atomicModifyIORef    53.67ns  -- variable; showing cost of lazy creation of (const 'x') thunks?

newEmptyMVar  7.32ns
takeMVar     16.21ns
putMVar       9.02ns 
modifyMVarMasked_   35.09ns  -- handler overhead ~ 10ns

newTVarIO    12.96ns
atomically writeTVar    53.35ns
atomically readTVar     54.29ns
readTVarIO               4.13ns
atomically modifyTVar'  63.76ns

--counter from atomic-primops v0.5
-- NOTE: ACTUALLY 
newCounter   11.99ns
incrCounter   9.28ns


Throughput of incrementing atomic counter with...
    modifyMVar_        331.29ms / 100000  = 3312.9ns per increment
    modifyMVarMasked_  323.41ms / 100000    3234.1ns    -- NOTE: small variance
    atomicModifyIORef'  87.66ms / 100000     876.6ns    -- NOTE: sort of folded normal distribution beginning at 9.76ms , where the max we saw was 256.12ms
    modifyTVar'         19.10ms / 100000     191.0ns    -- NOTE: much lower variance, with samples 17 - 21 ms

    incrCounter          0.97ms / 100000  -- NOTE: GARBAGE; COUNTER NOT ATOMIC

Random resources

Some discussion of nitty-gritty of atomicModifyIORef:

http://stackoverflow.com/questions/10102881/haskell-how-does-atomicmodifyioref-work

Random Analysis

Back-of-envelope look at how primitive var read write cost relates to chan RW cost.

As of the current test run, looking at the mean times for the fastest three contenders on the easiest test (write some, read some), we get the following mean timings for one read and write (although reads and writes might vary widely)

Chan             135 ns
TQueue           175 ns
chan-split-fast   88 ns

Measured timings for an atomic modify (or take/put; again not ideal) divided by 2 (i.e. very approx timing for a take/read or put/write):

MVar    15 ns
TVar    36 ns

and var creation:

MVar    24 ns
TVar    21 ns

Counting var operations, with (count) around slowest path

chan-split-fast
---------------
             puts  takes  creates   TOTAL
readChan     1(2)  1(3)   (1)       30-99 ns
writeChan    1(2)  1      /         30-45 ns
          TOTAL for read and write: 60-144 ns

So if we didn't screw that up: - yes, read/write timing dominates - but there might still be room to shave time elsewhere - in "write some / read some" we don't take the slow reader-blocked path much, as expected