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Merged
johannes-graner merged 2 commits into from
Jan 14, 2026
Merged

[CK Profiler] Initialize tensors on GPU in CK profiler #3550

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Initialize tensors on GPU in CK profiler
johannes-graner Jan 12, 2026
65ed81d
Kick CI
johannes-graner Jan 12, 2026
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64 changes: 45 additions & 19 deletions profiler/include/profiler/profile_grouped_conv_bwd_data_impl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -58,37 +58,63 @@ bool profile_grouped_conv_bwd_data_impl(int do_verification,
const auto in_g_n_c_wis_desc =
ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(conv_param);

Tensor<OutDataType> out(out_g_n_k_wos_desc);
Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
Tensor<InDataType> in_host(in_g_n_c_wis_desc);
Tensor<InDataType> in_device(in_g_n_c_wis_desc);
std::cout << "out: " << out_g_n_k_wos_desc << std::endl;
std::cout << "wei: " << wei_g_k_c_xs_desc << std::endl;
std::cout << "in: " << in_g_n_c_wis_desc << std::endl;

std::cout << "out: " << out.mDesc << std::endl;
std::cout << "wei: " << wei.mDesc << std::endl;
std::cout << "in: " << in_host.mDesc << std::endl;
// Get element space sizes
const auto out_element_space_size = out_g_n_k_wos_desc.GetElementSpaceSize();
const auto wei_element_space_size = wei_g_k_c_xs_desc.GetElementSpaceSize();
const auto in_element_space_size = in_g_n_c_wis_desc.GetElementSpaceSize();

// Allocate GPU buffers
DeviceMem out_device_buf(sizeof(OutDataType) * out_element_space_size);
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei_element_space_size);
DeviceMem in_device_buf(sizeof(InDataType) * in_element_space_size);

// Generate data directly on GPU using DeviceMem methods
switch(init_method)
{
case 0: break;
case 0:
// Zero initialization
out_device_buf.SetZero();
wei_device_buf.SetZero();
break;
case 1:
out.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
// Discrete integer values in range [-5, 5]
out_device_buf.FillUniformRandInteger<OutDataType>(-5, 5);
wei_device_buf.FillUniformRandInteger<WeiDataType>(-5, 5);
break;
case 2:
out.GenerateTensorValue(GeneratorTensor_3<OutDataType>{0.0, 1.0});
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
// Continuous float values
out_device_buf.FillUniformRandFp<OutDataType>(0.0f, 1.0f);
wei_device_buf.FillUniformRandFp<WeiDataType>(-0.5f, 0.5f);
break;
default:
out.GenerateTensorValue(GeneratorTensor_1<OutDataType>{1});
wei.GenerateTensorValue(GeneratorTensor_1<WeiDataType>{1});
// Constant value 1
out_device_buf.SetValue<OutDataType>(ck::type_convert<OutDataType>(1));
wei_device_buf.SetValue<WeiDataType>(ck::type_convert<WeiDataType>(1));
}

DeviceMem out_device_buf(sizeof(OutDataType) * out.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
DeviceMem in_device_buf(sizeof(InDataType) * in_device.mDesc.GetElementSpaceSize());
// Create host tensors (needed only for verification)
Tensor<OutDataType> out(out_g_n_k_wos_desc);
Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
Tensor<InDataType> in_host(in_g_n_c_wis_desc);
Tensor<InDataType> in_device(in_g_n_c_wis_desc);

out_device_buf.ToDevice(out.mData.data());
wei_device_buf.ToDevice(wei.mData.data());
// Copy GPU→CPU only if verification is enabled
if(do_verification == 1 || do_verification == 2)
{
out_device_buf.FromDevice(out.mData.data());
wei_device_buf.FromDevice(wei.mData.data());
}

// Copy to host only if CPU verification is needed
if(do_verification == 1)
{
out_device_buf.FromDevice(out.mData.data());
wei_device_buf.FromDevice(wei.mData.data());
}

// Allocate GPU reference buffer (used only if do_verification == 2)
DeviceMem gpu_ref_in_buf(
Expand Down
53 changes: 35 additions & 18 deletions profiler/include/profiler/profile_grouped_conv_bwd_weight_impl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -63,34 +63,51 @@ bool profile_grouped_conv_bwd_weight_impl(int do_verification,
const auto out_g_n_k_wos_desc =
ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(conv_param);

Tensor<InDataType> input(in_g_n_c_wis_desc);
Tensor<WeiDataType> weight_host_result(wei_g_k_c_xs_desc);
Tensor<WeiDataType> weight_device_result(wei_g_k_c_xs_desc);
Tensor<OutDataType> output(out_g_n_k_wos_desc);
std::cout << "input: " << in_g_n_c_wis_desc << std::endl;
std::cout << "weight: " << wei_g_k_c_xs_desc << std::endl;
std::cout << "output: " << out_g_n_k_wos_desc << std::endl;

// Get element space sizes
const auto input_element_space_size = in_g_n_c_wis_desc.GetElementSpaceSize();
const auto weight_element_space_size = wei_g_k_c_xs_desc.GetElementSpaceSize();
const auto output_element_space_size = out_g_n_k_wos_desc.GetElementSpaceSize();

std::cout << "input: " << input.mDesc << std::endl;
std::cout << "weight: " << weight_host_result.mDesc << std::endl;
std::cout << "output: " << output.mDesc << std::endl;
// Allocate GPU buffers
DeviceMem in_device_buf(sizeof(InDataType) * input_element_space_size);
DeviceMem wei_device_buf(sizeof(WeiDataType) * weight_element_space_size);
DeviceMem out_device_buf(sizeof(OutDataType) * output_element_space_size);

// Generate data directly on GPU using DeviceMem methods
switch(init_method)
{
case 0: break;
case 0:
// Zero initialization
in_device_buf.SetZero();
out_device_buf.SetZero();
break;
case 1:
input.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
output.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
// Discrete integer values in range [-5, 5]
in_device_buf.FillUniformRandInteger<InDataType>(-5, 5);
out_device_buf.FillUniformRandInteger<OutDataType>(-5, 5);
break;
default:
input.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
output.GenerateTensorValue(GeneratorTensor_3<OutDataType>{-0.5, 0.5});
// Continuous float values
in_device_buf.FillUniformRandFp<InDataType>(0.0f, 1.0f);
out_device_buf.FillUniformRandFp<OutDataType>(-0.5f, 0.5f);
}

DeviceMem in_device_buf(sizeof(InDataType) * input.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiDataType) *
weight_device_result.mDesc.GetElementSpaceSize());
DeviceMem out_device_buf(sizeof(OutDataType) * output.mDesc.GetElementSpaceSize());
// Create host tensors (needed only for verification)
Tensor<InDataType> input(in_g_n_c_wis_desc);
Tensor<WeiDataType> weight_host_result(wei_g_k_c_xs_desc);
Tensor<WeiDataType> weight_device_result(wei_g_k_c_xs_desc);
Tensor<OutDataType> output(out_g_n_k_wos_desc);

in_device_buf.ToDevice(input.mData.data());
out_device_buf.ToDevice(output.mData.data());
// Copy to host only if CPU verification is needed
if(do_verification == 1)
{
in_device_buf.FromDevice(input.mData.data());
out_device_buf.FromDevice(output.mData.data());
}

// Allocate GPU reference buffer (used only if do_verification == 2)
DeviceMem gpu_ref_wei_buf(
Expand Down
52 changes: 35 additions & 17 deletions profiler/include/profiler/profile_grouped_conv_fwd_impl.hpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -86,33 +86,51 @@ bool profile_grouped_conv_fwd_impl(int do_verification,
copy(conv_param.input_left_pads_, input_left_pads);
copy(conv_param.input_right_pads_, input_right_pads);

Tensor<InDataType> input(in_g_n_c_wis_desc);
Tensor<WeiDataType> weight(wei_g_k_c_xs_desc);
Tensor<OutDataType> host_output(out_g_n_k_wos_desc);
Tensor<OutDataType> device_output(out_g_n_k_wos_desc);
// Get element space sizes for GPU allocation
const auto input_size = in_g_n_c_wis_desc.GetElementSpaceSize();
const auto weight_size = wei_g_k_c_xs_desc.GetElementSpaceSize();
const auto output_size = out_g_n_k_wos_desc.GetElementSpaceSize();

std::cout << "input: " << in_g_n_c_wis_desc << std::endl;
std::cout << "weight: " << wei_g_k_c_xs_desc << std::endl;
std::cout << "output: " << out_g_n_k_wos_desc << std::endl;

std::cout << "input: " << input.mDesc << std::endl;
std::cout << "weight: " << weight.mDesc << std::endl;
std::cout << "output: " << host_output.mDesc << std::endl;
// Allocate GPU memory first (GPU-first workflow)
DeviceMem in_device_buf(sizeof(InDataType) * input_size);
DeviceMem wei_device_buf(sizeof(WeiDataType) * weight_size);
DeviceMem out_device_buf(sizeof(OutDataType) * output_size);

// Generate data directly on GPU using DeviceMem methods
switch(init_method)
{
case 0: break;
case 0:
// Zero initialization
in_device_buf.SetZero();
wei_device_buf.SetZero();
break;
case 1:
input.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
weight.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
// Discrete integer generation: {-5, -4, -3, ..., 3, 4}
in_device_buf.FillUniformRandInteger<InDataType>(-5, 5);
wei_device_buf.FillUniformRandInteger<WeiDataType>(-5, 5);
break;
default:
input.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
weight.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
// Continuous float generation
in_device_buf.FillUniformRandFp<InDataType>(0.0f, 1.0f);
wei_device_buf.FillUniformRandFp<WeiDataType>(-0.5f, 0.5f);
}

DeviceMem in_device_buf(sizeof(InDataType) * input.mDesc.GetElementSpaceSize());
DeviceMem wei_device_buf(sizeof(WeiDataType) * weight.mDesc.GetElementSpaceSize());
DeviceMem out_device_buf(sizeof(OutDataType) * device_output.mDesc.GetElementSpaceSize());
// Create host tensors (for verification if needed)
Tensor<InDataType> input(in_g_n_c_wis_desc);
Tensor<WeiDataType> weight(wei_g_k_c_xs_desc);
Tensor<OutDataType> host_output(out_g_n_k_wos_desc);
Tensor<OutDataType> device_output(out_g_n_k_wos_desc);

in_device_buf.ToDevice(input.mData.data());
wei_device_buf.ToDevice(weight.mData.data());
// Copy to host only if CPU verification is needed
if(do_verification == 1)
{
in_device_buf.FromDevice(input.mData.data());
wei_device_buf.FromDevice(weight.mData.data());
}

// Allocate GPU reference buffer (used only if do_verification == 2)
DeviceMem gpu_ref_out_buf(
Expand Down