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Giving up on Julia

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Re: Giving up on Julia

#2

Post by sgt101 »

I'm not bothered by "hello world" performance myself, and I my recent issues with Julia have been caused by rapid development meaning that when I had to put it down for a few months lots of things I had done (because I'm mortal) stopped working. I wrote this off to "it's 0.x, getoverit". I've never tried complex text formatting in Julia either! My concerns are more focused on the type system (this I love) and performance for massive computation (I've still not managed to persuade my Hadoop admin to put julia images across our cluster, but I suppose I might win the argument one day!)

Re: Giving up on Julia

#3

Post by vitaut »

sgt101 wrote: post #2

I'm not bothered by "hello world" performance myself, and I my recent issues with Julia have been caused by rapid development meaning that when I had to put it down for a few months lots of things I had done (because I'm mortal) stopped working. I wrote this off to "it's 0.x, getoverit". I've never tried complex text formatting in Julia either! My concerns are more focused on the type system (this I love) and perform…

I wouldn't be bothered about it either if the language, like Java, targeted more the development of long-running services rather than interactive applications (with some exceptions like mobile). But as far as I can see it is advertised for use in interactive applications, possibly as a Python alternative, where responsiveness is important.

Re: Giving up on Julia

#4

Post by dnautics »

sgt101 wrote: post #2

I'm not bothered by "hello world" performance myself, and I my recent issues with Julia have been caused by rapid development meaning that when I had to put it down for a few months lots of things I had done (because I'm mortal) stopped working. I wrote this off to "it's 0.x, getoverit". I've never tried complex text formatting in Julia either! My concerns are more focused on the type system (this I love) and perform…

Yeah the poor performance in this blog post is a total misunderstanding of why and how julia is performant. Is printing "hello world" fast really that important? OK. Then don't use Julia.

You pay for it by having the compiler JIT the code in a highly optimized fashion. If you have actual numerical calculations that are compile-once, run-many-many-many-times, then you will see a huge performance benefit, amortizing the cost of expensive compilation and optimization that happens once at the beginning of the program cycle.

The very title of what he links to "How To Make Python run as fast as Julia" betrays the problem. The goal of Julia is to not have to do that sort of boilerplate/arcane tweaking to get really good performance - the system will do it out of the box.

I'll have to disagree with the notion that Julia is hard to read. I'm currently deploying Julia to run automated hardware verification on a computer chip. Effectively, I've written a DSL using Julia macros that generates assembly code files, compiles, and executes it, and my coworkers (who do not use julia) have found it easy to read my code and understand what's going on. Far easier, in any case, than the equivalent C code using asm blocks.

I do agree about the one-based indexing. I get it, it's what matlab does. But it would be nice to say, be able to throw an option at the top of a program that forces the appropriate indexing.

Re: Giving up on Julia

#6

Post by Xcelerate »

dnautics wrote: post #4
sgt101 wrote: post #2

I'm not bothered by "hello world" performance myself, and I my recent issues with Julia have been caused by rapid development meaning that when I had to put it down for a few months lots of things I had done (because I'm mortal) stopped working. I wrote this off to "it's 0.x, getoverit". I've never tried complex text formatting in Julia either! My concerns are more focused on the type system (this I love) and perform…

Yeah the poor performance in this blog post is a total misunderstanding of why and how julia is performant. Is printing "hello world" fast really that important? OK. Then don't use Julia. You pay for it by having the compiler JIT the code in a highly optimized fashion. If you have actual numerical calculations that are compile-once, run-many-many-many-times, then you will see a huge performance benefit, amortizing th…

> If you have actual numerical calculations that are compile-once, run-many-many-many-times, then you will see a huge performance benefit

I agree, and I haven't found anything like this in other (non-exotic) languages. I recently wrote a function using the @generated macro to produce Wigner-D matrices via the recursion relations. The function dispatches on the size of the matrix (using Type{Val{N}}) and after it compiles once for a particular value of N, all future calls are blazing fast (since the machine code is essentially just a long list of multiply and add instructions).

Re: Giving up on Julia

#7

Post by sgt101 »

vitaut wrote: post #3
sgt101 wrote: post #2

I'm not bothered by "hello world" performance myself, and I my recent issues with Julia have been caused by rapid development meaning that when I had to put it down for a few months lots of things I had done (because I'm mortal) stopped working. I wrote this off to "it's 0.x, getoverit". I've never tried complex text formatting in Julia either! My concerns are more focused on the type system (this I love) and perform…

I wouldn't be bothered about it either if the language, like Java, targeted more the development of long-running services rather than interactive applications (with some exceptions like mobile). But as far as I can see it is advertised for use in interactive applications, possibly as a Python alternative, where responsiveness is important.

I haven't got the same perception - I think it's aimed at things like simulator and solvers. Those things tend to have front ends (that is true) but not front ends that support 100's of users.

Re: Giving up on Julia

#9

Post by KenoFischer »

Happy to address these points:

  - Startup performance/memory usage
Yes, we are definitely very acutely aware of these. Julia is not currently optimized for frequently run short scripts. That's the price on pays for having to bring up the entire runtime system (initializing the compiler, RNG, external libraries etc). The good news is that there will be a solution to this soon, which is to statically compile your julia program. The area where this really comes up for most people using is package load times. We're very actively working on making that faster.

  - Syntax
A little subjective, so not sure how much I can say here. I can say that I'm not a huge fan of our multi-line comment syntax. It's not entirely clear what a better syntax would be though (the original issue on this had some suggestions, but some of them were worse).

  - One-based indexing
I think there has been plenty said on this topic, though interestingly this is one of the only times I've seen the argument made in a way that I actually agree with. That said, I do think there is an easy way to deal with this though. For packages that needs arrays of indices, it would be quite easy to define an `IndexArray` type that does the translation automatically.

  - String Formatting
Yep, you're right, it's a mess. It'll have to be cleaned up.

  - Unsafe C Interface
There's two projects (Clang.jl and Cxx.jl) which can help with this. The former automatically generates ccall definitions for you, the latter just parses the header and generates the call directly.

  - Slowing down in development
I'm really not sure where that impression comes from. Perhaps it is that we're adding fewer features, but rather working on cleaning up existing features. Also, I personally at least have been doing a lot of work outside of base (particularly on the debugger). Not sure. Would love to know.

Re: Giving up on Julia

#10

Post by acomjean »

dnautics wrote: post #4
sgt101 wrote: post #2

I'm not bothered by "hello world" performance myself, and I my recent issues with Julia have been caused by rapid development meaning that when I had to put it down for a few months lots of things I had done (because I'm mortal) stopped working. I wrote this off to "it's 0.x, getoverit". I've never tried complex text formatting in Julia either! My concerns are more focused on the type system (this I love) and perform…

Yeah the poor performance in this blog post is a total misunderstanding of why and how julia is performant. Is printing "hello world" fast really that important? OK. Then don't use Julia. You pay for it by having the compiler JIT the code in a highly optimized fashion. If you have actual numerical calculations that are compile-once, run-many-many-many-times, then you will see a huge performance benefit, amortizing th…

>The goal of Julia is to not have to do that sort of boilerplate/arcane tweaking to get really good performance

As someone who is new to python (for bioinformatics), and find python is a fine language... but..

The do it "this way not that way" method of implementation of the same algorithms to get it to run fast makes writing performant python a tedious exercise in research and profiling. The article cited suggests Cpython, numby and numpy [1] as ways to make it faster.

Why not C using GPU acceleration as the time spent coding would probably be the same? Thats what I love about plain python, its fast to write and has some good data structures.

I haven't tried Julia, but someday its on my list of languages to learn more about.

[1]https://www.ibm.com/developerworks/community/blogs/jfp/entry...

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