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Release v13.3 of the CUDA samples with CUDA 13.3 Toolkit (#435)
This is the release of the CUDA 13.3 samples, which include additions for CUDA Tile C++, and updated CCCL and Python samples.
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@@ -52,9 +52,9 @@ if (tid % (2 * s) == 0) { // Don't do this!
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- CUDA Toolkit 13.0+
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- Python 3.10+
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- `cuda-python` (13.0.0+)
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- `cuda-core` (>=0.6.0)
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- `cuda-core` (>=1.0.0)
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- `cuda-cccl` (1.0.0+)
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- `cupy` (13.0.0+)
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- `cupy-cuda13x` (>=14.0.0)
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- `numpy` (>=2.3.2)
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## Installation
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@@ -35,7 +35,7 @@ Key Concepts:
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- Reduction tree pattern: Divide-and-conquer parallel algorithm
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- Thread synchronization: Using __syncthreads() for coordination
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- Sequential thread IDs: How to avoid warp divergence
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- cuda.core Stream integration with CuPy via ExternalStream
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- cuda.core Stream integration with CuPy via Stream.from_external
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"""
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import math
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@@ -217,7 +217,7 @@ def benchmark_custom(
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stream, kernel, d_input, block_size=block_size, work_buffers=work_buffers
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)
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event_opts = {"enable_timing": True}
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event_opts = {"timing_enabled": True}
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start_event = stream.device.create_event(options=event_opts)
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end_event = stream.device.create_event(options=event_opts)
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@@ -264,7 +264,7 @@ def benchmark_cuda_compute(
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stream.sync()
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d_output = cp.empty(1, dtype=cp.float32)
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event_opts = {"enable_timing": True}
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event_opts = {"timing_enabled": True}
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start_event = stream.device.create_event(options=event_opts)
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end_event = stream.device.create_event(options=event_opts)
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@@ -299,7 +299,7 @@ def main() -> bool:
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device = Device(0)
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device.set_current()
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stream = device.create_stream()
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cp_stream = cp.cuda.ExternalStream(int(stream.handle))
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cp_stream = cp.cuda.Stream.from_external(stream)
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print()
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print_gpu_info(device)
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@@ -1,7 +1,7 @@
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# Parallel Reduction Sample Requirements
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cuda-python>=13.0.0
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cuda-core>=0.6.0
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cuda-core>=1.0.0
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cuda-cccl>=1.0.0
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cupy-cuda13x>=13.0.0
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cupy-cuda13x>=14.0.0
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numpy>=2.3.2
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