Hi,
I'm trying to optimise julia script for spectra baseline correction using
rolling ball algorithm
(http://linkinghub.elsevier.com/retrieve/pii/0168583X95009086,
http://cran.r-project.org/web/packages/baseline).
Profiling the code showed that the most time consuming part is actually
subarray pickup.
I was just wondering if there is any other possible speedup for this
problem?
I've started initially with standard sub-indexing:
a = rand(300000);
w = 200;
@time for i in 1:length(a)-w
a[i:i+w]
end
elapsed time: 0.387236571 seconds (645148344 bytes allocated, 56.46% gc
time)
Then I've tried directly with subarray function and it improved the runtime
significantly:
@time for i in 1:length(a)-w
sub(a,i:i+w)
end
elapsed time: 0.10720574 seconds (86321144 bytes allocated, 32.13% gc time)
With approach to internally remove and add elements I've gained yet some
extra speed-up (eliminating gc):
subset = a[1:1+w]
@time for i in 2:length(a)-w
splice!(subset,1)
insert!(subset,w+1,a[i+w])
end
elapsed time: 0.067341484 seconds (33556344 bytes allocated)
However I wonder if this is the end....
And obligatory version info:
Julia Version 0.3.4
Commit 3392026* (2014-12-26 10:42 UTC)
Platform Info:
System: Darwin (x86_64-apple-darwin13.4.0)
CPU: Intel(R) Core(TM) i5-4690 CPU @ 3.50GHz
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
LAPACK: libopenblas
LIBM: libopenlibm
LLVM: libLLVM-3.3
