SIMD Vectorization in Julia
software.intel.com
SIMD Vectorization in Julia
1–10 of 12 posts
Re: SIMD Vectorization in Julia
#2Julia is really shaping up quite nicely.
Re: SIMD Vectorization in Julia
#3This looks great! I used Julia in my Master's thesis and it was very fast and easy to use. One thing however was annoying: The lack of shared memory parallel computing. Unfortunately, in Julia, each parallel process has its own memory such that you have to keep multiple instances of your data and/or move data around all the time. This can be a deal breaker if working with very large data sets and actually is preventing me from using Julia even more. But I'm sure, it's on the right track.
Re: SIMD Vectorization in Julia
#4This looks great! I used Julia in my Master's thesis and it was very fast and easy to use. One thing however was annoying: The lack of shared memory parallel computing. Unfortunately, in Julia, each parallel process has its own memory such that you have to keep multiple instances of your data and/or move data around all the time. This can be a deal breaker if working with very large data sets and actually is preventi…
Doesn't it have mmap?
Re: SIMD Vectorization in Julia
#5This looks great! I used Julia in my Master's thesis and it was very fast and easy to use. One thing however was annoying: The lack of shared memory parallel computing. Unfortunately, in Julia, each parallel process has its own memory such that you have to keep multiple instances of your data and/or move data around all the time. This can be a deal breaker if working with very large data sets and actually is preventi…
Doesn't it have mmap?
It does, in the base library in fact:
https://github.com/JuliaLang/julia/blob/master/base/mmap.jl
Here is the relevant documentation:
http://julia.readthedocs.org/en/latest/stdlib/base/#memory-m...
Re: SIMD Vectorization in Julia
#6as always, intel comes up with nice tutorial from time to time.
Re: SIMD Vectorization in Julia
#7as always, intel comes up with nice tutorial from time to time.
Really nice to see Intel giving Julia some attention.
Re: SIMD Vectorization in Julia
#8This looks great! I used Julia in my Master's thesis and it was very fast and easy to use. One thing however was annoying: The lack of shared memory parallel computing. Unfortunately, in Julia, each parallel process has its own memory such that you have to keep multiple instances of your data and/or move data around all the time. This can be a deal breaker if working with very large data sets and actually is preventi…
In Julia 0.3 there are SharedArrays on Linux/OS X: http://julia.readthedocs.org/en/latest/stdlib/base/#shared-a...
Hopefully there will also be multithreading someday, although right now it's still a work in progress: https://github.com/JuliaLang/julia/tree/threads
Re: SIMD Vectorization in Julia
#9This looks great! I used Julia in my Master's thesis and it was very fast and easy to use. One thing however was annoying: The lack of shared memory parallel computing. Unfortunately, in Julia, each parallel process has its own memory such that you have to keep multiple instances of your data and/or move data around all the time. This can be a deal breaker if working with very large data sets and actually is preventi…
Shared-memory multiprocessing is supported in the latest release on linux and mac. Multi-threading is in development and has seen some significant progress over the past few months.
> But I'm sure, it's on the right track.
Yes, and it is worth pointing out that both this article and the @simd feature were written by Arch Robison - who is also the architect of Intel's Threading Building Blocks.
Re: SIMD Vectorization in Julia
#10as always, intel comes up with nice tutorial from time to time.
The author of this piece, Arch Robison, has been an active contributor to Julia. Not only did he write this tutorial, but he actually contributed the `@simd` implementation himself.[1]
He also presented this information as a talk at Juliacon back in June.[2]