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Simplified the code that launches cuda kernels.
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@ -291,18 +291,9 @@ struct GpuDevice {
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int max_blocks_;
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};
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#if !defined(__CUDA_ARCH__)
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#define LAUNCH_CUDA_KERNEL(kernel, gridsize, blocksize, sharedmem, device, ...) \
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(kernel) <<< (gridsize), (blocksize), (sharedmem), (device).stream() >>> (__VA_ARGS__); \
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assert(cudaGetLastError() == cudaSuccess);
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#elif __CUDA_ARCH__ >= 350
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#define LAUNCH_CUDA_KERNEL(kernel, ...) \
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{ const auto __attribute__((__unused__)) __makeTheKernelInstantiate = &(kernel); } \
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eigen_assert(false && "Cannot launch a kernel from another kernel" __CUDA_ARCH__ kernel);
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#else
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#define LAUNCH_CUDA_KERNEL(kernel, ...) \
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eigen_assert(false && "Cannot launch a kernel from another kernel" __CUDA_ARCH__ kernel);
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#endif
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// FIXME: Should be device and kernel specific.
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@ -193,7 +193,7 @@ struct EigenMetaKernelEval {
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template <typename Evaluator, typename Index>
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struct EigenMetaKernelEval<Evaluator, Index, true> {
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static __device__ EIGEN_ALWAYS_INLINE
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void run(Evaluator eval, Index first, Index last, Index step_size) {
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void run(Evaluator& eval, Index first, Index last, Index step_size) {
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const Index PacketSize = unpacket_traits<typename Evaluator::PacketReturnType>::size;
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const Index vectorized_size = (last / PacketSize) * PacketSize;
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const Index vectorized_step_size = step_size * PacketSize;
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@ -126,11 +126,11 @@ struct FullReducer<Self, Op, GpuDevice, Vectorizable> {
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internal::is_same<typename Self::CoeffReturnType, float>::value;
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template <typename OutputType>
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static EIGEN_DEVICE_FUNC void run(const Self&, Op&, const GpuDevice&, OutputType*) {
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static void run(const Self&, Op&, const GpuDevice&, OutputType*) {
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assert(false && "Should only be called on floats");
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}
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static EIGEN_DEVICE_FUNC void run(const Self& self, Op& reducer, const GpuDevice& device, float* output) {
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static void run(const Self& self, Op& reducer, const GpuDevice& device, float* output) {
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typedef typename Self::Index Index;
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const Index num_coeffs = array_prod(self.m_impl.dimensions());
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@ -226,12 +226,12 @@ struct InnerReducer<Self, Op, GpuDevice> {
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internal::is_same<typename Self::CoeffReturnType, float>::value;
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template <typename Device, typename OutputType>
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static EIGEN_DEVICE_FUNC bool run(const Self&, Op&, const Device&, OutputType*, typename Self::Index, typename Self::Index) {
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static bool run(const Self&, Op&, const Device&, OutputType*, typename Self::Index, typename Self::Index) {
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assert(false && "Should only be called to reduce floats on a gpu device");
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return true;
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}
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static EIGEN_DEVICE_FUNC bool run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
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static bool run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
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typedef typename Self::Index Index;
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// It's faster to use the usual code.
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@ -305,12 +305,12 @@ struct OuterReducer<Self, Op, GpuDevice> {
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internal::is_same<typename Self::CoeffReturnType, float>::value;
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template <typename Device, typename OutputType>
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static EIGEN_DEVICE_FUNC bool run(const Self&, Op&, const Device&, OutputType*, typename Self::Index, typename Self::Index) {
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static bool run(const Self&, Op&, const Device&, OutputType*, typename Self::Index, typename Self::Index) {
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assert(false && "Should only be called to reduce floats on a gpu device");
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return true;
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}
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static EIGEN_DEVICE_FUNC bool run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
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static bool run(const Self& self, Op& reducer, const GpuDevice& device, float* output, typename Self::Index num_coeffs_to_reduce, typename Self::Index num_preserved_vals) {
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typedef typename Self::Index Index;
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// It's faster to use the usual code.
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