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WIP: DP4AMatMul fix matmul for subgoup size 64 GPUs #23637

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Feb 13, 2025
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WIP: DP4AMatMul fix matmul for subgoup size 64 GPUs #23637

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45 changes: 13 additions & 32 deletions onnxruntime/contrib_ops/webgpu/quantization/matmul_nbits.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -535,42 +535,23 @@ Status DP4AMatMulQuantizeProgram::GenerateShaderCode(ShaderHelper& shader) const
shader.AddOutput("output", ShaderUsage::UseUniform);
shader.AddOutput("scales", ShaderUsage::UseUniform);

shader.AdditionalImplementation() << R"ADDNL_FN(
var<workgroup> max_values : array<input_a_element_t, 4>;
)ADDNL_FN";

shader.MainFunctionBody() << R"MAIN_FN(
var local_a = input_a[global_idx];
var max_val = subgroupMax(abs(local_a));
var max_temp = max(max_val.xy, max_val.zw);
var scale = max(max_temp[0], max_temp[1]);
if (local_idx % sg_size == 0) {
max_values[local_idx / sg_size] = scale;
}
workgroupBarrier();

if (sg_size == 8)
var local_a : array<vec4<input_a_element_t>, 32>;
var max_value:vec4<input_a_element_t> = vec4<input_a_element_t>(0);
for (var idx:u32=0;idx<32;idx+=1)
{
scale = max(max_values[0], max_values[1]);
scale = max(scale, max_values[2]);
scale = max(scale, max_values[3]);
local_a[idx] = input_a[workgroup_id.x*32 + idx];
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max_value = max(max_value, abs(local_a[idx]));
}
else if (sg_size == 16)
{
scale = max(max_values[0], max_values[1]);
}
else
{
scale = max_values[0];
}

var norm_a = local_a/scale;
output[global_idx] = pack4x8snorm(vec4<f32>(norm_a));
if (local_idx == 0)
var scale = max(max_value.x, max_value.y);
scale = max(scale, max_value.z);
scale = max(scale, max_value.w);
for (var idx:u32=0;idx<32;idx+=1)
{
// 127 is the max value of signed int8 [-127,127] used by pack4x8snorm for 1.0f.
scales[workgroup_idx] = scale/127;
output[workgroup_id.x*32+idx] = pack4x8snorm(vec4<f32>(local_a[idx]/scale));
}
// 127 is the max value of signed int8 [-127,127] used by pack4x8snorm for 1.0f.
scales[workgroup_id.x] = scale/127;
)MAIN_FN";
return Status::OK();
}
Expand Down Expand Up @@ -838,7 +819,7 @@ Status MatMulNBits::ComputeInternal(onnxruntime::webgpu::ComputeContext& context

constexpr uint32_t kBlockSizeA = 128;
DP4AMatMulQuantizeProgram quantize_program;
quantize_program.SetWorkgroupSize(32);
quantize_program.SetWorkgroupSize(1);
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quantize_program.SetDispatchGroupSize(M * K / kBlockSizeA, 1, 1);
TensorShape a_quant_shape{1, M, K / kU32Components};
Tensor a_quant = context.CreateGPUTensor(DataTypeImpl::GetType<uint32_t>(), a_quant_shape);
Expand Down
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