# How to utilize "MKLSparse.jl"?

**URL:** <https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263>\
**Category:** General Usage\
**Tags:** question\
**Created:** [August 3, 2022, 8:07pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263 "2022-08-03T20:07:15Z")\
**Posts on this page:** 15\
**Page:** 1

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [August 3, 2022, 8:07pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/1 "2022-08-03T20:07:16Z")

</div>

I have some sparse matrices and I thought using “MKLSparse.jl” could faster the execution, but it did not. However, in the documentation, there is this note

> The integer type that should be used in order for MKL to be called is the same as used by the Julia BLAS library, see `Base.USE_BLAS64`.  
> I am not sure if it is because of this issue. If so, how to set it given that I am using vs code?

```julia
julia> BLAS.lbt_get_config()
LinearAlgebra.BLAS.LBTConfig
Libraries:
└ [ILP64] mkl_rt.2.dll

```

---

<div class="post-metadata">

**Author:** ![carstenbauer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/carstenbauer/32/4981_2.png) [@carstenbauer](https://discourse.julialang.org/u/carstenbauer)\
**Post date:** [August 5, 2022, 2:06pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/3 "2022-08-05T14:06:06Z")

</div>

> [@Amro](#):
>
> I have some sparse matrices and I thought using “MKLSparse.jl” could faster the execution

Execution of what exactly?

Works fine for a sparse-dense matrix multiplication for me:

```julia
julia> using BenchmarkTools

julia> using SparseArrays

julia> S = sprand(10_000, 10_000, 0.01);

julia> D = rand(10_000, 10_000);

julia> @btime $S * $D;
  10.275 s (2 allocations: 762.94 MiB)

julia> using MKLSparse

julia> @btime $S * $D;
  485.737 ms (2 allocations: 762.94 MiB)

```

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<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [August 5, 2022, 2:56pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/4 "2022-08-05T14:56:46Z")

</div>

- I have similar to your results without `MKLSparse`, but your result is faster with it. Any idea?
- Does my results below means `MKLSparse` works correctly in my case?

```julia
julia> @btime $S * $D;
  10.912 s (2 allocations: 762.94 MiB)

julia> using MKLSparse

julia> @btime $S * $D;
  2.834 s (2 allocations: 762.94 MiB)

```

---

<div class="post-metadata">

**Author:** ![carstenbauer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/carstenbauer/32/4981_2.png) [@carstenbauer](https://discourse.julialang.org/u/carstenbauer)\
**Post date:** [August 5, 2022, 8:30pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/5 "2022-08-05T20:30:19Z")

</div>

I’d assume yes. But it’s hard to say given that you haven’t provided much information. For example, it would be relevant to know which CPU you’re running on. (My CPU has probably more threads etc. than yours)

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<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [August 6, 2022, 2:26pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/6 "2022-08-06T14:26:10Z")

</div>

Thanks for your reply. Please find my CPU details below.

Intel(R) Core™ i7-10750H CPU @ 2.60GHz 2.59 GHz

```julia
julia> Sys.cpu_info()
12-element Vector{Base.Sys.CPUinfo}:
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz: 
        speed user nice sys idle irq
     2592 MHz 6221562 0 9454234 218662796 3367234 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz: 
        speed user nice sys idle irq
     2592 MHz 6820937 0 5096546 222420734 148750 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 10452000 0 5743921 218142296 112703 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 9861718 0 4013812 220462687 82734 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 12091000 0 4026343 218220875 37468 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 13246093 0 4133781 216958343 38250 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 15318750 0 4460359 214559125 34562 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 15330390 0 4278515 214729312 39500 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 7359000 0 7165921 219813296 102062 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 6830562 0 4275578 223232078 99515 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 7758718 0 4911546 221667953 89359 ticks
 Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz:
        speed user nice sys idle irq
     2592 MHz 7871406 0 4968968 221497843 172296 ticks
julia> Threads.nthreads()
6

```

I changed threads to 12, but still giving me the same performance.

```julia
julia> Threads.nthreads()
12

```

Is there another issue to check the reason of the slow performance?

---

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [August 11, 2022, 6:48pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/8 "2022-08-11T18:48:32Z")

</div>

@carstenbauer Is there another issue to check the reason of the slow performance?  
Is there a special functions that I can use in `MKLSparse` for muliplication rather than `*` or it is overwrite?

---

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [August 31, 2022, 5:55pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/11 "2022-08-31T17:55:58Z")

</div>

@stevengj  
@lmiq  
@DNF  
@jling  
I am sorry if my mention is not proper. I just sucked at this for long time and I did know why I am not having the same fast speed as my colleague after using “MKLSparse”. I really appreciate any help from you. Thank you!

> [@carstenbauer](#):
>
> ```julia
> julia> @btime $S * $D;
> 10.275 s (2 allocations: 762.94 MiB)
> 
> julia> using MKLSparse
> 
> julia> @btime $S * $D;
> 485.737 ms (2 allocations: 762.94 MiB)
> 
> ```

> [@Amro](#):
>
> ```julia
> julia> @btime $S * $D;
> 10.912 s (2 allocations: 762.94 MiB)
> 
> julia> using MKLSparse
> 
> julia> @btime $S * $D;
> 2.834 s (2 allocations: 762.94 MiB)
> 
> ```

```julia
julia> versioninfo()
Julia Version 1.8.0-beta1
Commit 7b711ce699 (2022-02-23 15:09 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 12 × Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, skylake)
  Threads: 12 on 12 virtual cores
Environment:
  JULIA_EDITOR = code
  JULIA_NUM_THREADS = 12

julia> BLAS.lbt_get_config()
LinearAlgebra.BLAS.LBTConfig
Libraries:
└ [ILP64] libopenblas64_.dll

julia> using MKL

julia> BLAS.lbt_get_config()
LinearAlgebra.BLAS.LBTConfig
Libraries: 
└ [ILP64] mkl_rt.2.dll

```

---

<div class="post-metadata">

**Author:** ![acxz](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/acxz/32/16759_2.png) [@acxz](https://discourse.julialang.org/u/acxz)\
**Post date:** [August 31, 2022, 10:10pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/12 "2022-08-31T22:10:47Z")

</div>

> [@Amro](#):
>
> why I am not having the same fast speed as my colleague after using “MKLSparse”

Based on just the benchmark itself without MKL it is likely the case that @carstenbauer has a better CPU, and consequently a CPU that better utilizes MKL functionality over your CPU. We won’t know for sure though unless he posts his CPU info.

From this thread, it seems that he gets a 20x speed up and you get a 4x speed.

The complicated answer I could give you is that you should confirm if you get similar MKL performance gains without using Julia’s MKL package and see if similar times are observed. This would at least rule out if using Julia’s MKL is the cause for a potential slowdown, if any.

The easy answer I can give you though is get a better CPU.

---

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [September 1, 2022, 1:23pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/13 "2022-09-01T13:23:28Z")

</div>

Thank you very much for your reply.

> [@acxz](#):
>
> The complicated answer I could give you is that you should confirm if you get similar MKL performance gains without using Julia’s MKL package and see if similar times are observed.

Excuse me, I did not get it. From the post above, I have similar results with `carstenbauer ` when not importing `using MKLSparse` and slower with him when using it.

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<div class="post-metadata">

**Author:** ![pitsianis](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pitsianis/32/26588_2.png) [@pitsianis](https://discourse.julialang.org/u/pitsianis)\
**Post date:** [September 1, 2022, 1:30pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/14 "2022-09-01T13:30:11Z")

</div>

It might be interesting to try

> [@\[ANN\] Fast SpMv with CompressedSparseBlocks.jl](https://discourse.julialang.org/t/ann-fast-spmv-with-compressedsparseblocks-jl/84680):
>
> If you have a computation with an iteration where the time is dominated by a large sparse matrix multiplication, julia\> using LinearAlgebra, SparseArrays, BenchmarkTools julia\> n = 2^22; d = 10; A = sprand(n,n,d/n); x = rand(n); julia\> y = @btime $A\*$x; 909.738 ms (2 allocations: 32.00 MiB) julia\> yt = @btime $(transpose(A))\*$x; 640.637 ms (2 allocations: 32.00 MiB) you may want to consider the [CompressedSparseBlocks](https://github.com/fcdimitr/CompressedSparseBlocks.jl) package, a Julia wrapper to the [CSB Library](https://github.com/PASSIONLab/CSB). julia\> using Compressed…

if your sparse matrix does not change for several iterations. The CSB data structure and code has been observed to be faster than MKL for many sparse matrix families.

Your source codes will require a minor modification or abstraction to process the dense matrices in column batches. I think we compiled it with up to 32 dense columns per call.

---

<div class="post-metadata">

**Author:** ![acxz](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/acxz/32/16759_2.png) [@acxz](https://discourse.julialang.org/u/acxz)\
**Post date:** [September 1, 2022, 3:14pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/15 "2022-09-01T15:14:40Z")

</div>

> [@Amro](#):
>
> Excuse me, I did not get it. From the post above, I have similar results with `carstenbauer ` when not importing `using MKLSparse` and slower with him when using it.

> [@acxz](#):
>
> Based on just the benchmark itself without MKL it is likely the case that @carstenbauer has a better CPU, and consequently a CPU that better utilizes MKL functionality over your CPU. We won’t know for sure though unless he posts his CPU info.

> [@Amro](#):
>
> I have similar results

To be technical, you have slower results. If you had the same or above, the results would be alarming, but that is not the case. You should not compare with @carstenbauer 's results until you have his CPU information to compare with.

There is nothing you can do besides getting a better CPU or by trying to find a bug in MKLSparse.jl by comparing your results with MKLSparse.jl vs the Intel provided MKL Sparse routines.

---

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [September 1, 2022, 3:32pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/16 "2022-09-01T15:32:33Z")

</div>

I see. Thank you very much for your reply!

---

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [September 1, 2022, 3:32pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/17 "2022-09-01T15:32:54Z")

</div>

Thank you, I will check it

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<div class="post-metadata">

**Author:** ![lmiq](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lmiq/32/18314_2.png) [@lmiq](https://discourse.julialang.org/u/lmiq)\
**Post date:** [September 1, 2022, 3:42pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/18 "2022-09-01T15:42:52Z")

</div>

FWIW I get a result similar to yours (~10 s and ~3 s), with:

```julia
julia> versioninfo()
Julia Version 1.8.0
Commit 5544a0fab76 (2022-08-17 13:38 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 12 × 11th Gen Intel(R) Core(TM) i5-11500H @ 2.90GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-13.0.1 (ORCJIT, tigerlake)
  Threads: 12 on 12 virtual cores

```

---

<div class="post-metadata">

**Author:** ![Amro](https://avatars.discourse-cdn.com/v4/letter/a/4491bb/32.png) [@Amro](https://discourse.julialang.org/u/Amro)\
**Post date:** [September 1, 2022, 3:56pm UTC](https://discourse.julialang.org/t/how-to-utilize-mklsparse-jl/85263/20 "2022-09-01T15:56:08Z")

</div>

Thanks for your feedback! 🙂