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Update the README
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Some of the material is quite old and may not be accurate anymore.
Consequently it was moved to READMEOLD.md
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timholy committed Jul 12, 2018
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119 changes: 3 additions & 116 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@ like Fortran.
```julia
julia> using OffsetArrays

julia> y = OffsetArray{Float64}(uninitialized, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1);
julia> y = OffsetArray{Float64}(undef, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1);

julia> summary(y)
"OffsetArrays.OffsetArray{Float64,8,Array{Float64,8}} with indices -1:1×-7:7×-128:512×-5:5×-1:1×-3:3×-2:2×-1:1"
Expand All @@ -20,119 +20,6 @@ julia> y[-1,-7,-128,-5,-1,-3,-2,-1] += 5
19.0
```

Support for such arrays is based on new functionality in Julia v0.5,
and the modern package is not usable on earlier Julia versions.
## Notes on supporting OffsetArrays

## Special note for Julia 0.7

During the transition to allowing arrays with
arbitrary indices, certain operations (like `size` and `length`) are
deliberately unsupported; see the
[documentation](http://docs.julialang.org/en/latest/devdocs/offset-arrays/)
describing the reasoning behind this decision. The general
recommendation is to use iteration and `eachindex` and `LinearIndices` for most
operations where `size` and `length` would have formerly been used.

If your package makes use of OffsetArrays, you can also add the
following internal convenience definitions:

```jl
_size(A::AbstractArray) = size(LinearIndices(A))
_size(A) = size(A)

_length(A::AbstractArray) = length(LinearIndices(A))
_length(A) = length(A)
```

These versions should work for all types.

## Performance optimization with @unsafe

Also during Julia 0.5, `@inbounds` will not remove the internal
bounds-checking that happens when using an OffsetArray. Until this
changes, you can often accomplish the same task with `@unsafe`:

```jl
v = OffsetArray(rand(1000), 0:999)
@unsafe for i in indices(v, 1)
v[i] += 1
end
```

With such annotation, `OffsetArray`s are as performant as `Array`s.

`@unsafe` is not as powerful as `@inbounds`, and it is possible to set
up situations where it fails to remove bounds checks. However, it
suffices for many uses.

# Comparison with Fortran

The original purpose of the package was to simplify translation of Fortran codes, say
* the codes accompanying the book _Numerical Solution of Hyperbolic Partial Differential Equations_ by prof. John A. Trangenstein
Please refer [here](http://www.math.duke.edu/~johnt/) and [here](http://www.cambridge.org/us/academic/subjects/mathematics/differential-and-integral-equations-dynamical-systems-and-co/numerical-solution-hyperbolic-partial-differential-equations)
* Clawpack (stands for *Conservation Laws Package*) by prof. Randall J. LeVeque

+ [classic ClawPack](http://depts.washington.edu/clawpack/)

+ [ClawPack 5.0](http://clawpack.github.io/index.html)

see also [translation to Julia of Fortran codes from ClawPack](https://github.com/alsam/Claw.jl)

The directory _examples_ of [hyperbolic_PDE](https://github.com/alsam/hyperbolic_PDE.jl) contains at the moment a translation of explicit upwind finite difference scheme for scalar law advection equation from
the book _Numerical Solution of Hyperbolic Partial Differential Equations_ by prof. John A. Trangenstein.

+ examples/scalar_law/PROGRAM0/main.jl
The original Fortran arrays `u(-2:ncells+1), x(0:ncells), flux(0:ncells)` transformed to 1-based Julia arrays by shifting index expressions
```julia
u = Array(Float64, ncells+4)
x = Array(Float64, ncells+1)
flux = Array(Float64, ncells+1)
```

+ examples/scalar_law/PROGRAM0/main_offset_array.jl
Exemplary _use case_ of this package
```julia
u = OffsetArray(Float64, -2:ncells+1)
x = OffsetArray(Float64, 0:ncells)
flux = OffsetArray(Float64, 0:ncells)
```

+ Timings for baseline with `@unsafe` annotation:
```sh
0.103402 seconds (21 allocations: 235.531 KB)
```

+ Timing for `OffsetArray` version with `@unsafe` annotation:
```sh
0.103987 seconds (16 allocations: 235.094 KB)
```

+ Timing for `sub` macro version with `@unsafe` annotation (doesn't work without `@unsafe`):
```sh
0.105967 seconds (217 allocations: 268.094 KB)
```
Only the 2nd timing after warming up is given.

+ UPDATE:
Added
+ examples/scalar_law/PROGRAM1/...
```sh
[~/w/m/O/e/s/PROGRAM1] $ julia linaddmain.jl --cells=10000 --runs=3 ms master|✚ 1…
0.672295 seconds (42.90 k allocations: 1.990 MB)
0.509693 seconds (18 allocations: 313.281 KB)
0.512243 seconds (18 allocations: 313.281 KB)
[~/w/m/O/e/s/PROGRAM1] $ julia linaddmain.jl --cells=100000 --runs=3 6134ms master|✚ 1…
7.270463 seconds (42.90 k allocations: 4.736 MB)
7.177485 seconds (18 allocations: 3.053 MB)
7.248687 seconds (18 allocations: 3.053 MB)
```

Fortran timing for `100000` number of cells
```sh
real 0m4.781s
user 0m4.760s
sys 0m0.000s

```

That is 7.2s for Julia script vs. 4.8s for Fortran.
Julia supports generic programming with arrays that doesn't require you to assume that indices start with 1, see the [documentation](http://docs.julialang.org/en/latest/devdocs/offset-arrays/).
63 changes: 63 additions & 0 deletions READMEOLD.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,63 @@
# Comparison with Fortran

The original purpose of the package was to simplify translation of Fortran codes, say
* the codes accompanying the book _Numerical Solution of Hyperbolic Partial Differential Equations_ by prof. John A. Trangenstein
Please refer [here](http://www.math.duke.edu/~johnt/) and [here](http://www.cambridge.org/us/academic/subjects/mathematics/differential-and-integral-equations-dynamical-systems-and-co/numerical-solution-hyperbolic-partial-differential-equations)
* Clawpack (stands for *Conservation Laws Package*) by prof. Randall J. LeVeque

+ [classic ClawPack](http://depts.washington.edu/clawpack/)

+ [ClawPack 5.0](http://clawpack.github.io/index.html)

see also [translation to Julia of Fortran codes from ClawPack](https://github.com/alsam/Claw.jl)

The directory _examples_ of [hyperbolic_PDE](https://github.com/alsam/hyperbolic_PDE.jl) contains at the moment a translation of explicit upwind finite difference scheme for scalar law advection equation from
the book _Numerical Solution of Hyperbolic Partial Differential Equations_ by prof. John A. Trangenstein.

+ examples/scalar_law/PROGRAM0/main.jl
The original Fortran arrays `u(-2:ncells+1), x(0:ncells), flux(0:ncells)` transformed to 1-based Julia arrays by shifting index expressions
```julia
u = Array{Float64}(undef, ncells+4)
x = Array{Float64}(undef, ncells+1)
flux = Array{Float64}(undef, ncells+1)
```{+ examp}(undef,es/scalar_law/PROGRAM0/main_offset_array.jl
Exemplary _use case_ of this package
```julia
u = OffsetArray{Float64}(undef, -2:ncells+1)
x = OffsetArray{Float64}(undef, 0:ncells)
flux = OffsetArray{Float64}(undef, 0:ncells)
```

+ Timings for baseline with `@inbounds` annotation:
```sh
0.103402 seconds (21 allocations: 235.531 KB)
```

+ Timing for `OffsetArray` version with `@inbounds` annotation:
```sh
0.103987 seconds (16 allocations: 235.094 KB)
```

+ UPDATE:
Added
+ examples/scalar_law/PROGRAM1/...
```sh
[~/w/m/O/e/s/PROGRAM1] $ julia linaddmain.jl --cells=10000 --runs=3 ms master|✚ 1…
0.672295 seconds (42.90 k allocations: 1.990 MB)
0.509693 seconds (18 allocations: 313.281 KB)
0.512243 seconds (18 allocations: 313.281 KB)
[~/w/m/O/e/s/PROGRAM1] $ julia linaddmain.jl --cells=100000 --runs=3 6134ms master|✚ 1…
7.270463 seconds (42.90 k allocations: 4.736 MB)
7.177485 seconds (18 allocations: 3.053 MB)
7.248687 seconds (18 allocations: 3.053 MB)
```

Fortran timing for `100000` number of cells
```sh
real 0m4.781s
user 0m4.760s
sys 0m0.000s

```

That is 7.2s for Julia script vs. 4.8s for Fortran.

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