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Merged
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Jan 12, 2020
Merged

using AcuteBenchmark #30

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89a86cd
Adding AcuteBenchmark master
aminya Dec 31, 2019
c5a2af1
Real Functions
aminya Dec 31, 2019
574f6f3
Complex functions
aminya Dec 31, 2019
ffd88e9
Performing benchmark and plotting
aminya Dec 31, 2019
60effe4
Create CompatHelper.yml
aminya Jan 1, 2020
9d3af80
Create AcuteBenchmark.yml
aminya Jan 1, 2020
c3e28ef
Update AcuteBenchmark.yml
aminya Jan 1, 2020
6a6d677
Delete AcuteBenchmark.yml
aminya Jan 1, 2020
6c04968
Adding Complex Benchmark
aminya Jan 2, 2020
8905a19
Adding Comprehensive benchmark result
aminya Jan 3, 2020
dc53b38
dimplot Real result
aminya Jan 3, 2020
fa9be34
dimplot Complex
aminya Jan 3, 2020
739d45b
Adding AcuteBenchmark-Results sub-module
aminya Jan 12, 2020
b0e348f
Adding Full Results to the readme
aminya Jan 12, 2020
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27 changes: 27 additions & 0 deletions .github/workflows/CompatHelper.yml
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name: CompatHelper

on:
schedule:
- cron: '00 * * * *'
issues:
types: [opened, reopened]

jobs:
build:
runs-on: ${{ matrix.os }}
strategy:
matrix:
julia-version: [1.3.1]
julia-arch: [x86]
os: [ubuntu-latest]
steps:
- uses: julia-actions/setup-julia@latest
with:
version: ${{ matrix.julia-version }}
- name: Install dependencies
run: julia -e 'using Pkg; Pkg.add(Pkg.PackageSpec(name = "CompatHelper", url = "https://github.com/bcbi/CompatHelper.jl.git"))'
- name: CompatHelper.main
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
JULIA_DEBUG: CompatHelper
run: julia -e 'using CompatHelper; CompatHelper.main()'
3 changes: 3 additions & 0 deletions .gitmodules
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[submodule "benchmark-results"]
path = benchmark-results
url = C:/Users/yahyaaba/Documents/GitHub/AcuteBenchmark-Results
97 changes: 84 additions & 13 deletions README.md
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Expand Up @@ -3,7 +3,7 @@
[![Build status](https://ci.appveyor.com/api/projects/status/btdduqfsxux8fhsr?svg=true)](https://ci.appveyor.com/project/Crown421/IntelVectorMath-jl)

This package provides bindings to the Intel MKL [Vector Mathematics Functions](https://software.intel.com/en-us/node/521751).
This is often substantially faster than broadcasting Julia's built-in functions, especially when applying a transcendental function over a large array.
This is often substantially faster than broadcasting Julia's built-in functions, especially when applying a transcendental function over a large array.
Until Julia 0.6 the package was registered as `VML.jl`.

## Basic install
Expand All @@ -24,8 +24,8 @@ julia> ] add https://github.com/JuliaMath/IntelVectorMath.jl

## Using IntelVectorMath
After loading `IntelVectorMath`, you have the supported function listed below, for example `IntelVectorMath.sin(rand(100))`. These should provide a significant speed-up over broadcasting the Base functions.
Since the package name is quite long, an alias `IVM` is also exported to allow `IVM.sin(rand(100))` after `using` the package.
If you `import` the package, you can add this alias via `const IVM = IntelVectorMath`. Equally, you can replace `IVM` with another alias of your choice.
Since the package name is quite long, an alias `IVM` is also exported to allow `IVM.sin(rand(100))` after `using` the package.
If you `import` the package, you can add this alias via `const IVM = IntelVectorMath`. Equally, you can replace `IVM` with another alias of your choice.

#### Example
```julia
Expand Down Expand Up @@ -87,16 +87,87 @@ regarding these options is available on
[Intel's website](http://software.intel.com/sites/products/documentation/hpc/mkl/IntelVectorMath/vmldata.htm).

## Performance
(These results are currently outdated and will be updated in due course)
![IntelVectorMath Performance Comparison](/benchmark/performance.png)

![IntelVectorMath Complex Performance Comparison](/benchmark/performance_complex.png)

Tests were performed on an Intel(R) Core(TM) i7-3930K CPU. Error bars
are 95% confidence intervals based on 25 repetitions of each test with
a 1,000,000 element vector. The dashed line indicates equivalent
performance for IntelVectorMath versus the implementations in Base. Both Base and
IntelVectorMath use only a single core when performing these benchmarks.
Summary of Results:

Relative speed of IntelVectorMath/Base

![IntelVectorMath Performance Comparison](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set6-relative.png)

![IntelVectorMath Complex Performance Comparison](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set6-relative.png)

Full Results:

<details>
<summary>Real Functions - Full Benchmark Results</summary>

![Dimension set 1](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set1-relative.png)
![Dimension set 2](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set2-relative.png)
![Dimension set 3](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set3-relative.png)
![Dimension set 4](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set4-relative.png)
![Dimension set 5](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set5-relative.png)
![Dimension set 6](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set6-relative.png)
![Dimension set 7](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set7-relative.png)
![Dimension set 8](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set8-relative.png)
![Dimension set 9](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set9-relative.png)
![Dimension set 10](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/bar/bench-dims-set10-relative.png)

</details>

<details>
<summary>Complex Functions - Full Benchmark Results</summary>

![Dimension set 1](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set1-relative.png)
![Dimension set 2](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set2-relative.png)
![Dimension set 3](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set3-relative.png)
![Dimension set 4](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set4-relative.png)
![Dimension set 5](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set5-relative.png)
![Dimension set 6](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set6-relative.png)
![Dimension set 7](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set7-relative.png)
![Dimension set 8](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set8-relative.png)
![Dimension set 9](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set9-relative.png)
![Dimension set 10](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Complex/bar/bench-dims-set10-relative.png)

</details>

<details>
<summary>Real Functions - Performance over dimensions</summary>

![abs](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-abs-Type-Float64.png)
![abs2](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-abs2-Type-Float64.png)
![acos](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-acos-Type-Float64.png)
![acosh](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-acosh-Type-Float64.png)
![asin](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-asin-Type-Float64.png)
![asinh](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-asinh-Type-Float64.png)
![atan](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-atan-Type-Float64.png)
![atanh](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-atanh-Type-Float64.png)
![cbrt](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-cbrt-Type-Float64.png)
![ceil](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-ceil-Type-Float64.png)
![cis](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-cis-Type-Float64.png)
![cos](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-cos-Type-Float64.png)
![cosh](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-cosh-Type-Float64.png)
![erf](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-erf-Type-Float64.png)
![erfc](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-erfc-Type-Float64.png)
![erfcinv](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-erfcinv-Type-Float64.png)
![erfcinv](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-erfcinv-Type-Float64.png)
![exp](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-exp-Type-Float64.png)
![expm1](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-expm1-Type-Float64.png)
![floor](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-floor-Type-Float64.png)
![gamma](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-gamma-Type-Float64.png)
![hypot](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-hypot-Type-Float64.png)
![log](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-log-Type-Float64.png)
![round](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-round-Type-Float64.png)
![sin](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-sin-Type-Float64.png)
![sinh](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-sinh-Type-Float64.png)
![sqrt](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-sqrt-Type-Float64.png)
![tan](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-tan-Type-Float64.png)
![tanh](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-tanh-Type-Float64.png)
![trunc](https://raw.githubusercontent.com/aminya/AcuteBenchmark-Results/master/IntelVectorMath/Real/dimplot/bench-trunc-Type-Float64.png)

</details>

<br/>

Tests were performed on an Intel(R) Core(TM) i5-8250U @ 1.6 [GHz] 1800 Mhz. The dashed line indicates equivalent performance for IntelVectorMath versus the implementations in Base.

## Supported functions

Expand Down
1 change: 1 addition & 0 deletions benchmark-results
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Submodule benchmark-results added at 06b87c
2 changes: 2 additions & 0 deletions benchmark/Project.toml
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[deps]
AcuteBenchmark = "8f64fb4b-d933-4fa5-a855-09390d771cf3"
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