246 lines
7.2 KiB
Markdown
246 lines
7.2 KiB
Markdown
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---
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# try also 'default' to start simple
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theme: seriph
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# random image from a curated Unsplash collection by Anthony
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# like them? see https://unsplash.com/collections/94734566/slidev
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background: https://cover.sli.dev
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# some information about your slides, markdown enabled
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title: Halide
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# apply any unocss classes to the current slide
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class: text-center
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# https://sli.dev/custom/highlighters.html
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highlighter: shiki
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# https://sli.dev/guide/drawing
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drawings:
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persist: false
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# slide transition: https://sli.dev/guide/animations#slide-transitions
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transition: slide-left
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# enable MDC Syntax: https://sli.dev/guide/syntax#mdc-syntax
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mdc: true
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---
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# Halide
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a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines
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Hongcheng Li
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Xinyu Xu
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<!--
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The last comment block of each slide will be treated as slide notes. It will be visible and editable in Presenter Mode along with the slide. [Read more in the docs](https://sli.dev/guide/syntax.html#notes)
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-->
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---
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layout: two-cols
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layoutClass: gap-16
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---
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<Toc minDepth="1" maxDepth="2"></Toc>
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---
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transition: fade-out
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---
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# What is Halide?
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Halide is a domain-specific language (DSL) and compiler
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- Designed for image processing pipelines.
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- Optimizes parallelism, locality, and recomputation.
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- Enables high-level expression of algorithms.
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- Automatically applies optimization techniques.
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- Generates optimized code for CPUs, GPUs, and specialized units.
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- Simplifies development of complex image processing applications.
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---
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transition: slide-up
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mdc: true
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---
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# Cache
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{width=500px lazy}
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---
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transition: slide-up
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level: 2
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mdc: true
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---
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# Memory Hierarchy
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{width=500px lazy}
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---
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transition: slide-up
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level: 2
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mdc: true
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---
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# Moore's law
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{width=500px lazy}
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---
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transition: slide-up
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level: 2
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---
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# Locality
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- Temporal Locality
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- Spatial Locality
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---
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transition: slide-left
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level: 2
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---
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# Small Experiment
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<<< @/snippets/blur.ts ts {all}{maxHeight:'250px'}
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```ts {monaco-run}
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// Paste your code here
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//
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//
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```
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---
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transition: slide-up
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---
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# A simple blur algorithm
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````md magic-move
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```cpp {all|3|4|all} twoslash
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UniformImage in(UInt(8), 2)
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Var x, y
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Func blurx(x,y) = in(x-1,y) + in(x,y) + in(x+1,y)
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Func out(x,y) = blurx(x,y-1) + blurx(x,y) + blurx(x,y+1)
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```
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```cpp {all} twoslash
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UniformImage in(UInt(8), 2)
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Var x, y
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Func blurx(x,y) = in(x-1,y) + in(x,y) + in(x+1,y)
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Func out(x,y) = blurx(x,y-1) + blurx(x,y) + blurx(x,y+1)
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// Generated code
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alloc blurx[2048][3072]
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for each x in 0..3072:
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for each y in 0..2048:
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blurx[y][x] = in[y][x-1] + in[y][x] + in[y][x+1]
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alloc out[2046][3072]
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for each x in 0..3072:
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for each y in 1..2047:
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out[y][x] = blurx[y-1][x] + blurx[y][x] + blurx[y+1][x]
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```
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```cpp {all|3-4,7-8} twoslash
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// Breadth first: each function is entirely evaluated before the next one.
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alloc blurx[2048][3072]
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for each x in 0..3072:
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for each y in 0..2048:
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blurx[y][x] = in[y][x-1] + in[y][x] + in[y][x+1]
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alloc out[2046][3072]
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for each x in 0..3072:
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for each y in 1..2047:
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out[y][x] = blurx[y-1][x] + blurx[y][x] + blurx[y+1][x]
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```
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```cpp {all|2-4,6-8} twoslash
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// Reorder
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alloc blurx[2048][3072]
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for each y in 0..2048:
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for each x in 0..3072:
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blurx[y][x] = in[y][x-1] + in[y][x] + in[y][x+1]
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alloc out[2046][3072]
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for each y in 1..2047:
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for each x in 0..3072:
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out[y][x] = blurx[y-1][x] + blurx[y][x] + blurx[y+1][x]
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```
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```cpp {all|5-7} twoslash
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// Total fusion: values are computed on the fly each time that they are needed.
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alloc out[2046][3072]
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for each y in 1..2047:
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for each x in 0..3072:
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alloc blurx[-1..1]
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for each i in -1..1:
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blurx[i] = in[y-1+i][x-1]+in[y-1+i][x]+in[y-1+i][x+1]
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out[y][x] = blurx[0] + blurx[1] + blurx[2]
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```
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```cpp {all|4-5} twoslash
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// Sliding window: values are computed when needed then stored until not useful anymore.
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alloc out[2046][3072]
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alloc blurx[3][3072]
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for each y in -1..2047:
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for each x in 0..3072:
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blurx[(y+1)%3][x] = in[y+1][x-1] + in[y+1][x] + in[y+1][x+1]
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if y < 1: continue
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out[y][x] = blurx[(y-1)%3][x] + blurx[ y % 3 ][x] + blurx[(y+1)%3][x]
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```
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```cpp {all} twoslash
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// Tiles: overlapping regions are processed in parallel, functions are evaluated one after another.
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alloc out[2046][3072]
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for each ty in 0..2048/32:
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for each tx in 0..3072/32:
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alloc blurx[-1..33][32]
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for y in -1..33:
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for 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 y in 0..32:
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for 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]
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```
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```cpp {all} twoslash
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// Sliding windows within tiles: tiles are evaluated in parallel using sliding windows.
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alloc out[2046][3072]
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for each ty in 0..2048/8:
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alloc blurx[-1..1][3072]
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for y in -2..8:
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for 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 y < 0: continue
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for 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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```
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````
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---
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transition: fade-out
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---
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# Results
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## x86
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| Algorithm | Halide tuned(ms) | Expert tuned(ms) | Speedup | Lines Halide | Lines Expert | Factor Shorter |
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| --------------- | ---------------- | ---------------- | ------- | ------------ | ------------ | -------------- |
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| Blur | 11 | 13 | 1.2× | 2 | 35 | 18× |
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| Bilateral grid | 36 | 158 | 4.4× | 34 | 122 | 4× |
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| Camera pipe | 14 | 49 | 3.4× | 123 | 306 | 2× |
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| Interpolate | 32 | 54 | 1.7× | 21 | 152 | 7× |
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| Local Laplacian | 113 | 189 | 1.7× | 52 | 262 | 5× |
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---
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transition: slide-left
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hideInToc: true
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---
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# Results
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## CUDA
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| Algorithm | Halide tuned(ms) | Expert tuned(ms) | Speedup | Lines Halide | Lines Expert | Factor Shorter |
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| --------------- | ---------------- | ---------------- | ------- | ------------ | ------------ | -------------- |
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| Bilateral grid | 8.1 | 18 | 2.3× | 34 | 370 | 11× |
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| Interpolate | 9.1 | 54* | 5.9× | 21 | 152* | 7× |
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| Local Laplacian | 21 | 189* | 9× | 52 | 262* | 5× |
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---
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transition: slide-left
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---
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# References
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- [Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines](https://dl.acm.org/doi/10.1145/2491956.2462176)
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- [CPU die shot](https://www.computerhope.com/issues/pictures/cpu-cache-die.png)
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- [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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