The updated code is available at
https://github.com/kapiliitr/JuliaBenchmarks/blob/master/streamp.jl
I am getting a performance slightly less than C for multiple processes, but
for single process, performance is much less (though better than previous
values)
Just a very basic implementation of one of the benchmarks is:
julia> size=5000000;
julia> a=fill(3,size);
julia> b=fill(0,size);
julia> @time for i=1:size
b[i]=a[i]
end
The output is
elapsed time: 0.537257426 seconds (159983648 bytes allocated, 3.16% gc time)
In C, the same code takes 0.012210 seconds.
ᐧ
Regards,
Kapil Agarwal
On Sat, Nov 1, 2014 at 12:36 PM, Jason Merrill <[email protected]> wrote:
> On Saturday, November 1, 2014 9:35:03 AM UTC-7, Jason Merrill wrote:
>>
>> On Saturday, November 1, 2014 9:15:43 AM UTC-7, Kapil Agarwal wrote:
>>>
>>> I need those variables as globals as otherwise I will have to pass them
>>> from one function to another all the time.
>>>
>>
>> It's generally better long-term design to pass the relevant state around
>> than to have it be global. One thing that helps is to define a type that
>> encapsulates the relevant state, so that you only have to pass one thing
>> around between functions instead of many. E.g. if I have
>>
>> f(a, b, c, d)
>> mutatea!(a)
>> mutateb!(b)
>> mutatec!(c)
>> mutated!(d)
>> return g(a,b,c,d)
>> end
>>
>
> Sorry, this wasn't quite real Julia syntax. Should have written `function`
> before `f(a, b, c, d)` here and below.
>
>
>> and suppose that g calls another function that also depends on a, b, c,
>> and d, and so on, it can get kind of tedious to pass all the arguments
>> separately.
>>
>> But you can do
>>
>> type algorithmState
>> a::Ta
>> b::Tb
>> c::Tc
>> d::Td
>> end
>>
>> (where the Ta, Tb, Tc, and Td should be replaced by appropriate concrete
>> types).
>>
>> Then you can do
>>
>> f(x::algorithmState)
>> mutateState!(x)
>> g(x)
>> end
>>
>>
>
