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Removing Caveats
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- Downstream binary libraries that depend on BLAS such as SuiteSparse (solving sparse linear systems) and ARPACK (for large scale eigenvalue computations) will currently not work once MKL.jl has been installed. We are working on removing these limitations.



Tested on JuliaLinearAlgebra#14 and there are no issues.
```julia
julia> using LinearAlgebra; BLAS.vendor()
:mkl

julia> using Arpack, SparseArrays

julia> βŠ—(A, B) = kron(A, B);

julia> function Hub_ED(U, ΞΌ, L,)
           id = [1 0; 0 1]
           c = [0 0; 1 0]

           c_up = c βŠ— id
           c_dn = id βŠ— c
           idΒ² = id βŠ— id

           n_up = c_up' * c_up
           n_dn = c_dn' * c_dn

           Γ› =  U*(n_up * n_dn) - ΞΌ*(n_up + n_dn)

           c_dg_up(i) = foldl(βŠ—, sparse.([i==j ? c_up' : idΒ² for j in 1:L]))
           cup(i)     = foldl(βŠ—, sparse.([i==j ? c_up  : idΒ² for j in 1:L]))
           c_dg_dn(i) = foldl(βŠ—, sparse.([i==j ? c_dn' : idΒ² for j in 1:L]))
           cdn(i)     = foldl(βŠ—, sparse.([i==j ? c_dn  : idΒ² for j in 1:L]))
           Γ›f(i)      = foldl(βŠ—, sparse.([i==j ? Γ›     : idΒ² for j in 1:L]))

           function c_dg_c(i)
               out = c_dg_up(i)*cup(i+1) + c_dg_dn(i)*cdn(i+1)
               out + out'
           end

           H = -sum(c_dg_c, 1:(L-1)) + sum(Γ›f, 1:L)
           @show typeof(H)
           (Ξ», Ο•), t = @timed Arpack.eigs(H, nev=1, which=:SR)
           Ξ», Ο•, t
       end
Hub_ED (generic function with 1 method)

julia> Hub_ED(1, 1, 8)
typeof(H) = SparseMatrixCSC{Int64,Int64}
([-15.813000555255263], [-1.949487752371787e-18; -2.0668833887408264e-18; … ; 2.035974575802704e-18; 1.216026630767711e-18], 0.340870967)
```



- It is not possible to revert the effect of install MKL.jl. To return to OpenBLAS, it is necessary to reinstall Julia.
Enabling openBlas is possible using `MKL.enable_openblas_startup()`


Tested on Windows:
```julia
julia> using MKL

julia> MKL.enable_openblas_startup()
[ Info: Replacing libblas_name in C:\Julia-1.3.0-rc3\bin\..\share\julia\base\build_h.jl
β”Œ Info: Building `inference.o`:
β”” `'C:\Julia-1.3.0-rc3\bin\julia.exe' -C native --output-ji 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\basecompiler.ji' --output-o 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\basecompiler.o' compiler/compiler.jl`
essentials.jl
ctypes.jl
generator.jl
reflection.jl
options.jl
promotion.jl
tuple.jl
pair.jl
traits.jl
range.jl
expr.jl
error.jl
bool.jl
number.jl
int.jl
operators.jl
pointer.jl
refvalue.jl
indices.jl
array.jl
abstractarray.jl
bitarray.jl
bitset.jl
abstractdict.jl
abstractset.jl
iterators.jl
namedtuple.jl
docs/core.jl
ordering.jl
sort.jl
compiler/utilities.jl
compiler/validation.jl
compiler/inferenceresult.jl
compiler/params.jl
compiler/inferencestate.jl
compiler/typeutils.jl
compiler/typelimits.jl
compiler/typelattice.jl
compiler/tfuncs.jl
compiler/abstractinterpretation.jl
compiler/typeinfer.jl
compiler/optimize.jl
compiler/ssair/driver.jl
compiler/ssair/ir.jl
compiler/ssair/domtree.jl
compiler/ssair/slot2ssa.jl
compiler/ssair/queries.jl
compiler/ssair/passes.jl
compiler/ssair/inlining.jl
compiler/ssair/verify.jl
compiler/ssair/legacy.jl
compiler/bootstrap.jl
β”Œ Info: Building `sys.o`:
β”” `'C:\Julia-1.3.0-rc3\bin\julia.exe' -C native --output-ji 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\sys.ji' --output-o 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\sys.o' -J 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\basecompiler.ji' --startup-file=no sysimg.jl`
coreio.jl
exports.jl
essentials.jl
ctypes.jl
gcutils.jl
generator.jl
reflection.jl
options.jl
promotion.jl
tuple.jl
expr.jl
pair.jl
traits.jl
range.jl
error.jl
bool.jl
number.jl
int.jl
operators.jl
pointer.jl
refvalue.jl
refpointer.jl
checked.jl
indices.jl
array.jl
abstractarray.jl
subarray.jl
views.jl
baseext.jl
ntuple.jl
abstractdict.jl
iterators.jl
namedtuple.jl
hashing.jl
rounding.jl
float.jl
twiceprecision.jl
complex.jl
rational.jl
multinverses.jl
abstractarraymath.jl
arraymath.jl
simdloop.jl
reduce.jl
reshapedarray.jl
reinterpretarray.jl
bitarray.jl
bitset.jl
multimedia.jl
some.jl
dict.jl
abstractset.jl
set.jl
char.jl
strings/basic.jl
strings/string.jl
strings/substring.jl
build_h.jl
version_git.jl
osutils.jl
c.jl
io.jl
iobuffer.jl
intfuncs.jl
strings/strings.jl
strings/search.jl
strings/unicode.jl
strings/util.jl
strings/io.jl
parse.jl
shell.jl
regex.jl
pcre.jl
show.jl
arrayshow.jl
methodshow.jl
cartesian.jl
multidimensional.jl
permuteddimsarray.jl
broadcast.jl
missing.jl
version.jl
sysinfo.jl
libc.jl
env.jl
linked_list.jl
condition.jl
threads.jl
lock.jl
task.jl
weakkeydict.jl
logging.jl
libuv.jl
uv_constants.jl
asyncevent.jl
iostream.jl
stream.jl
filesystem.jl
cmd.jl
process.jl
grisu/grisu.jl
secretbuffer.jl
floatfuncs.jl
math.jl
reducedim.jl
accumulate.jl
ordering.jl
sort.jl
fastmath.jl
Enums.jl
gmp.jl
mpfr.jl
combinatorics.jl
hashing2.jl
irrationals.jl
mathconstants.jl
printf.jl
meta.jl
channels.jl
deepcopy.jl
download.jl
summarysize.jl
errorshow.jl
stacktraces.jl
initdefs.jl
threadcall.jl
uuid.jl
loading.jl
util.jl
asyncmap.jl
experimental.jl
deprecated.jl
docs\basedocs.jl
client.jl
docs\Docs.jl
Base  ─────────── 25.654957 seconds
Base64  ─────────  3.794240 seconds
CRC32c  ─────────  0.010188 seconds
SHA  ────────────  0.181228 seconds
FileWatching  ───  0.091911 seconds
Unicode  ────────  0.010193 seconds
Mmap  ───────────  0.074751 seconds
Serialization  ──  0.862091 seconds
Libdl  ──────────  0.030937 seconds
Markdown  ───────  1.054587 seconds
LibGit2  ────────  2.649440 seconds
Logging  ────────  0.506780 seconds
Sockets  ────────  1.877789 seconds
Printf  ─────────  0.012369 seconds
Profile  ────────  0.153111 seconds
Dates  ──────────  2.098834 seconds
DelimitedFiles  ─  0.104160 seconds
Random  ─────────  0.525311 seconds
UUIDs  ──────────  0.019996 seconds
Future  ─────────  0.011412 seconds
LinearAlgebra  ── 12.891522 seconds
SparseArrays  ───  6.296322 seconds
SuiteSparse  ────  1.802302 seconds
Distributed  ────  6.485953 seconds
SharedArrays  ───  0.222248 seconds
Pkg  ──────────── 13.223301 seconds
Test  ───────────  0.961266 seconds
REPL  ───────────  1.154462 seconds
Statistics  ─────  0.162380 seconds
Stdlibs total  ── 57.315055 seconds
Sysimage built. Summary:
Total ───────  82.973635 seconds
Base: ───────  25.654957 seconds 30.9194%
Stdlibs: ────  57.315055 seconds 69.0762%
Build shared library "C:\\Users\\yahyaaba\\.julia\\packages\\PackageCompiler\\CJQcs\\sysimg\\backup\\native\\sys.dll":
  `'C:\Users\yahyaaba\.julia\packages\WinRPM\Y9QdZ\deps\usr\x86_64-w64-mingw32\sys-root\mingw\bin\gcc.exe' --sysroot 'C:\Users\yahyaaba\.julia\packages\WinRPM\Y9QdZ\deps\usr\x86_64-w64-mingw32\sys-root' -shared '-DJULIAC_PROGRAM_LIBNAME="C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\sys.dll"' -o 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\sys.dll' -Wl,--whole-archive 'C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\sys.o' -Wl,--no-whole-archive -std=gnu99 '-IC:\Julia-1.3.0-rc3\include\julia' -DJULIA_ENABLE_THREADING=1 '-LC:\Julia-1.3.0-rc3\bin' -Wl,--stack,8388608 -ljulia -lopenlibm -m64 -Wl,--export-all-symbols`
[ Info: Copying system image: C:\Users\yahyaaba\.julia\packages\PackageCompiler\CJQcs\sysimg\backup\native\sys.dll to C:\Julia-1.3.0-rc3\lib\julia\sys.dll
```
After restart:
```julia
julia> using LinearAlgebra

julia> BLAS.vendor()
:openblas64
```

- The current version of MKL.jl doesn't have access to the same precompilation information as the official binaries and source builds so the REPL will have more latency after MKL.jl has been installed. It should be possible to fix this once Julia 1.1 has been released. See JuliaLinearAlgebra#1.

Tried on Windows and many different installations, only the first boot may take a little longer (less than 20 seconds). The next boots is just the same as normal Julia (less than 5 seconds).
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@aminya
aminya committed Oct 11, 2019
1 parent 1dad6dd commit 9192707
Showing 1 changed file with 2 additions and 10 deletions.
12 changes: 2 additions & 10 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -11,9 +11,9 @@
```julia
julia>]add https://github.com/JuliaComputing/MKL.jl
```
After installation it should build automatically (which takes some time). If building was not triggered automatically (happens when MKL download is done already on the system) run the following command:
After installation it should build automatically (which takes some time). If building was not triggered automatically (happens when MKL download is done already on the system), run the following command:
```julia
] build MKL
julia>] build MKL
```
Then after building restart Julia.

Expand All @@ -29,11 +29,3 @@ julia> BLAS.vendor()
:mkl
```
and all Julia's dense linear algebra routines ranging from matrix multiply, over solving linear systems of equations, to eigenvalue computations will be computed by Intel MKL. In many cases, this will greatly improve the execution time.

### Caveats

- Downstream binary libraries that depend on BLAS such as SuiteSparse (solving sparse linear systems) and ARPACK (for large scale eigevalue computations) will currently not work once MKL.jl has been installed. We are working on removing these limitations.

- It is not possible to revert the effect of install MKL.jl. To return to OpenBLAS, it is necessary to reinstall Julia.

- The current version of MKL.jl doesn't have access to the same precompilation information as the official binaries and source builds so the REPL will have more latency after MKL.jl has been installed. It should be possible to fix this once Julia 1.1 has been released. See https://github.com/JuliaComputing/MKL.jl/issues/1.

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