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authorGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2016-01-11 09:07:14 -0800
committerGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2016-01-11 09:07:14 -0800
commit780623261eedd996404795dfb7928e680408adb5 (patch)
tree14f995a2491d2dead393ad75914310bb0ce5f8a1 /unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
parentb557662e589a76265f73b99d7ca54a988d7bdb59 (diff)
Re-enabled the optimized reduction CUDA code.
Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h')
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h6
1 files changed, 3 insertions, 3 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h b/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
index 558d0c83d..198b3604c 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorReductionCuda.h
@@ -126,7 +126,7 @@ struct FullReducer<Self, Op, GpuDevice, Vectorizable> {
const int block_size = 256;
const int num_per_thread = 128;
const int num_blocks = std::ceil(static_cast<float>(num_coeffs) / (block_size * num_per_thread));
- LAUNCH_CUDA_KERNEL((FullReductionKernel<block_size, num_per_thread>),
+ LAUNCH_CUDA_KERNEL((FullReductionKernel<block_size, num_per_thread, Self, Op, Index>),
num_blocks, block_size, 0, device, reducer, self, num_coeffs, output);
}
};
@@ -222,7 +222,7 @@ struct InnerReducer<Self, Op, GpuDevice> {
const int num_per_thread = 128;
const int num_blocks = 32;
- LAUNCH_CUDA_KERNEL((InnerReductionKernel<num_per_thread>),
+ LAUNCH_CUDA_KERNEL((InnerReductionKernel<num_per_thread, Self, Op, Index>),
num_blocks, block_size, block_size*sizeof(float), device, reducer, self, num_coeffs_to_reduce, num_preserved_vals, output);
}
};
@@ -279,7 +279,7 @@ struct OuterReducer<Self, Op, GpuDevice> {
device.maxCudaThreadsPerMultiProcessor() / block_size;
const int num_blocks = numext::mini<int>(max_blocks, dyn_blocks);
- LAUNCH_CUDA_KERNEL((OuterReductionKernel<num_per_thread>),
+ LAUNCH_CUDA_KERNEL((OuterReductionKernel<num_per_thread, Self, Op, Index>),
num_blocks, block_size, 0, device, reducer, self, num_coeffs_to_reduce, num_preserved_vals, output);
}
};