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https://github.com/ROCm/composable_kernel.git
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use constant tensor descriptor
This commit is contained in:
Chao Liu
561
src/include/constant_direct_convolution.cuh
Normal file
561
src/include/constant_direct_convolution.cuh
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@@ -0,0 +1,561 @@
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#pragma once
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#include "constant_tensor_descriptor.cuh"
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template <class TFloat,
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class SrcDesc,
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class DstDesc,
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unsigned NWorkLen0,
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unsigned NWorkLen1,
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unsigned NWorkLen2,
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unsigned NWorkLen3,
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class F>
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__device__ void blockwise_4d_tensor_op(
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SrcDesc, TFloat* const __restrict__ p_src, DstDesc, TFloat* __restrict__ p_dst, F f)
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{
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto src_desc = SrcDesc{};
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constexpr auto dst_desc = DstDesc{};
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#if 1
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if(threadIdx.x == 0)
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{
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print_ConstantTensorDescriptor(src_desc);
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print_ConstantTensorDescriptor(dst_desc);
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}
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#endif
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constexpr unsigned NWorkStride3 = 1;
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constexpr unsigned NWorkStride2 = NWorkLen3 * NWorkStride3;
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constexpr unsigned NWorkStride1 = NWorkLen2 * NWorkStride2;
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constexpr unsigned NWorkStride0 = NWorkLen1 * NWorkStride1;
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unsigned itmp =
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threadIdx.x + threadIdx.y * blockDim.x + threadIdx.z * (blockDim.y * blockDim.x);
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const unsigned did0_begin = itmp / NWorkStride0;
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itmp -= did0_begin * NWorkStride0;
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const unsigned did1_begin = itmp / NWorkStride1;
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itmp -= did1_begin * NWorkStride1;
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const unsigned did2_begin = itmp / NWorkStride2;
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itmp -= did2_begin * NWorkStride2;
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const unsigned did3_begin = itmp / NWorkStride3;
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for(unsigned did0 = did0_begin; did0 < src_desc.GetLength(I0); did0 += NWorkLen0)
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{
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for(unsigned did1 = did1_begin; did1 < src_desc.GetLength(I1); did1 += NWorkLen1)
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{
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for(unsigned did2 = did2_begin; did2 < src_desc.GetLength(I2); did2 += NWorkLen2)
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{
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for(unsigned did3 = did3_begin; did3 < src_desc.GetLength(I3); did3 += NWorkLen3)
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{
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const unsigned sindex =
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src_desc.GetStride(I0) * did0 + src_desc.GetStride(I1) * did1 +
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src_desc.GetStride(I2) * did2 + src_desc.GetStride(I3) * did3;
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const unsigned dindex =
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dst_desc.GetStride(I0) * did0 + dst_desc.GetStride(I1) * did1 +
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dst_desc.GetStride(I2) * did2 + dst_desc.GetStride(I3) * did3;
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f(p_src[dindex], p_dst[sindex]);
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#if 0
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// if(threadIdx.x == 0)
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{
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printf("blockwise_4d_tensor_op: 1: thread id %u, \t"
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"sindex %u, p_src[sindex] %f, \t"
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"dindex %u, p_dst[dindex] %f\n",
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threadIdx.x,
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sindex,
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p_src[sindex],
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dindex,
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p_dst[dindex]);
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}
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#endif
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}
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}
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}
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}
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}
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template <class TFloat, class SrcDesc, class DstDesc, class F>
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__device__ void threadwise_4d_tensor_op(
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SrcDesc, TFloat* const __restrict__ p_src, DstDesc, TFloat* __restrict__ p_dst, F f)
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{
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto src_desc = SrcDesc{};
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constexpr auto dst_desc = DstDesc{};
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#if 1
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if(threadIdx.x == 0)
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{
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print_ConstantTensorDescriptor(src_desc);
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print_ConstantTensorDescriptor(dst_desc);
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}
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#endif
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for(unsigned did0 = 0; did0 < src_desc.GetLength(I0); ++did0)
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{
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for(unsigned did1 = 0; did1 < src_desc.GetLength(I1); ++did1)
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{
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for(unsigned did2 = 0; did2 < src_desc.GetLength(I2); ++did2)
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{
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for(unsigned did3 = 0; did3 < src_desc.GetLength(I3); ++did3)
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{
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const unsigned sindex =
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src_desc.GetStride(I0) * did0 + src_desc.GetStride(I1) * did1 +
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src_desc.GetStride(I2) * did2 + src_desc.GetStride(I3) * did3;
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const unsigned dindex =
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dst_desc.GetStride(I0) * did0 + dst_desc.GetStride(I1) * did1 +
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dst_desc.GetStride(I2) * did2 + dst_desc.GetStride(I3) * did3;
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f(p_src[sindex], p_dst[dindex]);
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#if 0
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if(threadIdx.x == 0)
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{
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printf("threadwise_4d_tensor_op: 1: thread id %u, \t"
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"sindex %u, p_src[sindex] %f, \t"
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"dindex %u, p_dst[dindex] %f\n",
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threadIdx.x,
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sindex,
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p_src[sindex],
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dindex,
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p_dst[dindex]);
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}
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#endif
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}
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}
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}
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}
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}
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template <class TFloat, class InDesc, class WeiDesc, class OutDesc>
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__device__ void threadwise_direct_convolution(InDesc,
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TFloat* const __restrict__ p_in,
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WeiDesc,
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TFloat* const __restrict__ p_wei,
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OutDesc,
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TFloat* __restrict__ p_out)
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{
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto in_desc = InDesc{};
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constexpr auto wei_desc = WeiDesc{};
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constexpr auto out_desc = OutDesc{};
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#if 1
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if(threadIdx.x == 0)
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{
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print_ConstantTensorDescriptor(in_desc);
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print_ConstantTensorDescriptor(wei_desc);
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print_ConstantTensorDescriptor(out_desc);
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}
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#endif
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for(unsigned n = 0; n < out_desc.GetLength(I0); ++n)
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{
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for(unsigned k = 0; k < out_desc.GetLength(I1); ++k)
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{
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for(unsigned ho = 0; ho < out_desc.GetLength(I2); ++ho)
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{
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for(unsigned wo = 0; wo < out_desc.GetLength(I3); ++wo)
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{
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for(unsigned c = 0; c < wei_desc.GetLength(I1); ++c)
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{
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for(unsigned s = 0; s < wei_desc.GetLength(I2); ++s)
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{
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for(unsigned r = 0; r < wei_desc.GetLength(I3); ++r)
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{
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const unsigned hi = ho + s;
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const unsigned wi = wo + r;
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const unsigned in_index =
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in_desc.GetStride(I0) * n + in_desc.GetStride(I1) * c +
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in_desc.GetStride(I2) * hi + in_desc.GetStride(I3) * wi;
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const unsigned wei_index =
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wei_desc.GetStride(I0) * k + wei_desc.GetStride(I1) * c +
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wei_desc.GetStride(I2) * s + in_desc.GetStride(I3) * r;
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const unsigned out_index =
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out_desc.GetStride(I0) * n + out_desc.GetStride(I1) * k +
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out_desc.GetStride(I2) * ho + out_desc.GetStride(I3) * wo;
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p_out[out_index] += p_wei[wei_index] * p_in[in_index];
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#if 0
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if(threadIdx.x == 0)
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{
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printf("threadwise_direct_convolution: 1: \t"
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"threadIdx.x %u\t"
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"out_index %u, p_out[out_index] %f, \t"
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"wei_index %u, p_wei[wei_index] %f, \t"
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"in_index %u, p_in[in_index] %f\n",
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threadIdx.x,
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out_index,
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p_out[out_index],
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wei_index,
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p_wei[wei_index],
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in_index,
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p_in[in_index]);
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}
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#endif
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}
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}
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}
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}
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}
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}
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}
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}
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template <class TFloat,
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class InDesc,
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class WeiDesc,
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class OutDesc,
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unsigned S,
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unsigned R,
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unsigned InTileSizeH,
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unsigned InTileSizeW,
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unsigned OutTileSizeH,
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unsigned OutTileSizeW,
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unsigned NPerBlock,
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unsigned KPerBlock,
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unsigned YPerBlock,
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unsigned XPerBlock,
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unsigned CPerBlockLoop>
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__device__ void blockwise_convolution(InDesc,
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TFloat* const __restrict__ p_in,
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WeiDesc,
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TFloat* const __restrict__ p_wei,
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OutDesc,
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TFloat* __restrict__ p_out)
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{
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto in_desc = InDesc{};
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constexpr auto wei_desc = WeiDesc{};
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constexpr auto out_desc = OutDesc{};
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#if 1
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if(threadIdx.x == 0)
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{
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print_ConstantTensorDescriptor(in_desc);
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print_ConstantTensorDescriptor(wei_desc);
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print_ConstantTensorDescriptor(out_desc);
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}
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#endif
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constexpr auto in_thread_src_desc = make_ConstantTensorDescriptor(
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Sequence<1, CPerBlockLoop, OutTileSizeH + S - 1, OutTileSizeW + R - 1>{},
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in_desc.GetStrides());
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constexpr auto wei_thread_src_desc =
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make_ConstantTensorDescriptor(Sequence<1, CPerBlockLoop, S, R>{}, wei_desc.GetStrides());
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constexpr auto out_thread_src_desc = make_ConstantTensorDescriptor(
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Sequence<1, 1, OutTileSizeH, OutTileSizeW>{}, out_desc.GetStrides());
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constexpr auto in_thread_dst_desc =
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make_ConstantTensorDescriptor(in_thread_src_desc.GetLengths());
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constexpr auto wei_thread_dst_desc =
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make_ConstantTensorDescriptor(wei_thread_src_desc.GetLengths());
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constexpr auto out_thread_dst_desc =
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make_ConstantTensorDescriptor(out_thread_src_desc.GetLengths());
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const unsigned thread_sz = blockDim.x * blockDim.y * blockDim.z;
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const unsigned thread_id =
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threadIdx.x + threadIdx.y * blockDim.x + threadIdx.z * (blockDim.y * blockDim.x);
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for(unsigned thread_work_id = thread_id;
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thread_work_id < NPerBlock * KPerBlock * YPerBlock * XPerBlock;
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thread_work_id += thread_sz)
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{
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unsigned itmp = thread_work_id;
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unsigned n_thread_work_id = itmp / (KPerBlock * YPerBlock * XPerBlock);
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itmp -= n_thread_work_id * (KPerBlock * YPerBlock * XPerBlock);
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unsigned k_thread_work_id = itmp / (YPerBlock * XPerBlock);
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itmp -= k_thread_work_id * (YPerBlock * XPerBlock);
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unsigned y_thread_work_id = itmp / XPerBlock;
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unsigned x_thread_work_id = itmp - y_thread_work_id * XPerBlock;
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unsigned n_thread_work_begin = n_thread_work_id * 1;
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unsigned k_thread_work_begin = k_thread_work_id * 1;
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unsigned ho_thread_work_begin = y_thread_work_id * OutTileSizeH;
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unsigned wo_thread_work_begin = x_thread_work_id * OutTileSizeW;
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unsigned hi_thread_work_begin = ho_thread_work_begin; // minus padding
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unsigned wi_thread_work_begin = wo_thread_work_begin; // minus padding
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TFloat p_in_thread[1 * CPerBlockLoop * InTileSizeH * InTileSizeW];
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TFloat p_wei_thread[1 * CPerBlockLoop * S * R];
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TFloat p_out_thread[1 * 1 * OutTileSizeH * OutTileSizeW];
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auto f_copy = [](const TFloat& src, TFloat& dst) { dst = src; };
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// copy input tensor into register
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threadwise_4d_tensor_op<TFloat,
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decltype(in_thread_src_desc),
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decltype(in_thread_dst_desc),
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decltype(f_copy)>(
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in_thread_src_desc,
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p_in + in_desc.Get1dIndex(
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n_thread_work_begin, 0, hi_thread_work_begin, wi_thread_work_begin),
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in_thread_dst_desc,
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p_in_thread,
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f_copy);
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// copy weight tensor into register
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threadwise_4d_tensor_op<TFloat,
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decltype(wei_thread_src_desc),
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decltype(wei_thread_dst_desc),
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decltype(f_copy)>(
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wei_thread_src_desc,
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p_wei + wei_desc.Get1dIndex(k_thread_work_begin, 0, 0, 0),
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wei_thread_dst_desc,
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p_wei_thread,
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f_copy);
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// copy output tensor into register
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threadwise_4d_tensor_op<TFloat,
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decltype(out_thread_src_desc),
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decltype(out_thread_dst_desc),
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decltype(f_copy)>(out_thread_src_desc,
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p_out + out_desc.Get1dIndex(n_thread_work_begin,
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k_thread_work_begin,
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ho_thread_work_begin,
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wo_thread_work_begin),
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out_thread_dst_desc,
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p_out_thread,
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f_copy);
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// threadwise convolution
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threadwise_direct_convolution<TFloat,
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decltype(in_thread_dst_desc),
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decltype(wei_thread_dst_desc),
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decltype(out_thread_dst_desc)>(in_thread_dst_desc,
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p_in_thread,
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wei_thread_dst_desc,
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p_wei_thread,
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out_thread_dst_desc,
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p_out_thread);
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// accumulate output tensor into device mem
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threadwise_4d_tensor_op<TFloat,
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decltype(out_thread_dst_desc),
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decltype(out_thread_src_desc),
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decltype(f_copy)>(out_thread_dst_desc,
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p_out_thread,
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out_thread_src_desc,
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p_out + out_desc.Get1dIndex(n_thread_work_begin,
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k_thread_work_begin,
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ho_thread_work_begin,
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wo_thread_work_begin),
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f_copy);
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}
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}
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template <class TFloat,
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class InDesc,
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class WeiDesc,
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class OutDesc,
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unsigned InTileSizeH,
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unsigned InTileSizeW,
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unsigned OutTileSizeH,
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unsigned OutTileSizeW,
|
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unsigned NPerBlock,
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unsigned KPerBlock,
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unsigned YPerBlock,
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unsigned XPerBlock,
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unsigned CPerBlockLoop>
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__global__ void gridwise_convolution(InDesc,
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TFloat* const __restrict__ p_in,
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WeiDesc,
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TFloat* const __restrict__ p_wei,
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OutDesc,
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TFloat* __restrict__ p_out)
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{
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto in_desc = InDesc{};
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constexpr auto wei_desc = WeiDesc{};
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constexpr auto out_desc = OutDesc{};
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constexpr unsigned S = wei_desc.GetLength(I2);
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constexpr unsigned R = wei_desc.GetLength(I3);
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#if 1
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if(threadIdx.x == 0)
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{
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print_ConstantTensorDescriptor(in_desc);
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print_ConstantTensorDescriptor(wei_desc);
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print_ConstantTensorDescriptor(out_desc);
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}
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#endif
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constexpr unsigned NBlockWork = (in_desc.GetLength(I0) + NPerBlock - 1) / NPerBlock;
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constexpr unsigned YBlockWork = (in_desc.GetLength(I2) + YPerBlock - 1) / YPerBlock;
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constexpr unsigned XBlockWork = (in_desc.GetLength(I3) + XPerBlock - 1) / XPerBlock;
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constexpr unsigned KBlockWork = (wei_desc.GetLength(I1) + KPerBlock - 1) / KPerBlock;
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const unsigned block_id =
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blockIdx.x + blockIdx.y * gridDim.x + blockIdx.z * (gridDim.y * gridDim.x);
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constexpr auto in_block_desc =
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make_ConstantTensorDescriptor(Sequence<NPerBlock,
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CPerBlockLoop,
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YPerBlock * OutTileSizeH + S - 1,
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XPerBlock * OutTileSizeW + R - 1>{});
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constexpr auto wei_block_desc =
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make_ConstantTensorDescriptor(Sequence<KPerBlock, CPerBlockLoop, S, R>{});
|
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constexpr auto out_block_desc = make_ConstantTensorDescriptor(
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Sequence<NPerBlock, KPerBlock, YPerBlock * OutTileSizeH, XPerBlock * OutTileSizeW>{});
|
||||
|
||||
__shared__ TFloat p_in_block[NPerBlock * CPerBlockLoop * (YPerBlock * OutTileSizeH + S - 1) *
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||||
(XPerBlock * OutTileSizeW + R - 1)];
|
||||
__shared__ TFloat p_wei_block[KPerBlock * CPerBlockLoop * S * R];
|
||||
__shared__ TFloat p_out_block[NPerBlock * KPerBlock * (YPerBlock * OutTileSizeH) *
|
||||
(XPerBlock * OutTileSizeW)];
|
||||
|
||||
unsigned itmp = block_id;
|
||||
unsigned n_block_work_id = itmp / (KBlockWork * YBlockWork * XBlockWork);
|
||||
itmp -= n_block_work_id * (KBlockWork * YBlockWork * XBlockWork);
|
||||
unsigned k_block_work_id = itmp / (YBlockWork * XBlockWork);
|
||||
itmp -= k_block_work_id * (YBlockWork * XBlockWork);
|
||||
unsigned y_block_work_id = itmp / XBlockWork;
|
||||
unsigned x_block_work_id = itmp - y_block_work_id * XBlockWork;
|
||||
|
||||
unsigned n_block_work_begin = n_block_work_id * NPerBlock;
|
||||
unsigned k_block_work_begin = k_block_work_id * KPerBlock;
|
||||
unsigned y_block_work_begin = y_block_work_id * YPerBlock;
|
||||
unsigned x_block_work_begin = x_block_work_id * XPerBlock;
|
||||
|
||||
unsigned ho_block_work_begin = y_block_work_begin * OutTileSizeH;
|
||||
unsigned wo_block_work_begin = x_block_work_begin * OutTileSizeW;
|
||||
|
||||
unsigned hi_block_work_begin = ho_block_work_begin; // minus padding
|
||||
unsigned wi_block_work_begin = wo_block_work_begin; // minus padding
|
||||
|
||||
for(unsigned c_block_work_begin = 0; c_block_work_begin < in_desc.GetLength(I1);
|
||||
c_block_work_begin += CPerBlockLoop)
|
||||
{
|
||||
auto f_copy = [](const TFloat& src, TFloat& dst) { dst = src; };
|
||||
|
||||
// copy input tensor to LDS
|
||||
blockwise_4d_tensor_op<TFloat,
|
||||
decltype(in_desc),
|
||||
decltype(in_block_desc),
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
64,
|
||||
decltype(f_copy)>(in_desc,
|
||||
p_in + in_desc.Get1dIndex(n_block_work_begin,
|
||||
c_block_work_begin,
|
||||
hi_block_work_begin,
|
||||
wi_block_work_begin),
|
||||
in_block_desc,
|
||||
p_in_block,
|
||||
f_copy);
|
||||
|
||||
// copy weight tensor to LDS
|
||||
blockwise_4d_tensor_op<TFloat,
|
||||
decltype(wei_desc),
|
||||
decltype(wei_block_desc),
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
64,
|
||||
decltype(f_copy)>(
|
||||
wei_desc,
|
||||
p_wei + wei_desc.Get1dIndex(k_block_work_begin, c_block_work_begin, 0, 0),
|
||||
wei_block_desc,
|
||||
p_wei_block,
|
||||
f_copy);
|
||||
|
||||
// copy output tensor to LDS
|
||||
blockwise_4d_tensor_op<TFloat,
|
||||
decltype(out_desc),
|
||||
decltype(out_block_desc),
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
64,
|
||||
decltype(f_copy)>(out_desc,
|
||||
p_out + out_desc.Get1dIndex(n_block_work_begin,
|
||||
k_block_work_begin,
|
||||
ho_block_work_begin,
|
||||
wo_block_work_begin),
|
||||
out_block_desc,
|
||||
p_out_block,
|
||||
f_copy);
|
||||
|
||||
__syncthreads();
|
||||
|
||||
// blockwise convolution
|
||||
blockwise_convolution<TFloat,
|
||||
decltype(in_block_desc),
|
||||
decltype(wei_block_desc),
|
||||
decltype(out_block_desc),
|
||||
S,
|
||||
R,
|
||||
InTileSizeH,
|
||||
InTileSizeW,
|
||||
OutTileSizeH,
|
||||
OutTileSizeW,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
YPerBlock,
|
||||
XPerBlock,
|
||||
CPerBlockLoop>(
|
||||
in_block_desc, p_in_block, wei_block_desc, p_wei_block, out_block_desc, p_out_block);
|
||||
|
||||
__syncthreads();
|
||||
|
||||
// accum output tensor from LDS to device mem
|
||||
blockwise_4d_tensor_op<TFloat,
|
||||
decltype(out_block_desc),
|
||||
decltype(out_desc),
|
||||
1,
|
||||
1,
|
||||
1,
|
||||
64,
|
||||
decltype(f_copy)>(out_block_desc,
|
||||
p_out_block,
|
||||
out_desc,
|
||||
p_out + out_desc.Get1dIndex(n_block_work_begin,
|
||||
k_block_work_begin,
|
||||
ho_block_work_begin,
|
||||
wo_block_work_begin),
|
||||
f_copy);
|
||||
}
|
||||
}
|
||||
169
src/include/constant_tensor_descriptor.cuh
Normal file
169
src/include/constant_tensor_descriptor.cuh
Normal file
@@ -0,0 +1,169 @@
|
||||
#pragma once
|
||||
#include "helper_cuda.h"
|
||||
|
||||
template <class T, T N>
|
||||
struct Constant
|
||||
{
|
||||
const T mValue = N;
|
||||
};
|
||||
|
||||
template <unsigned I>
|
||||
using Index = Constant<unsigned, I>;
|
||||
|
||||
template <unsigned... Is>
|
||||
struct Sequence
|
||||
{
|
||||
static constexpr unsigned nDim = sizeof...(Is);
|
||||
|
||||
const unsigned mData[nDim] = {Is...};
|
||||
|
||||
template <unsigned I>
|
||||
__host__ __device__ constexpr unsigned Get(Index<I>) const
|
||||
{
|
||||
return mData[I];
|
||||
}
|
||||
};
|
||||
|
||||
#if 0
|
||||
template<class F, class T, T... Is>
|
||||
void for_each(F f, std::integer_sequence<T, Is...>)
|
||||
{
|
||||
f(Is)...;
|
||||
}
|
||||
|
||||
template<class F, class T, T N>
|
||||
void for_n_time(F f, Constant<T, N>)
|
||||
{
|
||||
for_each(f, std::make_integer_sequence<T, N>{});
|
||||
}
|
||||
#endif
|
||||
|
||||
template <class Lengths, class Strides>
|
||||
struct ConstantTensorDescriptor
|
||||
{
|
||||
static constexpr unsigned nDim = Lengths::nDim;
|
||||
using NDimConstant = Index<nDim>;
|
||||
|
||||
__host__ __device__ constexpr ConstantTensorDescriptor()
|
||||
{
|
||||
static_assert(Lengths::nDim == Strides::nDim, "nDim not consistent");
|
||||
}
|
||||
|
||||
__host__ __device__ constexpr unsigned GetDimension() const { return nDim; }
|
||||
|
||||
__host__ __device__ constexpr Lengths GetLengths() const { return Lengths{}; }
|
||||
|
||||
__host__ __device__ constexpr Strides GetStrides() const { return Strides{}; }
|
||||
|
||||
template <unsigned I>
|
||||
__host__ __device__ constexpr unsigned GetLength(Index<I>) const
|
||||
{
|
||||
return Lengths{}.Get(Index<I>{});
|
||||
}
|
||||
|
||||
template <unsigned I>
|
||||
__host__ __device__ constexpr unsigned GetStride(Index<I>) const
|
||||
{
|
||||
return Strides{}.Get(Index<I>{});
|
||||
}
|
||||
|
||||
#if 0
|
||||
template <class... Is>
|
||||
__host__ __device__ unsigned Get1dIndex(Is... is) const
|
||||
{
|
||||
static_assert(nDim == sizeof...(Is), "nDim not consistent");
|
||||
const unsigned iss[nDim] = {static_cast<unsigned>(is)...};
|
||||
unsigned idx = 0;
|
||||
for_n_time([&](auto iDim) { idx += iss[iDim] * GetStride<iDim>(); }, NDimConstant{});
|
||||
return idx;
|
||||
}
|
||||
#elif 1
|
||||
// this is ugly, only for 4d
|
||||
__host__ __device__ unsigned Get1dIndex(unsigned n, unsigned c, unsigned h, unsigned w) const
|
||||
{
|
||||
constexpr auto I0 = Index<0>{};
|
||||
constexpr auto I1 = Index<1>{};
|
||||
constexpr auto I2 = Index<2>{};
|
||||
constexpr auto I3 = Index<3>{};
|
||||
|
||||
static_assert(nDim == 4, "nDim not consistent");
|
||||
return n * GetStride(I0) + c * GetStride(I1) + h * GetStride(I2) + w * GetStride(I3);
|
||||
}
|
||||
#endif
|
||||
};
|
||||
|
||||
// this is ugly, only for 4d
|
||||
template <unsigned N, unsigned C, unsigned H, unsigned W>
|
||||
__host__ __device__ constexpr auto calculate_default_strides(Sequence<N, C, H, W>)
|
||||
{
|
||||
return Sequence<C * H * W, H * W, W, 1>{};
|
||||
}
|
||||
|
||||
template <class Lengths>
|
||||
__host__ __device__ constexpr auto make_ConstantTensorDescriptor(Lengths)
|
||||
{
|
||||
using Strides = decltype(calculate_default_strides(Lengths{}));
|
||||
return ConstantTensorDescriptor<Lengths, Strides>{};
|
||||
}
|
||||
|
||||
template <class Lengths, class Strides>
|
||||
__host__ __device__ constexpr auto make_ConstantTensorDescriptor(Lengths, Strides)
|
||||
{
|
||||
return ConstantTensorDescriptor<Lengths, Strides>{};
|
||||
}
|
||||
|
||||
// this is ugly, only for 4d
|
||||
template <class InDesc, class WeiDesc>
|
||||
__host__ __device__ constexpr auto get_output_4d_tensor_descriptor(InDesc, WeiDesc)
|
||||
{
|
||||
constexpr auto in_desc = InDesc{};
|
||||
constexpr auto wei_desc = WeiDesc{};
|
||||
|
||||
constexpr auto I0 = Index<0>{};
|
||||
constexpr auto I1 = Index<1>{};
|
||||
constexpr auto I2 = Index<2>{};
|
||||
constexpr auto I3 = Index<3>{};
|
||||
|
||||
static_assert(in_desc.GetDimension() == 4, "input nDim is not 4");
|
||||
static_assert(wei_desc.GetDimension() == 4, "weight nDim is not 4");
|
||||
static_assert(in_desc.GetLength(I1) == wei_desc.GetLength(I1),
|
||||
"input & weight dimension not consistent");
|
||||
|
||||
constexpr auto N = in_desc.GetLength(I0);
|
||||
constexpr auto HI = in_desc.GetLength(I2);
|
||||
constexpr auto WI = in_desc.GetLength(I3);
|
||||
|
||||
constexpr auto K = wei_desc.GetLength(I0);
|
||||
constexpr auto S = wei_desc.GetLength(I2);
|
||||
constexpr auto R = wei_desc.GetLength(I3);
|
||||
|
||||
constexpr auto HO = HI - S + 1;
|
||||
constexpr auto WO = WI - R + 1;
|
||||
|
||||
return make_ConstantTensorDescriptor(Sequence<N, K, HO, WO>{});
|
||||
}
|
||||
|
||||
// this is ugly, only for 4d
|
||||
template <class TDesc>
|
||||
__host__ __device__ void print_ConstantTensorDescriptor(TDesc)
|
||||
{
|
||||
constexpr auto desc = TDesc{};
|
||||
|
||||
constexpr auto I0 = Index<0>{};
|
||||
constexpr auto I1 = Index<1>{};
|
||||
constexpr auto I2 = Index<2>{};
|
||||
constexpr auto I3 = Index<3>{};
|
||||
|
||||
static_assert(desc.GetDimension() == 4, "dim is not 4");
|
||||
|
||||
printf("dim %u, lengths {%u %u %u %u}, strides {%u %u %u %u}\n",
|
||||
desc.GetDimension(),
|
||||
desc.GetLength(I0),
|
||||
desc.GetLength(I1),
|
||||
desc.GetLength(I2),
|
||||
desc.GetLength(I3),
|
||||
desc.GetStride(I0),
|
||||
desc.GetStride(I1),
|
||||
desc.GetStride(I2),
|
||||
desc.GetStride(I3));
|
||||
}
|
||||
@@ -1,30 +0,0 @@
|
||||
#pragma once
|
||||
#include <algorithm>
|
||||
#include "helper_cuda.h"
|
||||
#include "tensor.hpp"
|
||||
|
||||
template <unsigned NDim>
|
||||
struct DeviceTensorDescriptor
|
||||
{
|
||||
__host__ __device__ DeviceTensorDescriptor() = default;
|
||||
|
||||
__host__ DeviceTensorDescriptor(const TensorDescriptor& host_desc)
|
||||
{
|
||||
assert(NDim == host_desc.GetDimension());
|
||||
std::copy(host_desc.GetLengths().begin(), host_desc.GetLengths().end(), mpLengths);
|
||||
std::copy(host_desc.GetStrides().begin(), host_desc.GetStrides().end(), mpStrides);
|
||||
}
|
||||
|
||||
__host__ __device__ unsigned GetLength(unsigned i) const { return mpLengths[i]; }
|
||||
|
||||
__host__ __device__ unsigned GetStride(unsigned i) const { return mpStrides[i]; }
|
||||
|
||||
// this is ugly
|
||||
__host__ __device__ unsigned Get1dIndex(unsigned n, unsigned c, unsigned h, unsigned w) const
|
||||
{
|
||||
return n * mpStrides[0] + c * mpStrides[1] + h * mpStrides[2] + w * mpStrides[3];
|
||||
}
|
||||
|
||||
unsigned mpLengths[NDim];
|
||||
unsigned mpStrides[NDim];
|
||||
};
|
||||
60
src/include/device_tensor_descriptor.cuh
Normal file
60
src/include/device_tensor_descriptor.cuh
Normal file
@@ -0,0 +1,60 @@
|
||||
#pragma once
|
||||
#include <algorithm>
|
||||
#include "constant_tensor_descriptor.cuh"
|
||||
#include "helper_cuda.h"
|
||||
#include "tensor.hpp"
|
||||
|
||||
template <unsigned NDim>
|
||||
struct DeviceTensorDescriptor
|
||||
{
|
||||
__host__ __device__ DeviceTensorDescriptor() = default;
|
||||
|
||||
__host__ DeviceTensorDescriptor(const TensorDescriptor& host_desc)
|
||||
{
|
||||
assert(NDim == host_desc.GetDimension());
|
||||
std::copy(host_desc.GetLengths().begin(), host_desc.GetLengths().end(), mpLengths);
|
||||
std::copy(host_desc.GetStrides().begin(), host_desc.GetStrides().end(), mpStrides);
|
||||
}
|
||||
|
||||
__host__ __device__ unsigned GetLength(unsigned i) const { return mpLengths[i]; }
|
||||
|
||||
__host__ __device__ unsigned GetStride(unsigned i) const { return mpStrides[i]; }
|
||||
|
||||
// this is ugly, only for 4d
|
||||
__host__ __device__ unsigned Get1dIndex(unsigned n, unsigned c, unsigned h, unsigned w) const
|
||||
{
|
||||
return n * mpStrides[0] + c * mpStrides[1] + h * mpStrides[2] + w * mpStrides[3];
|
||||
}
|
||||
|
||||
unsigned mpLengths[NDim];
|
||||
unsigned mpStrides[NDim];
|
||||
};
|
||||
|
||||
// this is ugly, only for 4d
|
||||
template <class TConstTensorDesc>
|
||||
__host__ __device__ auto make_DeviceTensorDescriptor(TConstTensorDesc)
|
||||
{
|
||||
static_assert(TConstTensorDesc::nDim == 4, "nDim is not 4");
|
||||
|
||||
constexpr auto I0 = Index<0>{};
|
||||
constexpr auto I1 = Index<1>{};
|
||||
constexpr auto I2 = Index<2>{};
|
||||
constexpr auto I3 = Index<3>{};
|
||||
constexpr auto const_desc = TConstTensorDesc{};
|
||||
|
||||
constexpr auto ndim = const_desc.GetDimension();
|
||||
|
||||
auto desc = DeviceTensorDescriptor<ndim>{};
|
||||
|
||||
desc.mpLengths[0] = const_desc.GetLength(I0);
|
||||
desc.mpLengths[1] = const_desc.GetLength(I1);
|
||||
desc.mpLengths[2] = const_desc.GetLength(I2);
|
||||
desc.mpLengths[3] = const_desc.GetLength(I3);
|
||||
|
||||
desc.mpStrides[0] = const_desc.GetStride(I0);
|
||||
desc.mpStrides[1] = const_desc.GetStride(I1);
|
||||
desc.mpStrides[2] = const_desc.GetStride(I2);
|
||||
desc.mpStrides[3] = const_desc.GetStride(I3);
|
||||
|
||||
return desc;
|
||||
}
|
||||
@@ -1,5 +1,5 @@
|
||||
#pragma once
|
||||
#include "device_tensor.cuh"
|
||||
#include "device_tensor_descriptor.cuh"
|
||||
|
||||
template <class TFloat,
|
||||
unsigned NWorkLen0,
|
||||
@@ -13,7 +13,7 @@ __device__ void blockwise_4d_tensor_op(const DeviceTensorDescriptor<4>& src_desc
|
||||
TFloat* __restrict__ p_dst,
|
||||
F f)
|
||||
{
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("blockwise_4d_tensor_op: 0: \t"
|
||||
@@ -80,7 +80,7 @@ __device__ void blockwise_4d_tensor_op(const DeviceTensorDescriptor<4>& src_desc
|
||||
|
||||
f(p_src[dindex], p_dst[sindex]);
|
||||
|
||||
#if 1
|
||||
#if 0
|
||||
// if(threadIdx.x == 0)
|
||||
{
|
||||
printf("blockwise_4d_tensor_op: 1: thread id %u, \t"
|
||||
@@ -106,7 +106,7 @@ __device__ void threadwise_4d_tensor_op(const DeviceTensorDescriptor<4>& src_des
|
||||
TFloat* __restrict__ p_dst,
|
||||
F f)
|
||||
{
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("threadwise_4d_tensor_op: 0: \t"
|
||||
@@ -151,7 +151,7 @@ __device__ void threadwise_4d_tensor_op(const DeviceTensorDescriptor<4>& src_des
|
||||
|
||||
f(p_src[sindex], p_dst[dindex]);
|
||||
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("threadwise_4d_tensor_op: 1: thread id %u, \t"
|
||||
@@ -178,7 +178,7 @@ __device__ void threadwise_direct_convolution(const DeviceTensorDescriptor<4>& i
|
||||
const DeviceTensorDescriptor<4>& out_desc,
|
||||
TFloat* __restrict__ p_out)
|
||||
{
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("threadwise_direct_convolution: 0: \t"
|
||||
@@ -212,7 +212,7 @@ __device__ void threadwise_direct_convolution(const DeviceTensorDescriptor<4>& i
|
||||
out_desc.GetStride(2),
|
||||
out_desc.GetStride(3));
|
||||
}
|
||||
#elif 1
|
||||
#elif 0
|
||||
{
|
||||
printf("threadwise_direct_convolution: 0: \t"
|
||||
"threadIdx.x %u \t"
|
||||
@@ -275,7 +275,7 @@ __device__ void threadwise_direct_convolution(const DeviceTensorDescriptor<4>& i
|
||||
|
||||
p_out[out_index] += p_wei[wei_index] * p_in[in_index];
|
||||
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("threadwise_direct_convolution: 1: \t"
|
||||
@@ -320,7 +320,7 @@ __device__ void blockwise_convolution(const DeviceTensorDescriptor<4>& in_desc,
|
||||
const DeviceTensorDescriptor<4>& out_desc,
|
||||
TFloat* __restrict__ p_out)
|
||||
{
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("blockwise_convolution: 0: \t"
|
||||
@@ -501,7 +501,7 @@ __global__ void gridwise_convolution(const DeviceTensorDescriptor<4> in_desc,
|
||||
const DeviceTensorDescriptor<4> out_desc,
|
||||
TFloat* __restrict__ p_out)
|
||||
{
|
||||
#if 1
|
||||
#if 0
|
||||
if(threadIdx.x == 0)
|
||||
{
|
||||
printf("gridwise_convolution: 0: \t"
|
||||
|
||||
@@ -69,28 +69,25 @@ auto construct_f_unpack_args(F, T args)
|
||||
struct TensorDescriptor
|
||||
{
|
||||
TensorDescriptor() = delete;
|
||||
TensorDescriptor(DataType_t t, std::initializer_list<std::size_t> lens);
|
||||
TensorDescriptor(DataType_t t,
|
||||
std::initializer_list<std::size_t> lens,
|
||||
TensorDescriptor(std::initializer_list<std::size_t> lens);
|
||||
TensorDescriptor(std::initializer_list<std::size_t> lens,
|
||||
std::initializer_list<std::size_t> strides);
|
||||
TensorDescriptor(DataType_t t, std::vector<std::size_t> lens, std::vector<std::size_t> strides);
|
||||
TensorDescriptor(std::vector<std::size_t> lens, std::vector<std::size_t> strides);
|
||||
|
||||
void CalculateStrides();
|
||||
|
||||
template <class Range>
|
||||
TensorDescriptor(DataType_t t, const Range& lens)
|
||||
: mLens(lens.begin(), lens.end()), mDataType(t)
|
||||
TensorDescriptor(const Range& lens) : mLens(lens.begin(), lens.end())
|
||||
{
|
||||
this->CalculateStrides();
|
||||
}
|
||||
|
||||
template <class Range1, class Range2>
|
||||
TensorDescriptor(DataType_t t, const Range1& lens, const Range2& strides)
|
||||
: mLens(lens.begin(), lens.end()), mStrides(strides.begin(), strides.end()), mDataType(t)
|
||||
TensorDescriptor(const Range1& lens, const Range2& strides)
|
||||
: mLens(lens.begin(), lens.end()), mStrides(strides.begin(), strides.end())
|
||||
{
|
||||
}
|
||||
|
||||
DataType_t GetDataType() const;
|
||||
std::size_t GetDimension() const;
|
||||
std::size_t GetElementSize() const;
|
||||
std::size_t GetElementSpace() const;
|
||||
@@ -107,7 +104,6 @@ struct TensorDescriptor
|
||||
}
|
||||
|
||||
private:
|
||||
DataType_t mDataType;
|
||||
std::vector<std::size_t> mLens;
|
||||
std::vector<std::size_t> mStrides;
|
||||
};
|
||||
@@ -220,22 +216,23 @@ template <class T>
|
||||
struct Tensor
|
||||
{
|
||||
template <class X>
|
||||
Tensor(std::initializer_list<X> lens)
|
||||
: mDesc(DataType<T>{}, lens), mData(mDesc.GetElementSpace())
|
||||
Tensor(std::initializer_list<X> lens) : mDesc(lens), mData(mDesc.GetElementSpace())
|
||||
{
|
||||
}
|
||||
|
||||
template <class X>
|
||||
Tensor(std::vector<X> lens) : mDesc(DataType<T>{}, lens), mData(mDesc.GetElementSpace())
|
||||
Tensor(std::vector<X> lens) : mDesc(lens), mData(mDesc.GetElementSpace())
|
||||
{
|
||||
}
|
||||
|
||||
template <class X, class Y>
|
||||
Tensor(std::vector<X> lens, std::vector<Y> strides)
|
||||
: mDesc(DataType<T>{}, lens, strides), mData(mDesc.GetElementSpace())
|
||||
: mDesc(lens, strides), mData(mDesc.GetElementSpace())
|
||||
{
|
||||
}
|
||||
|
||||
Tensor(const TensorDescriptor& desc) : mDesc(desc), mData(mDesc.GetElementSpace()) {}
|
||||
|
||||
template <class G>
|
||||
void GenerateTensorValue(G g, std::size_t num_thread = 1)
|
||||
{
|
||||
|
||||
Reference in New Issue
Block a user