[julia-users] mismatching types (confusion matrix)

I am new to julia so i might ask a strange question. So far i've been programming quite smoothly, but type managing leads me astray. I have 1d arrays i want to apply a confusion matrix function to from the MLBase library. http://mlbasejl.readthedocs.io/en/latest/perfeval.html However i have u

[julia-users] Re: trouble using Cxx.jl

I also run into issues compiling Cxx on OS X (10.10.2), I believe related to llvm-svn llvm[8]: Compiling Host.mm for Release+Asserts build In file included from /Users/sebastian/julia/deps/llvm-svn/tools/lldb/source/Host/macosx/Host.mm:68: In file included from /System/Library/Frameworks

[julia-users] Re: JuliaGPU, JuliaGeometry, JuliaGL

Forgive my ignorance, what is a gitter batch? On Tuesday, February 17, 2015 at 12:12:05 PM UTC-5, Simon Danisch wrote: > > Hi all, > I've tried to vitalize some of the Julia groups that I'm part of. > Groups: JuliaGPU , JuliaGeometry >

Re: [julia-users] Type matching in Julia version 0.4.0-dev+3434

Thanks for the hard work! I got a surprising deprecation when writing an array with one term in it. While the expression [1] is valid (creating an Array{Int64,1} with one element in it), the expression [1:5] generates the deprecation warning, and I now have to write [1:5;]. This seems a little

[julia-users] Re: Some simple use cases for multi-threading

Task stealing parallelism is an increasingly common use case and easy to program. e.g. Cilk, Grand Central Dispatch, On Thursday, March 12, 2015 at 11:52:37 PM UTC-4, Viral Shah wrote: > > I am looking to put together a set of use cases for our multi-threading > capabilities - mainly to push fo

[julia-users] Linking directly with LLVM generated bytecode

I've compiled a separate set of functions with another LLVM-based toolchain (in this case Intel's SPMD compiler, ispc). If I have it emit LLVM byte code (i.e. as a .bc file), is it possible to link that LLVM code directly into a Julia session? I can compile the library into a dynamic library, l

[julia-users] zero-allocation reinterpretation of bytes

I'm trying to read some binary formatted data. In C, I would define an appropriately padded struct and cast away. Is is possible to do something similar in Julia, though for only one value at a time? Philosophically, I'd like to approximate the following, for some simple bittypes T (Int32, Floa

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

read function. If the data is read as an Uint8 array you can use an immutable and reinterprete into it. This does however not work if the C-struct would contain fixed-size array data. Cheers Tobi Am Montag, 23. März 2015 20:20:09 UTC+1 schrieb Sebastian Good: I'm trying to read some b

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

Thanks Simon, I’ve tried this approach, but the disassembly still indicates it calls a function julia_pointer, which is overhead I’d like to avoid if possible.  On March 23, 2015 at 6:11:08 PM, Simon Danisch (sdani...@gmail.com) wrote: unsafe_read_t(T::DataType, x::Vector{Uint8}, byte_offset::In

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

rstand llvmcall well enough, though ;) Am Montag, 23. März 2015 20:20:09 UTC+1 schrieb Sebastian Good: I'm trying to read some binary formatted data. In C, I would define an appropriately padded struct and cast away. Is is possible to do something similar in Julia, though for only one value a

[julia-users] When are files un mmap'd?

Given s = open("bigdata") a = mmap_array(Int64, (a_billion, a_jillion), s) Is it safe to use a after s has been closed? The documentation isn't entirely clear about when munmap is called; is there an explicit operation we should use on a to deterministically unmap it?

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

Karpinski wrote: There's a branch in eltype, which is probably causing this difference. On Tue, Mar 24, 2015 at 7:00 PM, Sebastian Good wrote: Yep, that’s done it. The only difference I can see in the code I wrote before and this code is that previously I had convert(Ptr{T}, pointer(raw,

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

n Wed, Mar 25, 2015 at 12:53 PM, Sebastian Good wrote: I guess what I find most confusing is that there would be a difference, since adding 1 to a pointer only adds one byte, not one element size. > p1 = pointer(zeros(UInt64)); Ptr{UInt64} @0x00010b28c360 > p1 + 1 Ptr{UInt64} @0x0001

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

6 AM UTC-4, Sebastian Good wrote: The benefit of the semantics of the two argument pointer function is that it preserves intuitive pointer arithmetic. As a new (yet happy!) Julia programmer, I certainly don’t know what the deprecation implications of changing pointer arithmetic are (vast, sadly,

[julia-users] SubArray memory footprint

I was surprised by two things in the SubArray implementation 1) They are big! About 175 bytes for a simple subset from a 1D array from my naive measurement.[*] 2) They are not flat. That is, they seem to get heap allocated and have indirections in them. I'm guessing this is because SubArrays ar

Re: [julia-users] SubArray memory footprint

000697173 seconds (1 MB allocated) So you can see it's about 50x faster and about 8-fold more memory efficient on 0.4. Once Jeff finishes his tuple overhaul, the allocation on 0.4 could potentially drop to 0. --Tim On Wednesday, March 25, 2015 11:18:08 AM Sebastian Good wrote:

Re: [julia-users] Re: zero-allocation reinterpretation of bytes

e the two-argument form of pointer. On Wed, Mar 25, 2015 at 12:53 PM, Sebastian Good wrote: I guess what I find most confusing is that there would be a difference, since adding 1 to a pointer only adds one byte, not one element size. > p1 = pointer(zeros(UInt64)); Ptr{UInt64} @0x00010b2

Re: [julia-users] SubArray memory footprint

ecords) I’d think it would specialize > very fast since there is still contiguous access in the first dimension, > and a contiguous stride. > > And it’s good enough to get working, but I was a bit surprised. Any > suggestions? > > On March 25, 2015 at 4:48:41 PM, Se

Re: [julia-users] SubArray memory footprint

bly more algorithms in base that need to be > modified. > Can you file an issue with any you notice? > > Best, > --Tim > > On Thursday, March 26, 2015 10:48:31 PM Sebastian Good wrote: > > Sorry, didn’t realize the conversation had wandered off-list. Thanks for > > correct

Re: [julia-users] SubArray memory footprint

Ah, excellent, that makes sense. In practice this is how we'll be doing it anyway. On Friday, March 27, 2015, Matt Bauman wrote: > On Friday, March 27, 2015 at 8:21:10 AM UTC-4, Sebastian Good wrote: >> >> Forgive my ignorance, but what is Cartesian indexing? >>

Re: [julia-users] SubArray memory footprint

r is one of the advantages of 0.4's > SubArrays over ArrayViews.) But in general it's not efficient. > > But Sebastian, please do file those issues. It's hard to keep track of what > needs updating, and issues are vastly preferable to posts to julia-users. > For > insta

Re: [julia-users] SubArray memory footprint

Random thought: If tuples can avoid boxing why not return tuples from the iterator protocol? On Friday, March 27, 2015, Matt Bauman wrote: > On Friday, March 27, 2015 at 8:21:10 AM UTC-4, Sebastian Good wrote: >> >> Forgive my ignorance, but what is Cartesian indexing? >> &

Re: [julia-users] SubArray memory footprint

them, > and > it's not obvious they should. But all that is supported by CartesianIndex. > > --Tim > > On Saturday, March 28, 2015 07:10:50 AM Sebastian Good wrote: > > Random thought: If tuples can avoid boxing why not return tuples from the > > iterator proto

Re: [julia-users] Understanding the Cost of Virtualization

I guess this is ultimately where a JavaScript flavored optimistic dispatch jump table would benefit us. The code can start as fully polymorphic but specialize to a direct jump or at least a small vtable after a few executions

[julia-users] Re: [ANN] JuliaIO and FileIO

Very interesting project. I've worked a little on problems like this in my projects and have found that filename extensions aren't always enough to distinguish filetypes. It's not uncommon to have to scan the first few (hundred) bytes looking for distinctive patterns, magic cookies, etc. to det

Re: [julia-users] merged arrays?

oable. > > Cheers! > Kevin > > On Wed, Apr 8, 2015 at 8:56 PM, Sebastian Good < > > sebast...@palladiumconsulting.com> wrote: > > I can use sub to pretend a larger array is a smaller, or differently > > shaped one. Is there functionality to allow me to

[julia-users] merged arrays?

I can use sub to pretend a larger array is a smaller, or differently shaped one. Is there functionality to allow me to treat several smaller arrays as a larger one without copying them? In effect, mimicking hcat and friends, but without copying data.

[julia-users] Re: Non-GPL Julia?

Is producing a non-GPL Julia build still on the radar? It might be a nice goal for the 0.4 release, even if we have to build it ourselves (e.g. against MKL, etc.) On Monday, April 21, 2014 at 5:00:47 PM UTC-4, Steven G. Johnson wrote: > > > > On Monday, April 21, 2014 4:40:38 PM UTC-4, Tobias Kn

Re: [julia-users] Re: Non-GPL Julia?

developers or contributors at the moment (in fact several people have said they would strongly prefer to not remove any other code from Base until after 0.4.0 is released, and I agree with that), but help and contributions are always welcome. On Wednesday, April 15, 2015 at 6:51:44 AM UTC-7, S

Re: [julia-users] Re: Non-GPL Julia?

pr 17, 2015 at 11:08 AM, Sebastian Good wrote: Certainly the licensing is important from a commercial aspect, but I think this is also an interesting discussion from a  core vs packages perspective. Python is separate from numpy, but indeed no one is under the illusion that they should work agains

Re: [julia-users] zero cost subarray?

This was discussed a few weeks ago https://groups.google.com/d/msg/julia-users/IxrvV8ABZoQ/uWZu5-IB3McJ I think the bottom line is that the current implementation *should* be 'zero-cost' once a set of planned improvements and optimizations take place. One of the key ones is a tuple overhaul. F

Re: [julia-users] Can't make something out of nothing

Boy that sure seems confusing! On Thursday, April 16, 2015 at 4:14:21 PM UTC-4, Jameson wrote: > > Nothing was renamed to Void, to better reflect its place in C-interop. > It's instance is still named `nothing`. > >

Re: [julia-users] zero cost subarray?

the other hand, while SubArrays allocate nearly 2x more memory than ArrayViews, the speed of the two (replacing `slice` with `view` above) is, for me, nearly identical. --Tim On Friday, April 17, 2015 08:30:27 PM Sebastian Good wrote: > This was discussed a few weeks ago > &

Re: [julia-users] zero cost subarray?

type with a pointer, 2 ints and a tuple costs so much memory though. On Sunday, April 19, 2015 at 11:38:17 AM UTC-6, Tim Holy wrote: It's not just escape analysis, as this (new) issue demonstrates: https://github.com/JuliaLang/julia/issues/10899 --Tim On Sunday, April 19, 2015 12:33:51 PM

Re: [julia-users] zero cost subarray?

overhead of this part, the compiler may need to introduce additional optimization. Dahua  On Monday, April 20, 2015 at 6:39:35 AM UTC+8, Sebastian Good wrote: —track-allocation still requires guesswork, as optimizations can move the allocation to a different place than you would expect. On April 19

Re: [julia-users] Re: Non-GPL Julia?

+1 On April 20, 2015 at 9:18:10 AM, Jay Kickliter (jay.kickli...@gmail.com) wrote: Thanks Viral On Sunday, April 19, 2015 at 10:05:23 AM UTC-6, Viral Shah wrote: And it is merged now.  On Saturday, April 18, 2015 at 4:22:26 PM UTC+5:30, Scott Jones wrote: That's great! That solves our dilemma fo

Re: [julia-users] Auto warn for unstable types

Iain, I love this idea! Even languages like JavaScript and Visual Basic which embraced dynamic typing added directives to help users avoid the most obvious problems. With the wonderful richness of Julia's type system, it would be nice to be able to 'opt in' to a fully enforced function or modu

[julia-users] Re: Is there a plotting package that works for a current 0.4 build?

Gadfly is very close or nearly there, though it relies on changes to some downstream packages and I don't know if those have all been updated such that you'll get the edge versions if you grab Gadfly. https://github.com/dcjones/Gadfly.jl/pull/587 https://github.com/dcjones/Gadfly.jl/commit/4daa1

[julia-users] idiom for range + offset

I find myself creating ranges of the form i:i+num-1. That is, the ith thing, and num more. Whenever I see a +1 or -1 I worry about careless off by one errors, so I wonder if there is a function or operator to capture this idiom, or open and closed ranges in general?

Re: [julia-users] idiom for range + offset

Perfect, thanks! On April 29, 2015 at 10:27:04 AM, René Donner (li...@donner.at) wrote: I believe range(i,num) is what you are looking for. Am 29.04.2015 um 16:22 schrieb Sebastian Good : > I find myself creating ranges of the form i:i+num-1. That is, the ith thing, > and nu

[julia-users] performance of functions

I ran into this issue today (http://stackoverflow.com/questions/26173635/performance-penalty-using-anonymous-function-in-julia) whereby functions -- whether anonymous or not -- generate lots of garbage when called indirectly. That is when using type signatures like clever_function(f::Function)

Re: [julia-users] performance of functions

AM, Tim Holy (tim.h...@gmail.com) wrote: Check the SO post again; there are now many suggested workarounds, some of which are not a big hit to readability. And no, this won't be fixed in 0.4. --Tim On Wednesday, April 29, 2015 08:57:46 PM Sebastian Good wrote: > I ran into th

[julia-users] type stable leading_zeros etc.

Recent 0.4 changes made expressions like Int32(1) + Int32(2) type stable, i.e returning Int32 instead of Int64 as they did previously (on a 64-bit system, anyway). However leading_zeros seems to always return an Int64. I wonder if it makes sense to convert the result of leading_zeros to the same

Re: [julia-users] type stable leading_zeros etc.

Existing compiler intrinsics work this way (__lzcnt, __lzcnt64, __lzcnt16), It came up for me in the following line of code in StreamingStats     ρ(s::Uint32) = uint32(uint32(leading_zeros(s)) + 0x0001) The outer uint32 is no longer necessary in v0.4 because the addition no longer expands 3

Re: [julia-users] type stable leading_zeros etc.

And I guess as a matter of practicality, a vectorized leading_zeros instruction should leave its results in the same sized registers as it started, or it would only be possible on Int64s, though I don’t know if LLVM is doing that just yet. On April 30, 2015 at 2:36:53 PM, Sebastian Good (sebast

Re: [julia-users] Re: Performance of Distributed Arrays

Steven, are you working on such things at the moment? On Friday, May 1, 2015 at 4:50:39 AM UTC-4, Steven Sagaert wrote: > > I'd be nice to see a distributed array implemented on top of MPI (or > similar high perf distribution libs) like Fortran co-arrays but since I'm > out of academia and do

Re: [julia-users] type stable leading_zeros etc.

reaks, fix it, repeat. It will potentially cause some breakage in packages, but this is a good time for that and it shouldn't be too bad. On Thu, Apr 30, 2015 at 2:39 PM, Sebastian Good wrote: And I guess as a matter of practicality, a vectorized leading_zeros instruction should leave its

[julia-users] Re: Any Julians attending CVPR 2015?

Hi Tracy, I am a regular Julia user and will be attending CVPR, feel free to find me at the conference. (Also, I have seen Dahua Lin at previous CVPRs, but I am not sure he will attend this year.) Best, Sebastian Nowozin On Saturday, 16 May 2015 12:19:30 UTC+1, Tracy Wadleigh wrote: > &

[julia-users] SharedArray definition and assignation of values. Is this behavior a bug?

It seems that there is a bug when you define several SharedArray in one call (for example using include("file.jl")). Or maybe I'm missing something about how to use SharedArray. I'm using Windows 7. Let me explain with an example: This code has no problem. It assign correctly the values of Shar

Re: [julia-users] SharedArray definition and assignation of values. Is this behavior a bug?

I used #11280 and it fixes the problem. Thank you, Jacob! Sebastian On Tuesday, May 19, 2015 at 12:06:52 AM UTC-5, Jacob Quinn wrote: > > I'm not able to reproduce the above behavior with my latest changes to > #11280, so that's a good sign! > > If you're feelin

Re: [julia-users] SharedArray definition and assignation of values. Is this behavior a bug?

Thanks, Tim. I'll try later 0.4. I'm using 0.3.8 and #11280 fix the issue. Sebastian

[julia-users] Re: Sampling a Discrete Probability Distribution Using a Vector

nteresting idea (trading runtime for space), let us know if you find literature on this topic. Best, Sebastian On Tuesday, 26 May 2015 16:42:20 UTC+1, Pontus Stenetorp wrote: > > Everyone, > > tl;dr: When trading memory for computation time by sampling from a > discrete probab

[julia-users] Re: julia on arm - some more progress

Same here on a Raspberry Pi 2. Sebastian On Wednesday, 27 May 2015 14:37:53 UTC+1, Seth wrote: > > > > On Monday, May 25, 2015 at 11:51:56 PM UTC-7, Viral Shah wrote: >> >> I believe that the build process for arm is reasonably straightforward. >> Just `make` an

Re: [julia-users] Re: Sampling a Discrete Probability Distribution Using a Vector

Hi Jason, great answer, I learned something useful today :-) Sebastian On Wed, May 27, 2015 at 4:07 PM, Jason Merrill wrote: > You might want to take a look at > http://en.m.wikipedia.org/wiki/Alias_method > > There's a nice, detailed exposition at > http://www.keithsc

[julia-users] Re: Announcement: Escher.jl - a toolkit for beautiful Web UIs in pure Julia

Looks pretty interesting and in line with a lot of current web framework thinking. Are there any pieces inside Escher which help with compiling Julia code to JavaScript? Or is it all "driven" from the server? On Monday, June 8, 2015 at 12:23:21 PM UTC-4, Shashi Gowda wrote: > > Hello all! > > I

Re: [julia-users] Current Performance w Trunk Compared to 0.3

I've seen the same. Looked away for a few weeks, and my code got ~5x slower. There's a lot going on so it's hard to say without detailed testing. However this code was always very sensitive to optimization to be able to specialize code which read data of different types. I got massive increases

[julia-users] libgfortran in a linux install

julia-cb77503114/lib/julia/libgfortran.so.3). Why is it not included in the tarball? Is there a make flag that can force this? Or is it avoided for a licensing reason? Thanks, Sebastian

Re: [julia-users] libgfortran in a linux install

No apparent problems ./contrib/fixup-libgfortran.sh /home/vagrant/julia/julia-cb77503114/lib/julia ‘/lib/x86_64-linux-gnu/libgcc_s.so.1’ -> ‘/home/vagrant/julia/julia-cb77503114/lib/julia/libgcc_s.so.1’ ‘/usr/lib/x86_64-linux-gnu/libgfortran.so.3’ -> ‘/home/vagrant/julia/julia-cb77503114/lib/jul

Re: [julia-users] libgfortran in a linux install

/libgfortran.so.3  does not exist? -E On Thu, Jun 25, 2015 at 3:18 PM, Sebastian Good wrote: No apparent problems ./contrib/fixup-libgfortran.sh /home/vagrant/julia/julia-cb77503114/lib/julia ‘/lib/x86_64-linux-gnu/libgcc_s.so.1’ -> ‘/home/vagrant/julia/julia-cb77503114/lib/julia/libgcc_s.s

[julia-users] Re: Legend Layers Gadfly

ine, Theme(default_color=color("green"))) plot(l1, l2, Guide.manual_color_key("hello",["line1","line2"], ["red", "green"])) sebastian On Monday, July 6, 2015 at 7:33:35 AM UTC-5, m wrote: > > Hello, > > I am using Gadfly pack

[julia-users] Re: Legend Layers Gadfly

ine, Theme(default_color=color("green"))) plot(l1, l2, Guide.manual_color_key("legend name",["line1","line2"], ["red", "green"])) sebastian On Monday, July 6, 2015 at 7:33:35 AM UTC-5, m wrote: > > Hello, > > I am using G

[julia-users] P2P Parallelcomputing

functions. Thank you, Sebastian

Re: [julia-users] P2P Parallelcomputing

with remote references. Sebastian On 4 Aug 2015, at 11:14, Tim Holy wrote: > Do the @async and @sync macros cover that for you? > > --Tim > > On Tuesday, August 04, 2015 12:45:26 AM Sebastian Vollmer wrote: >> Is it possible to implement P2P parallel computing in Julia

[julia-users] reinterpret SubArray

I found myself trying to reinterpret a subarray today, and it didn't work. There are obviously plenty of cases where this makes no sense, but it would be convenient where it did. Is this on someone's roadmap? For instance: reinterpret(Int16, sub(readbytes(...), 5:10))

Re: [julia-users] Embarrassingly parallel workload

may be difficult to implement for a language as dynamic as Julia, but it is hard to argue against this simplicity from the users' point of view. As Clang/LLVM now support OpenMP (https://clang-omp.github.io/), one perhaps can recycle the same OpenMP runtime for such lightweight parallelism

Re: [julia-users] Embarrassingly parallel workload

Thanks Ryan for the pointer, this is awesome work, I am looking forward to this becoming part of the Julia release in Q3. Sebastian On Thu, Aug 20, 2015 at 3:34 PM, Ryan Cox wrote: > Sebastian, > > This talk from JuliaCon 2015 discusses progress on OpenMP-like threading: > Kiran

[julia-users] Job posting: science startup

I'm hiring Julia partisans to join me in a stealth-mode science-focused startup doing computational math and visualization -- both interactive and simulation based, including code running on large clusters. Why Julia? We're in a math-heavy domain, speed matters, and we want well-rounded hackers

[julia-users] Potential bug in Task/iterators?

nts on the produce statements, and how to fix the above code? Any help is appreciated. If it would help I could open an issue on the Julia issue tracker. Thanks, Sebastian

[julia-users] Re: Potential bug in Task/iterators?

Hi, I filed this as an issue with code to reproduce a different behaviour (hanging) at https://github.com/JuliaLang/julia/issues/7498 Best, Sebastian On Tuesday, 1 July 2014 20:05:48 UTC+1, Sebastian Nowozin wrote: > > > Hi everyone, > > I followed the pattern prop

[julia-users] Re: Potential bug in Task/iterators?

k from the REPL but the hanging issue files remains when I call "julia.exe bug1.jl". Thanks for your help, Sebastian On Tuesday, 1 July 2014 20:05:48 UTC+1, Sebastian Nowozin wrote: > > > Hi everyone, > > I followed the pattern proposed at > http://slendermeans.org/

[julia-users] Re: How do you do interactive development in Julia?

ance of the keyboard statement. I know Julia has a debugger, and it may support this use, but I have not tried whether this is possible to use it for a similar workflow. After such a prototype run I typically extract the verified code into a test case without any keyboard statements. Best, Seba

[julia-users] Re: How do you do interactive development in Julia?

Hah, I just checked the help message of Julia once again and indeed the "-L" option seems to accomplish exactly what I want. Sorry for the noise ;-) Sebastian On Saturday, 5 July 2014 21:36:41 UTC+1, Sebastian Nowozin wrote: > > > Hi, > > I use a similar method; howeve

Re: [julia-users] Re: How do you do interactive development in Julia?

experimental results? Thanks, Sebastian On Mon, Jul 7, 2014 at 10:39 PM, Andrei Zh wrote: > Thanks Tim, this is another interesting capability, and I'm definitely > looking forward to try it out in Julia REPL. It's a bit unusual though, so > I'm still looking for smoother w

[julia-users] NotShared Memory

thread for scheduling and all the computations can be done locally. I would like the results to be stored in local array and be fetched to the main thread once all calculations have finished. For this I need to create a local array on each worker. But I don't know how. Thanks, Sebastian

[julia-users] NotShared Memory

like fetch these arrays and combine them then. I can create shared variables using @everywhere i=1 The only possibility that came to my mind is to use take and put using appropriate RemoteRefs, but this seems overly complicated. Thank you, Sebastian

[julia-users] Re: NotShared Memory

not work. Best wishes, Sebastian - times=linspace(0.1,2.0,10) # times in secs representing different difficult computations sort!(times,rev=true) np = nprocs() n = length(times) #create local variables for p=1:np if p != myid

[julia-users] Access to Distributed Arrays

I am trying to access parts of a distributed array that belongs to the current worker res=dzeros((1,length(workers())), workers(), [1,length(workers())]) (for some reason res=dzeros((length(workers())), workers(), [length(workers())]) throws an error ) @spawnat 2 localpart(res)[1]+=rand()

Re: [julia-users] Access to Distributed Arrays

Thanks a lot. That was helpful.

[julia-users] Time constraint Julia computations

Array{RemoteRef,nw} which does not seem to work and I don't understand why. 3) How do I do a read only variable that can be read by all workers Thank you, Sebastian @everywhere function dowork(res,nZs) global toStop global steps while !toStop for j=1:

[julia-users] Re: Time constraint Julia computations

Additional Remark Removing the sleep(0.1) in the dowork() function results in an infinite loop. Why is that and what can be done? @everywhere function dowork(res,nZs) global toStop global steps while !toStop for j=1:steps localpart(res)[1]+=rand()

[julia-users] Re: How quickly calculate the entropy for long vectors ? -sum(x->x*log(2,x), [count(x->x==c,s)/length(s) for c in unique(s)])

formula is given as equation (6) in http://www.nowozin.net/sebastian/papers/nowozin2012infogain.pdf In terms of best statistical accuracy, the NSB Bayes estimator is probably the best over a broad range of input distributions. Good luck, Sebastian On Friday, 5 September 2014 05:42:20 UTC+1, paul

Re: [julia-users] Re: Article on `@simd`

Based on this thread, I spent a few days playing around with a toy algorithm in Julia and C++ (trying OpenLC & OpenMP), and finally ISPC. My verdict? ISPC is nothing short of magical. While my code was easily parallelizable (working independently on each element of a large array), it was not re

Re: [julia-users] Re: Article on `@simd`

be produced incrementally. We'd need help from the Julia language/standard library itself to expose masked vector operations. *Sebastian Good* On Tue, Sep 23, 2014 at 2:52 PM, Jeff Waller wrote: > Could this theoretical thing be approached incrementally? Meaning here's > a p

Re: [julia-users] Re: Article on `@simd`

... though I suspect to really profit from masked vectorization like this, it needs to be tackled at a much lower level in the compiler, likely even as an LLVM optimization pass, guided only by some hints from Julia itself. *Sebastian Good* On Wed, Sep 24, 2014 at 10:16 AM, Sebastian Good

Re: [julia-users] Re: Article on `@simd`

rized and so it's much easier to figure out. (Figuring out whether it was a good idea or not is left to the programmer!) *Sebastian Good* On Wed, Sep 24, 2014 at 12:52 PM, Jake Bolewski wrote: > You couldn't really preserve the semantics as Julia is a much more dynamic > language.

[julia-users] Re: Geometry package

If you're focused on 3D cartesian space, would some of the existing graphics-focused packages do the trick? these might be "easily" wrapped in Julia. On Tuesday, September 30, 2014 8:05:51 PM UTC-4, Yakir Gagnon wrote: > > A Geometry package has been discussed here >

[julia-users] Deploying Julia libraries

With the release of v0.4 imminent, I thought I'd see what the latest thinking was on deploying Julia libraries (or even executables) to foreign machines. I see several steps required to run a Julia program: 1. Install Julia. This is easy enough to do in a system image. 2. Add/clone packages. Thi

Re: [julia-users] Re: Deploying Julia libraries

Setting JULIA_PKGPATH lets me put everything in a more amenable spot, but transporting everything over to another identical machine results in inconsistent behavior with precompiled binaries. They are always “stale”. Is there a good resource to consult to understand binary staleness? Thanks On

Re: [julia-users] Re: The Julia Community Standards

Thanks Stefan. On Saturday, October 10, 2015 at 12:32:05 PM UTC-5, Stefan Karpinski wrote: > > That was not an ad hominem attack, it was a request for you to stop > talking over everyone else on a subject about which you've already > demonstrated a considerable lack of awareness or insight. When

[julia-users] Re: ANN: NullableArrays.jl package

This brings to mind a question that commonly comes up in scientific computing: nullable arrays simulated through means of a canonical "no-data value", e.g in a domain where all values are expected to be negative, using +. It's ugly, but it's really common. From what I can see of the impleme

[julia-users] Re: What features are interesting in a VS Code plug-in?

I would imagine most of the things on this list would apply readily to any IDE, but since you ask. 1) One of the best IDE experiences out of MSFT was the F# IDE, where you could easily interrogate expression types by hovering. this helped immensely in that statically typed language. Now Julia

Re: [julia-users] Re: ANN: NullableArrays.jl package

{Float32, .0f} vs NulllableBits{Float32, .0f}. But this is just speculation on my part; was curious if the group had looked at this representation in their explorations. On October 18, 2015 at 3:54:23 PM, David Gold (david.gol...@gmail.com) wrote: @Sebastian: If I understand you correctly

[julia-users] MXNet.jl FeedForward question, sum of loss functions

) that performs this implicit summation? (I am interested in defining multiple loss functions and additional regularization terms on parameter nodes throughout the network and optimize their sum.) Thanks a lot, Sebastian

[julia-users] [ANN] ArcadeLearningEnvironment.jl

available at the ALE homepage. Any feedback is welcome. Sebastian

[julia-users] Reload and parallel processing

Loading a script using reload executes the code on all workers. How do I only execute code on one worker? Pseudo code algorithm.jl: function fun(s::Int64) end run.jl: result=pmap(fun, [1:100]) #do something with result one the julia shell I execute addprocs(12) reload(algorithm.jl) reloa

[julia-users] Surprising machine code for bitstype

When I've run benchmarks with custom bitstypes, they seem to run very quickly. But I wouldn't have guessed it from the machine code I can preview at the REPL. Can anyone explain what I'm seeing here? (I'm dumping @code_llvm as it's more instructive; the @code_native is very large). Converting a

Re: [julia-users] Surprising machine code for bitstype

lia> convert(Foo, 0x10) Foo(0x10) julia> convert(Uint8, 0x10) 0x10 *Sebastian Good* On Mon, Oct 20, 2014 at 11:29 AM, Stefan Karpinski wrote: > julia> bitstype 8 Foo > > julia> convert(Foo, 100) > ERROR: `convert` has no method matching convert(::Type{Foo}, ::Int64) >

Re: [julia-users] Surprising machine code for bitstype

https://github.com/JuliaLang/julia/issues/8742 Let me know if it needs any changes. FWIW I'm on Julia 0.3.1, OS X. Cheers! *Sebastian Good* On Mon, Oct 20, 2014 at 11:43 AM, Jameson Nash wrote: > Can you open an issue? It looks like it's still emitting a gc-frame, even >

[julia-users] map performance

I created an array `i` of 500M 32-bit ints, then converted the whole array (into a new array) to float32s. The naive call to `float32(i)` ran at one speed, but map at quite another! julia> i = Int32[1:5]; julia> @time float32(i); elapsed time: 1.669573141 seconds (200128 bytes alloc

[julia-users] Re: map performance

, 2014 10:36:42 PM UTC-4, Sebastian Good wrote: > > I created an array `i` of 500M 32-bit ints, then converted the whole array > (into a new array) to float32s. The naive call to `float32(i)` ran at one > speed, but map at quite another! > > julia> i = Int32[1:5]; >

  1   2   >