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Commit b4abe4e2 authored by Astha Rai's avatar Astha Rai
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integrated variable for thread distribution into device elementwise and added... 

integrated variable for thread distribution into device elementwise and added as parameter for gridwise elementwise
parent b61bb071
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Showing with 32 additions and 45 deletions
include/ck/tensor_operation/gpu/device/device_elementwise_2d.hpp
View file @ b4abe4e2
......@@ -69,12 +69,14 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
using OutDataTypePointerTuple = decltype(GenerateOutDataTypePointerTuple());
template <typename Desc_MN>
static auto PadDescriptor_MN_2d(Desc_MN desc_mn, index_t gridSize, index_t blockSize)
static auto PadDescriptor_MN_2d(Desc_MN desc_mn, index_t gridSize, index_t blockSize, index_t num_threads_m, index_t num_threads_n)
{
std::ignore = blockSize;
std::ignore = gridSize;
const auto m = desc_mn.GetLength(I0);
const auto n = desc_mn.GetLength(I1);
const index_t loop_step_m = MPerThread;
const index_t loop_step_n = gridSize * blockSize * NPerThread;
const index_t loop_step_m = num_threads_m * MPerThread;
const index_t loop_step_n = num_threads_n * NPerThread;
const auto pad_m = math::integer_least_multiple(m, loop_step_m) - m;
const auto pad_n = math::integer_least_multiple(n, loop_step_n) - n;
std::cout << NumDim_m << " m: " << m << " loop_step_m: " << loop_step_m
......@@ -92,7 +94,9 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
static auto MakeDescriptor_MN(const std::array<index_t, NumDim>& lengths,
const std::array<index_t, NumDim>& stride,
index_t gridSize,
index_t blockSize)
index_t blockSize,
index_t num_threads_m,
index_t num_threads_n)
{
auto tupleOfShape = generate_tuple([&](auto I) { return lengths[I]; }, Number<NumDim>{});
auto tupleOfStride = generate_tuple([&](auto I) { return stride[I]; }, Number<NumDim>{});
......@@ -117,10 +121,10 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
make_tuple(mDimIds, nDimIds),
make_tuple(Sequence<0>{}, Sequence<1>{}));
return PadDescriptor_MN_2d(desc_mn, gridSize, blockSize);
return PadDescriptor_MN_2d(desc_mn, gridSize, blockSize, num_threads_m, num_threads_n);
}
else
return PadDescriptor_MN_2d(desc, gridSize, blockSize);
return PadDescriptor_MN_2d(desc, gridSize, blockSize, num_threads_m, num_threads_n);
}
template <index_t TupleSize>
......@@ -130,11 +134,11 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
[&](auto) {
if constexpr(NumDim > 2)
{
return MakeDescriptor_MN({1, 1}, {1, 1}, 1, 1);
return MakeDescriptor_MN({1, 1}, {1, 1}, 1, 1, 1, 1);
}
else
{
return MakeDescriptor_MN({1}, {1}, 1, 1);
return MakeDescriptor_MN({1}, {1}, 1, 1, 1, 1);
};
},
Number<TupleSize>{});
......@@ -150,8 +154,6 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
ElementwiseOperation,
MPerThread,
NPerThread,
//num_threads_m,
//num_threads_n,
InScalarPerVectorSeq,
OutScalarPerVectorSeq>;
......@@ -169,7 +171,9 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
outStridesArray_(outStridesArray),
elementwise_op_(elementwise_op),
blockSize_(256),
gridSize_(120) // FIXME - Calculate the grid size by number of CU in the future
gridSize_(120), // FIXME - Calculate the grid size by number of CU in the future
num_threads_m_((gridSize_*blockSize_)/8),
num_threads_n_(8)
{
static_assert(NumDim_m > 0, "");
static_assert(NumDim_n > 0, "");
......@@ -191,19 +195,16 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
in_grid_2d_desc_tuple_ = generate_tuple(
[&](auto I) {
return MakeDescriptor_MN(
lengths, inStridesArray[I.value], gridSize_, blockSize_);
lengths, inStridesArray[I.value], gridSize_, blockSize_, num_threads_m_, num_threads_n_);
},
Number<NumInput>{});
out_grid_2d_desc_tuple_ = generate_tuple(
[&](auto I) {
return MakeDescriptor_MN(
lengths, outStridesArray[I.value], gridSize_, blockSize_);
lengths, outStridesArray[I.value], gridSize_, blockSize_, num_threads_m_, num_threads_n_);
},
Number<NumOutput>{});
//num_threads_m = 1;
//num_threads_n = gridSize_ * blockSize_;
}
InDataTypePointerTuple in_dev_buffers_;
......@@ -218,6 +219,8 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
ElementwiseOperation elementwise_op_;
index_t blockSize_;
index_t gridSize_;
index_t num_threads_m_;
index_t num_threads_n_;
};
struct Invoker : public BaseInvoker
......@@ -240,7 +243,9 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
arg.out_grid_2d_desc_tuple_,
arg.in_dev_buffers_,
arg.out_dev_buffers_,
arg.elementwise_op_);
arg.elementwise_op_,
arg.num_threads_m_,
arg.num_threads_n_);
return elapsed_time;
}
......@@ -258,9 +263,6 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
if(pArg == nullptr)
return false;
std::cout << "made it here" << std::endl;
std::cout << "lengths back: " << pArg->lengths_.back() << std::endl;
if(pArg->lengths_.back() % MPerThread != 0)
return false;
......@@ -273,20 +275,12 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
(lengths[vectorDim] % scalarPerVector == 0 ||
lengths[vectorDim] % scalarPerVector == lengths[vectorDim]))
{
// std::cout << "Check 1 passed" << std::endl;
return true;
}
// std::cout << "Check 1 failed " << std::endl;
// std::cout << "ISPVV Check 2 starting" << std::endl;
// std::cout << "strides[vectorDim]: " << strides[vectorDim] << std::endl;
if(strides[vectorDim] != 1 && scalarPerVector == strides[vectorDim])
{
// std::cout << "Check 2 passed " << std::endl;
return true;
}
// std::cout << "Check 2 failed" << std::endl;
return false;
};
......@@ -300,7 +294,6 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
NumDim_m - 1))
valid = false;
});
std::cout << "valid after loop through input: " << valid << std::endl;
static_for<0, NumOutput, 1>{}([&](auto I) {
std::cout << "running 2: " << I << std::endl;
......@@ -310,7 +303,6 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
NumDim - 1))
valid = false;
});
std::cout << "valid after loop through output: " << valid << std::endl;
return valid;
};
......
include/ck/tensor_operation/gpu/grid/gridwise_elementwise_2d.hpp
View file @ b4abe4e2
......@@ -20,13 +20,17 @@ __global__ void kernel_elementwise_2d(const InGrid2dDescTuple in_grid_2d_desc_tu
const OutGrid2dDescTuple out_grid_2d_desc_tuple,
const InDataTypePointerTuple p_in_global_tuple,
const OutDataTypePointerTuple p_out_global_tuple,
const ElementwiseOperation elementwise_op)
const ElementwiseOperation elementwise_op,
const index_t num_threads_m,
const index_t num_threads_n)
{
GridwiseElementwise2dFunctor::Run(in_grid_2d_desc_tuple,
out_grid_2d_desc_tuple,
p_in_global_tuple,
p_out_global_tuple,
elementwise_op);
elementwise_op,
num_threads_m,
num_threads_n);
}
template <typename InGrid2dDescTuple,
......@@ -61,7 +65,9 @@ struct GridwiseElementwise_2D
const OutGrid2dDescTuple out_grid_2d_desc_tuple,
const InDataTypePointerTuple p_in_global_tuple,
const OutDataTypePointerTuple p_out_global_tuple,
const ElementwiseOperation elementwise_op)
const ElementwiseOperation elementwise_op,
const index_t num_threads_m,
const index_t num_threads_n)
{
auto in_thread_buf_tuple = generate_tuple(
[&](auto I) {
......@@ -101,14 +107,6 @@ struct GridwiseElementwise_2D
},
Number<NumOutput>{});
const index_t blockSize = get_block_size();
const index_t blockPerGrid = get_grid_size();
const index_t totalNumThread = blockSize * blockPerGrid;
const index_t num_threads_m = 4;
const index_t num_threads_n = totalNumThread/4;
//static_assert(num_threads_m * num_threads_n == totalNumThread, "error: threads per dimension not equal to total threads");
const auto M = in_grid_2d_desc_tuple[I0].GetLength(I0);
const auto N = in_grid_2d_desc_tuple[I0].GetLength(I1);
......@@ -201,9 +199,6 @@ struct GridwiseElementwise_2D
});
});
// static_for<0, MPerThread * NPerThread, 1>{}(
//[&](auto i) { out_thread_buf_tuple(I0)(i) = 1; });
static_for<0, NumOutput, 1>{}([&](auto I) {
out_global_store_tuple(I).Run(thread_buffer_desc_mn,
make_tuple(I0, I0),
......
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