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This is the release of the CUDA 13.3 samples, which include additions for CUDA Tile C++, and updated CCCL and Python samples.
56 lines
1.8 KiB
Markdown
56 lines
1.8 KiB
Markdown
# tileMatmul
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## Description
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This sample demonstrates how to write a matrix multiplication kernel with good
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performance in CUDA Tile C++. The kernel multiplies FP16 input tiles with FP32
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accumulation using `cuda::tiles::mma`.
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The sample compares a naive implementation with an optimized implementation
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that applies good practices and provides the compiler with additional guidance
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for better code generation. The host code uses CUDA events to capture execution time.
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The optimized kernel uses neutral placeholder values for `LOAD_LATENCY` and
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`STORE_LATENCY`. See [tileMatmulAutotuner](../tileMatmulAutotuner) for an
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example of autotuning these values to find a suitable
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configuration for your hardware.
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## Running
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```
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# Run with default warmup and benchmark iterations. Validation is disabled by default.
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./tileMatmul
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# Enable CPU validation
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./tileMatmul --validate
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# To run faster, skip warmups (not recommended) and set iteration to 1
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./tileMatmul --skip-warmup -i 1
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# Show all options
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./tileMatmul --help
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```
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## Command-Line Options
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| Option | Description |
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|--------|-------------|
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| `--validate` | Enable CPU cross-validation. Validation is disabled by default. |
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| `--skip-warmup` | Disable warmup iterations. |
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| `--warmup=N` | Set warmup iterations. The default is 5. |
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| `-i N`, `--iters=N` | Set benchmark iterations. The default is 20. |
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## Example Output
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```
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Note: CPU cross-validation disabled
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matmul : 0.073 ms, 115.2 GB/s, 29495.8 GFLOPS
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matmul_naive : 0.497 ms, 16.9 GB/s, 4322.8 GFLOPS
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```
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## Prerequisites
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- [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) version 13.3 or later.
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- [CUDA Driver](https://www.nvidia.com/en-us/drivers/) version 580 or later.
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- Host compiler with C++20 support.
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