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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.
29 lines
1.1 KiB
Markdown
29 lines
1.1 KiB
Markdown
# tileBmm
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## Description
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This sample demonstrates a static-persistent batched matrix multiplication
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(BMM) using CUDA Tile C++. Given inputs A of shape (Q, M, K) and B of shape
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(Q, K, N), the kernel computes C = A x B of shape (Q, M, N). The grid
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launches a fixed number of persistent blocks sized from the device's SM
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count, and each block walks the (M, N, Q-chunk) tile space via a grid-stride
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loop. The batch dimension is tiled by BLOCK_SIZE_Q so every iteration issues
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a single rank-3 batched cuda::tiles::mma per K-step over tiles of shape
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(BLOCK_SIZE_Q, BLOCK_SIZE_M, BLOCK_SIZE_K) and
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(BLOCK_SIZE_Q, BLOCK_SIZE_K, BLOCK_SIZE_N). Grouped ordering on
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(pid_m, pid_n) gives L2 reuse. The accumulator is kept in float32 for
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precision, and masked loads/stores handle tiles that overhang the matrix
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or batch boundaries. Inputs and outputs use __half precision.
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## Expected Output
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```
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Success! BMM matches expected results.
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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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