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This commit is contained in:
Chao Liu
2022-10-03 14:34:40 -05:00
committed by GitHub
parent 473ba5bc4a
commit 6de749e29c
3 changed files with 15 additions and 18 deletions

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# 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++.
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:
CK utilizes two concepts to achieve performance portability and code maintainability:
* A tile-based programming model
* Algorithm complexity reduction for complex ML operators, using innovative technique we call "Tensor Coordinate Transformation".
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## Code Structure
Current CK library are structured into 4 layers:
* "Templated Tile Operators"
* "Templated Tile Operators" layer
* "Templated Kernel and Invoker" layer
* "Instantiated Kernel and Invoker" layer
* "Client API" layer
@@ -90,7 +90,7 @@ Instructions for using CK as a pre-built kernel library are under [client_exampl
### 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.
output buffer to be accumulated multiple times, causing verification 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.