switch to BinaryBuilder binaries

[stevengj]

Closes #73.

[stevengj]

@ararslan, is there test coverage for the MKL version?

[ararslan]

No, I don't think MKL is available on any CI providers.

[stevengj]

Do you have an MKL version installed that you can try?

[ararslan]

I don't, unfortunately.

[andreasnoack]

No, I don't think MKL is available on any CI providers.

travis-ci/travis-ci#5381 (comment) might be relevant here

[stevengj]

To use this MKL, it seems like the build script should be updated so that you can simply specify the path of an MKL library rather than the one included with Julia...

[stevengj]

Another possibility that occurs to me is to use the mkl_fft Anaconda package with Conda.jl, which has the advantage that I can easily try it locally.

[stevengj]

Updated the PR to add a Conda dependency, so that we can support using MKL even if Julia was not built with MKL support. Now Travis can exercise the MKL API.

[ararslan]

Unfortunate to have to add a dependency on Conda but I don't know of a way around it...

[stevengj]

Note that the Conda dependency is actually quite small if you aren't using it — it only actually runs the Miniconda installer when you decide to add a Conda package.

[stevengj]

Okay to merge?

(As I wrote above, the Conda.jl dependency itself is lightweight because Miniconda is only installed lazily. Conda also has BinDeps and JSON dependency, but the BinDeps support can probably be split into a separate package at some point.)

[staticfloat]

Out of curiosity, how can Conda distribute MKL for free? I thought MKL was proprietary?

[stevengj]

Intel provides Conda packages via https://github.com/IntelPython, so I guess it's okay for Anaconda to get it directly from Intel.

[EthanAnderes]

I ran into a small hiccup trying this out [with MKL]. However, I'm only an avid user so hope I'm not adding noise to the dev process.
When first trying it out I got

               _
   _       _ _(_)_     |  A fresh approach to technical computing
  (_)     | (_) (_)    |  Documentation: https://docs.julialang.org
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.7.0-alpha.154 (2018-06-18 14:53 UTC)
 _/ |\__'_|_|_|\__'_|  |  Commit 77449852cf* (0 days old master)
|__/                   |  x86_64-apple-darwin17.6.0

(v0.7) pkg> build FFTW
  Building FFTW → `~/.julia/dev/FFTW/deps/build.log`
 Resolving package versions...
Downloaded Nullables ────── v0.0.5
Downloaded JSON ─────────── v0.17.2
Downloaded VersionParsing ─ v1.1.1
Downloaded BinaryProvider ─ v0.3.2
Downloaded Conda ────────── v0.8.1
  Building Conda → `~/.julia/packages/Conda/S0nV/deps/build.log`
┌ Error: Error building `FFTW`; see log file for further info
└ @ Pkg.Operations Operations.jl:938

Here is what build.log reads

WARNING: Base.BLAS is deprecated: it has been moved to the standard library package `LinearAlgebra`.
Add `using LinearAlgebra` to your imports.
  likely near /Users/ethananderes/.julia/dev/FFTW/deps/build.jl:17
ERROR: LoadError: ArgumentError: Package Conda not found in current path:
 - Run `Pkg.add("Conda")` to install the Conda package.

Stacktrace:
 [1] require(::Module, ::Symbol) at ./loading.jl:871
 [2] top-level scope at /Users/ethananderes/.julia/dev/FFTW/deps/build.jl:21
 [3] include at ./boot.jl:317 [inlined]
 [4] include_relative(::Module, ::String) at ./loading.jl:1089
 [5] include(::Module, ::String) at ./sysimg.jl:29
 [6] include(::String) at ./client.jl:393
 [7] top-level scope at none:0
in expression starting at /Users/ethananderes/.julia/dev/FFTW/deps/build.jl:17

Now, I went back to check if Conda was installed and got this:

julia> using Conda
ERROR: ArgumentError: Package Conda not found in current path:
 - Run `Pkg.add("Conda")` to install the Conda package.

Stacktrace:
 [1] require(::Module, ::Symbol) at ./loading.jl:871

(v0.7) pkg> add Conda
  Updating registry at `~/.julia/registries/Uncurated`
  Updating git-repo `https://github.com/JuliaRegistries/Uncurated.git`
 Resolving package versions...
  Updating `~/.julia/environments/v0.7/Project.toml`
  [8f4d0f93] + Conda v0.8.1
  Updating `~/.julia/environments/v0.7/Manifest.toml`
  [b99e7846] + BinaryProvider v0.3.2
  [8f4d0f93] + Conda v0.8.1
  [682c06a0] + JSON v0.17.2
  [4d1e1d77] + Nullables v0.0.5
  [81def892] + VersionParsing v1.1.1

(v0.7) pkg> build FFTW
  Building Conda → `~/.julia/packages/Conda/S0nV/deps/build.log`
  Building FFTW ─→ `~/.julia/dev/FFTW/deps/build.log`
 Resolving package versions...

Now everything works great. Getting OpenBlas in LinearAlgebra and can tell I'm working with MKL by the output of plan_rfft (i.e. it would look different if it was FFTW).

julia> LinearAlgebra.BLAS.vendor()
:openblas64

julia> m = rand(Float32, 2^14, 2^14);

julia> p = plan_rfft(m)
FFTW real-to-complex plan for 16384×16384 array of Float32

Here is my version info

julia> versioninfo()
Julia Version 0.7.0-alpha.154
Commit 77449852cf* (2018-06-18 14:53 UTC)
Platform Info:
  OS: macOS (x86_64-apple-darwin17.6.0)
  CPU: Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.0 (ORCJIT, skylake)
Environment:
  JULIA_NUM_THREADS = 2
  JULIA_FFTW_PROVIDER = MKL

[EthanAnderes]

just realized that perhaps this is due to dev FFTW + switching to a different branch in the terminal, not automatically installing new additions in REQUIRE. Sorry for the noise.

[stevengj]

@EthanAnderes, yes, that is JuliaLang/Pkg.jl#367

[stevengj]

@ararslan, okay to merge?

[ararslan]

Yep, looks good to me. Feel free to merge or squash-merge at your leisure.