README.md 3.32 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
# Composable Kernel

## Methodology
Composable Kernel (CK) library aims to provide a programming model for writing performance critical kernels for Machine Learning workloads across multiple architectures including GPUs, CPUs, etc, through general purpose kernel languages, like HIP C++.

CK utilizes two concepts to achieve performance portabilatity and code maintainbility:
* A tile-based programming model
* Algorithm complexity reduction for complex ML operators, using innovative technique we call "Tensor Coordinate Transformation".

![ALT](/doc/image/ck_component.png "CK Components")

## Code Structure
Current CK library are structured into 4 layers:
* "Templated Tile Operators"
* "Templated Kernel and Invoker" layer
* "Instantiated Kernel and Invoker" layer
* "Client API" layer

![ALT](/doc/image/ck_layer.png "CK Layers")

## Contributors
The list of developers and contributors is here: [Contributors](/CONTRIBUTORS.md)

## Citation
If you use CK, please use following citations:
* CK paper will be freely available on arXiv soon: [Realizing Tensor Operators Using Coordinate Transformations and Tile Based Programming](???)
* [CITATION.cff](/CITATION.cff)

## License
CK is released under the MIT license. [License File](/LICENSE)


# Build CK

## Build docker image
```bash
DOCKER_BUILDKIT=1 docker build -t ck:latest -f Dockerfile .
```

## Launch docker
41
42
43
44
45
46
47
```bash
docker run                                     \
-it                                            \
--privileged                                   \
--group-add sudo                               \
-w /root/workspace                             \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace  \
48
ck:latest                                      \
49
50
/bin/bash
```
Chao Liu's avatar
Chao Liu committed
51

52
## Build CK
53
54
55
```bash
mkdir build && cd build

56
57
58
59
60
61
62
# Need to specify target ID, example below is for gfx908 and gfx90a
cmake                                                                                             \
-D CMAKE_PREFIX_PATH=/opt/rocm                                                                    \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc                                                         \
-D CMAKE_CXX_FLAGS="-O3"                                                                          \
-D CMAKE_BUILD_TYPE=Release                                                                       \
-D GPU_TARGETS=gfx908;gfx90a                                                                      \
63
64
65
..
```

66
### Build examples and tests
67
```bash
68
 make -j examples tests
69
70
71
 make test
```

72
73
74
Instructions for running each individual examples are under [example](/example)


75
76
77
78
## Build ckProfiler
```bash
 make -j ckProfiler
```
79
Instructions for running ckProfiler are under [profiler](/profiler)
JD's avatar
JD committed
80

81
82
83
84
85
86
## Install CK
```bash
make install
```

## Using CK as pre-built kernel library
87
Instructions for using CK as a pre-built kernel library are under [client_example](/client_example)
JD's avatar
JD committed
88
89
90
91
92
93
94
95
96

## Caveat
### Kernel Timing and Verification
CK's own kernel timer will warn up kernel once, and then run it multiple times
to get average kernel time. For some kernels that use atomic add, this will cause
output buffer to be accumulated multiple times, causing verfication failure.
To work around it, do not use CK's own timer and do verification at the same time.
CK's own timer and verification in each example and ckProfiler can be enabled or
disabled from command line.