# Matrix profile calculation: STOMP method

**URL:** https://discourse.julialang.org/t/matrix-profile-calculation-stomp-method/25389
**Category:** Machine Learning
**Created:** [June 18, 2019, 8:03am UTC](https://discourse.julialang.org/t/matrix-profile-calculation-stomp-method/25389 "2019-06-18T08:03:28Z")
**Posts on this page:** 2
**Page:** 1

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### Author: ![taqtiqa-mark](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/taqtiqa-mark/32/4383_2.png) [@taqtiqa-mark](https://discourse.julialang.org/u/taqtiqa-mark)
#### Post date: [June 18, 2019, 8:03am UTC](https://discourse.julialang.org/t/matrix-profile-calculation-stomp-method/25389/1 "2019-06-18T08:03:28Z")

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Hi,  
Is there a Julia package that implements the matrix profile calculation using the [STOMP method](https://stumpy.readthedocs.io/en/latest/Tutorial_0.html?highlight=stomp#STUMPY), i.e. corresponds to [Stumpy](https://github.com/TDAmeritrade/stumpy)’s

> … scalable library that efficiently computes something called the [matrix profile](https://stumpy.readthedocs.io/en/latest/Tutorial_0.html)

Alternatively, is there a Julia package that has it on their road-map?

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<div class="post-metadata">

### Author: ![baggepinnen](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/baggepinnen/32/693_2.png) [@baggepinnen](https://discourse.julialang.org/u/baggepinnen)
#### Post date: [May 1, 2020, 4:13am UTC](https://discourse.julialang.org/t/matrix-profile-calculation-stomp-method/25389/2 "2020-05-01T04:13:37Z")

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See

> **[GitHub - baggepinnen/MatrixProfile.jl: Time-series analysis using the Matrix...](https://github.com/baggepinnen/MatrixProfile.jl)**
>
> Time-series analysis using the Matrix profile in Julia - GitHub - baggepinnen/MatrixProfile.jl: Time-series analysis using the Matrix profile in Julia

for an implementation of STOMP. It does currently not support GPU, but it’s quite a bit faster than the implementation of the original paper.

```julia
@time matrix_profile(randn(Float32, 2^17), 256)
# 55.262552 seconds (140 allocations: 5.009 MiB)

```

on a laptop from 2014, while the authors implementation from the paper took 4.2 minutes  
[(table III from their paper)](https://www.cs.ucr.edu/~eamonn/STOMP_GPU_final_submission_camera_ready.pdf).
