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title: Halide
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# Halide
a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines
Hongcheng Li
Xinyu Xu
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# What is Halide?
Halide is a domain-specific language (DSL) and compiler
- Designed for image processing pipelines.
- Optimizes parallelism, locality, and recomputation.
- Enables high-level expression of algorithms.
- Automatically applies optimization techniques.
- Generates optimized code for CPUs, GPUs, and specialized units.
- Simplifies development of complex image processing applications.
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# Cache
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# Memory Hierarchy
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# Moore's law
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# Locality
- Temporal Locality
- Spatial Locality
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# Small Experiment
<< < @/snippets/blur .ts ts { all }{ maxHeight: ' 250px '}
```ts {monaco-run}
// Paste your code here
//
//
```
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# A Simple Blur Algorithm
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````md magic-move
```cpp {all|3|4|all} twoslash
UniformImage in(UInt(8), 2)
Var x, y
Func blurx(x,y) = in(x-1,y) + in(x,y) + in(x+1,y)
Func out(x,y) = blurx(x,y-1) + blurx(x,y) + blurx(x,y+1)
```
```cpp {all} twoslash
UniformImage in(UInt(8), 2)
Var x, y
Func blurx(x,y) = in(x-1,y) + in(x,y) + in(x+1,y)
Func out(x,y) = blurx(x,y-1) + blurx(x,y) + blurx(x,y+1)
// Generated code
alloc blurx[2048][3072]
for each x in 0..3072:
for each y in 0..2048:
blurx[y][x] = in[y][x-1] + in[y][x] + in[y][x+1]
alloc out[2046][3072]
for each x in 0..3072:
for each y in 1..2047:
out[y][x] = blurx[y-1][x] + blurx[y][x] + blurx[y+1][x]
```
```cpp {all|3-4,7-8} twoslash
// Breadth first: each function is entirely evaluated before the next one.
alloc blurx[2048][3072]
for each x in 0..3072:
for each y in 0..2048:
blurx[y][x] = in[y][x-1] + in[y][x] + in[y][x+1]
alloc out[2046][3072]
for each x in 0..3072:
for each y in 1..2047:
out[y][x] = blurx[y-1][x] + blurx[y][x] + blurx[y+1][x]
```
```cpp {all|2-4,6-8} twoslash
// Reorder
alloc blurx[2048][3072]
for each y in 0..2048:
for each x in 0..3072:
blurx[y][x] = in[y][x-1] + in[y][x] + in[y][x+1]
alloc out[2046][3072]
for each y in 1..2047:
for each x in 0..3072:
out[y][x] = blurx[y-1][x] + blurx[y][x] + blurx[y+1][x]
```
```cpp {all|5-7} twoslash
// Total fusion: values are computed on the fly each time that they are needed.
alloc out[2046][3072]
for each y in 1..2047:
for each x in 0..3072:
alloc blurx[-1..1]
for each i in -1..1:
blurx[i] = in[y-1+i][x-1]+in[y-1+i][x]+in[y-1+i][x+1]
out[y][x] = blurx[0] + blurx[1] + blurx[2]
```
```cpp {all|4-5} twoslash
// Sliding window: values are computed when needed then stored until not useful anymore.
alloc out[2046][3072]
alloc blurx[3][3072]
for each y in -1..2047:
for each x in 0..3072:
blurx[(y+1)%3][x] = in[y+1][x-1] + in[y+1][x] + in[y+1][x+1]
if y < 1: continue
out[y][x] = blurx[(y-1)%3][x] + blurx[ y % 3 ][x] + blurx[(y+1)%3][x]
```
```cpp {all} twoslash
// Tiles: overlapping regions are processed in parallel, functions are evaluated one after another.
alloc out[2046][3072]
for each ty in 0..2048/32:
for each tx in 0..3072/32:
alloc blurx[-1..33][32]
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for each y in -1..33:
for each x in 0..32:
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blurx[y][x] = in[ty*32+y][tx*32+x-1] + in[ty*32+y][tx*32+x] + in[ty*32+y][tx*32+x+1]
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for each y in 0..32:
for each x in 0..32:
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out[ty*32+y][tx*32+x] = blurx[y-1][x] + blurx[y ][x] + blurx[y+1][x]
```
```cpp {all} twoslash
// Sliding windows within tiles: tiles are evaluated in parallel using sliding windows.
alloc out[2046][3072]
for each ty in 0..2048/8:
alloc blurx[-1..1][3072]
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for each y in -2..8:
for each x in 0..3072:
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blurx[(y+1)%3][x] = in[ty*8+y+1][tx*32+x-1] + in[ty*8+y+1][tx*32+x] + in[ty*8+y+1][tx*32+x+1]
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if each y < 0: continue
for each x in 0..3072:
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out[ty*8+y][x] = blurx[(y-1)%3][x] + blurx[ y % 3][x] + blurx[(y+1)%3][x]
```
````
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# Results
## x86
| Algorithm | Halide tuned(ms) | Expert tuned(ms) | Speedup | Lines Halide | Lines Expert | Factor Shorter |
| --------------- | ---------------- | ---------------- | ------- | ------------ | ------------ | -------------- |
| Blur | 11 | 13 | 1.2× ×
| Bilateral grid | 36 | 158 | 4.4× ×
| Camera pipe | 14 | 49 | 3.4× ×
| Interpolate | 32 | 54 | 1.7× ×
| Local Laplacian | 113 | 189 | 1.7× ×
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# Results
## CUDA
| Algorithm | Halide tuned(ms) | Expert tuned(ms) | Speedup | Lines Halide | Lines Expert | Factor Shorter |
| --------------- | ---------------- | ---------------- | ------- | ------------ | ------------ | -------------- |
| Bilateral grid | 8.1 | 18 | 2.3× ×
| Interpolate | 9.1 | 54* | 5.9× ×
| Local Laplacian | 21 | 189* | 9× ×
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# References
- [Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines ](https://dl.acm.org/doi/10.1145/2491956.2462176 )
- [CPU die shot ](https://www.computerhope.com/issues/pictures/cpu-cache-die.png )
- [Memory Hierarchy ](https://www.cs.swarthmore.edu/~kwebb/cs31/f18/memhierarchy/figures/MemoryHierarchy.png )
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- [Moore's Law ](https://image3.slideserve.com/6552767/moore-s-law-l.jpg )
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# Questions?
