Re: [julia-users] Re: CUDART and CURAND problem on running the same "do" loop twice

Are you sure this is due to CUDArt? For me, this works as many times as I care to try it (note that I'm not using CURAND): using CUDArt result = devices(dev->capability(dev)[1]>=2; nmax = 1) do devlist device(devlist[1]) h = rand(Float32, 1000) d_a = CudaArray(h) a = to_host(d_a)

[julia-users] Re: Julia Hands-on: Introductory Tutorial for Distributed Computing

Thanks, Leandro. I apologize for the problems with the Hangout session, but I had to install Epson software to use the projector and I lost my connection to the Internet during the tutorial. André Lage. On Friday, November 6, 2015 at 1:34:27 PM

[julia-users] Re: Escher Spinner

On Saturday, November 7, 2015 at 4:21:09 AM UTC+5:30, Brandon Miller wrote: > > Code snippet: https://gist.github.com/r2dbg/14189258e9daee2cece6 > > I'd like for the spinner on line 23 to spin while do_work() is running and > stop after do_work returns. However, I can't seem to find a good way

Re: [julia-users] Julia vs C++ single dispatch performance comparison

I agree, in fact my knowledge about branch prediction mechanisms is rather limited. But doing *if(rand()%2)* instead of *if(i%i)* yields times close to the given one. On the other hand, with a single type (with *if(true)*) the times drop to around 320 μs. For julia code, randomness seems to have

Re: [julia-users] Julia vs C++ single dispatch performance comparison

The times for Julia code in my previous email are wrong, I wanted to write: 0.000126 seconds 0.004695 seconds (99.49 k allocations: 1.518 MB) 0.000871 seconds On Sun, Nov 8, 2015 at 10:19 PM Cristóvão Duarte Sousa wrote: > I agree, in fact my knowledge about branch prediction

Re: [julia-users] Do I have simd?

On another, slightly older system, I noticed similar (approximately identical) timings for the simd.jl test script using Julia 0.5:julia> include("/Users/rob/Projects/Julia/Rob/Julia/simd.jl")Julia Version 0.5.0-dev+720Commit 5920633* (2015-10-11 15:15 UTC)Platform Info:  System: Darwin

Re: [julia-users] Re: CUDART and CURAND problem on running the same "do" loop twice

Interesting. I have the bug when using cublas.jl I haven't found a way to initialize resources to avoid these errors but if I just use cudart on it's own there aren't memory errors.

Re: [julia-users] Re: CUDART and CURAND problem on running the same "do" loop twice

Interesting. I have the bug when using cublas.jl I haven't found a way to initialize resources to avoid these errors but if I just use cudart on it's own there aren't memory errors.

Re: [julia-users] Re: CUDART and CURAND problem on running the same "do" loop twice

Interesting. I have the bug when using cublas.jl I haven't found a way to initialize resources to avoid these errors but if I just use cudart on it's own there aren't memory errors.

Re: [julia-users] Julia vs C++ single dispatch performance comparison

On Sun, Nov 8, 2015 at 5:24 PM, Cristóvão Duarte Sousa wrote: > The times for Julia code in my previous email are wrong, I wanted to write: > 0.000126 seconds > 0.004695 seconds (99.49 k allocations: 1.518 MB) > 0.000871 seconds FYI, I see a 25-40% performance improvement on

[julia-users] Arrays as streams / consuming data with take et al

I'd like to be able to use take() and all the other iterator tools with a stream of data backed by an array (or string). By that I mean I'd like to be able to do something like: > stream = XXX([1,2,3,4,5]) > collect(take(stream, 3)) [1,2,3] > collect(take(stream, 2)) [4,5] Is this possible? I

Re: [julia-users] Arrays as streams / consuming data with take et al

On Sun, Nov 8, 2015 at 8:11 PM, andrew cooke wrote: > I'd like to be able to use take() and all the other iterator tools with a > stream of data backed by an array (or string). > > By that I mean I'd like to be able to do something like: > >> stream = XXX([1,2,3,4,5]) >>

Re: [julia-users] Re: Large Data Sets in Julia

Thanks! André Lage. On Fri, Nov 6, 2015 at 7:20 AM, Tim Holy wrote: > Not sure if it's as high-level as you're hoping for, but julia has great > support for arrays that are much bigger than memory. See Mmap.mmap and > SharedArray(filename, T, dims). > > --Tim > > On

[julia-users] Re: DataFrame to JSON

This is embarrassing since I'm just learning, but in the interest of getting feedback and improving my Julia coding skills, here is what I did: function df2json(df::DataFrame) nrow,ncol = size(df) io = IOBuffer(); write(io,"[\n") for irow = 1:nrow irow == nrow ? eor = "" : eor = ","