mirror of
https://github.com/slsdetectorgroup/aare.git
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kferjaoui
e894bdac9b
- Add bind_ClusterFinderCUDA.hpp with pybind11 bindings for ClusterFinderCUDA - Build CUDA bindings as separate _aare_cuda.so to avoid segfaults from mixing nvcc and gcc compiled code in the same shared object - Re-export CUDA classes onto _aare in __init__.py so user code uses `from aare import ClusterFinderCUDA` regardless of which .so hosts the class - Factory in ClusterFinder.py selects backend; RuntimeError if GPU requested on CPU-only build - Update python/CMakeLists.txt: _aare_cuda module gated behind AARE_CUDA and AARE_PYTHON_BINDINGS - Add validation notebook: ~20x speedup vs sequential ClusterFinder
67 lines
2.9 KiB
Plaintext
67 lines
2.9 KiB
Plaintext
// SPDX-License-Identifier: MPL-2.0
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//
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// CUDA-only Python extension module. Registers ClusterFinderCUDA along with
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// the ClusterVector and Cluster types it exposes in its return values, so
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// the module is self-contained — users can call steal_clusters() and get
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// back a usable ClusterVector without _aare needing to be imported first.
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#include "bind_Cluster.hpp"
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#include "bind_ClusterVector.hpp"
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#include "bind_ClusterFinderCUDA.hpp"
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#include <pybind11/pybind11.h>
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namespace py = pybind11;
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// Register the Cluster + ClusterVector pair for one (T, N, M) combination.
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// Subset of DEFINE_CLUSTER_BINDINGS from module.cpp: we register what
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// ClusterFinderCUDA actually returns, nothing more. File I/O, eta and
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// reduce_to_2x2 stay on the CPU side.
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#define DEFINE_CUDA_CLUSTER_TYPES(T, N, M, U, TYPE_CODE) \
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define_ClusterVector<T, N, M, U>(m, "Cluster" #N "x" #M #TYPE_CODE); \
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define_Cluster<T, N, M, U>(m, #N "x" #M #TYPE_CODE);
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#define DEFINE_BINDINGS_CLUSTERFINDER_CUDA(T, N, M, U, TYPE_CODE) \
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aare::define_ClusterFinderCUDA<T, N, M, U>( \
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m, "Cluster" #N "x" #M #TYPE_CODE);
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PYBIND11_MODULE(_aare_cuda, m) {
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// Types first — finders reference them in their signatures.
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// SFINAE excludes 2x2 on ClusterFinderCUDA, so we skip it here too.
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DEFINE_CUDA_CLUSTER_TYPES(int, 3, 3, uint16_t, i);
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DEFINE_CUDA_CLUSTER_TYPES(double, 3, 3, uint16_t, d);
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DEFINE_CUDA_CLUSTER_TYPES(float, 3, 3, uint16_t, f);
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DEFINE_CUDA_CLUSTER_TYPES(int, 5, 5, uint16_t, i);
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DEFINE_CUDA_CLUSTER_TYPES(double, 5, 5, uint16_t, d);
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DEFINE_CUDA_CLUSTER_TYPES(float, 5, 5, uint16_t, f);
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DEFINE_CUDA_CLUSTER_TYPES(int, 7, 7, uint16_t, i);
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DEFINE_CUDA_CLUSTER_TYPES(double, 7, 7, uint16_t, d);
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DEFINE_CUDA_CLUSTER_TYPES(float, 7, 7, uint16_t, f);
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DEFINE_CUDA_CLUSTER_TYPES(int, 9, 9, uint16_t, i);
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DEFINE_CUDA_CLUSTER_TYPES(double, 9, 9, uint16_t, d);
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DEFINE_CUDA_CLUSTER_TYPES(float, 9, 9, uint16_t, f);
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// Finders
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 3, 3, uint16_t, i);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 3, 3, uint16_t, d);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 3, 3, uint16_t, f);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 5, 5, uint16_t, i);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 5, 5, uint16_t, d);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 5, 5, uint16_t, f);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 7, 7, uint16_t, i);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 7, 7, uint16_t, d);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 7, 7, uint16_t, f);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 9, 9, uint16_t, i);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 9, 9, uint16_t, d);
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DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 9, 9, uint16_t, f);
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}
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#undef DEFINE_CUDA_CLUSTER_TYPES
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#undef DEFINE_BINDINGS_CLUSTERFINDER_CUDA |