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https://github.com/ggerganov/llama.cpp.git
synced 2024-12-29 04:44:34 +00:00
vulkan : optimize workgroup sizes
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84f7fc4553
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@ -847,9 +847,9 @@ void ggml_vk_norm_(const std::vector<uint32_t>& spirv, kp::Sequence& seq,
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};
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std::shared_ptr<kp::Algorithm> s_algo = nullptr;
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if (!komputeManager()->hasAlgorithm(__func__))
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if (!komputeManager()->hasAlgorithm(__func__)) {
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s_algo = komputeManager()->algorithm<float, PushConstants>(__func__, s_kompute_context->pool.get(), {in, out}, spirv, {(uint32_t)nrows}, {}, {pushConsts});
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else {
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} else {
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s_algo = komputeManager()->getAlgorithm(__func__);
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s_algo->setTensors({in, out});
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s_algo->setWorkgroup({(uint32_t)nrows});
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@ -10,13 +10,12 @@
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#include "common.comp"
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#define nth 32
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#define IN_TYPE float16_t
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#define IN_TYPE_SIZE 2
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#define OUT_TYPE float16_t
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#define OUT_TYPE_SIZE 2
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layout(local_size_x = nth) in;
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layout(local_size_x = 1024) in;
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layout (binding = 0) readonly buffer tensorIn { IN_TYPE in_[]; };
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layout (binding = 1) writeonly buffer tensorOut { OUT_TYPE out_[]; };
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@ -54,7 +53,7 @@ void main() {
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const uint dst_data = (i3*pcs.nb3 + i2*pcs.nb2 + i1*pcs.nb1 + i0*pcs.nb0) / OUT_TYPE_SIZE + pcs.outOff; // Based from out_
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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const uint src = uint((i03*pcs.nb03 + i02*pcs.nb02 + i01*pcs.nb01 + i00*pcs.nb00) / IN_TYPE_SIZE) + pcs.inOff; // Based from in_
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out_[dst_data+i00] = OUT_TYPE(in_[src]);
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}
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@ -10,13 +10,12 @@
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#include "common.comp"
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#define nth 32
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#define IN_TYPE float16_t
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#define IN_TYPE_SIZE 2
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#define OUT_TYPE float
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#define OUT_TYPE_SIZE 4
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layout(local_size_x = nth) in;
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layout(local_size_x = 1024) in;
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layout (binding = 0) readonly buffer tensorIn { IN_TYPE in_[]; };
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layout (binding = 1) writeonly buffer tensorOut { OUT_TYPE out_[]; };
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@ -54,7 +53,7 @@ void main() {
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const uint dst_data = (i3*pcs.nb3 + i2*pcs.nb2 + i1*pcs.nb1 + i0*pcs.nb0) / OUT_TYPE_SIZE + pcs.outOff; // Based from out_
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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const uint src = uint((i03*pcs.nb03 + i02*pcs.nb02 + i01*pcs.nb01 + i00*pcs.nb00) / IN_TYPE_SIZE) + pcs.inOff; // Based from in_
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out_[dst_data+i00] = OUT_TYPE(in_[src]);
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}
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@ -10,13 +10,12 @@
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#include "common.comp"
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#define nth 32
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#define IN_TYPE float
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#define IN_TYPE_SIZE 4
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#define OUT_TYPE float16_t
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#define OUT_TYPE_SIZE 2
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layout(local_size_x = nth) in;
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layout(local_size_x = 1024) in;
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layout (binding = 0) readonly buffer tensorIn { IN_TYPE in_[]; };
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layout (binding = 1) writeonly buffer tensorOut { OUT_TYPE out_[]; };
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@ -54,7 +53,7 @@ void main() {
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const uint dst_data = (i3*pcs.nb3 + i2*pcs.nb2 + i1*pcs.nb1 + i0*pcs.nb0) / OUT_TYPE_SIZE + pcs.outOff; // Based from out_
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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const uint src = uint((i03*pcs.nb03 + i02*pcs.nb02 + i01*pcs.nb01 + i00*pcs.nb00) / IN_TYPE_SIZE) + pcs.inOff; // Based from in_
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out_[dst_data+i00] = OUT_TYPE(in_[src]);
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}
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@ -2,13 +2,12 @@
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#include "common.comp"
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#define nth 32
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#define IN_TYPE float
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#define IN_TYPE_SIZE 4
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#define OUT_TYPE float
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#define OUT_TYPE_SIZE 4
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layout(local_size_x = nth) in;
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layout(local_size_x = 1024) in;
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layout (binding = 0) readonly buffer tensorIn { IN_TYPE in_[]; };
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layout (binding = 1) writeonly buffer tensorOut { OUT_TYPE out_[]; };
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@ -46,7 +45,7 @@ void main() {
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const uint dst_data = (i3*pcs.nb3 + i2*pcs.nb2 + i1*pcs.nb1 + i0*pcs.nb0) / OUT_TYPE_SIZE + pcs.outOff; // Based from out_
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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const uint src = uint((i03*pcs.nb03 + i02*pcs.nb02 + i01*pcs.nb01 + i00*pcs.nb00) / IN_TYPE_SIZE) + pcs.inOff; // Based from in_
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out_[dst_data+i00] = OUT_TYPE(in_[src]);
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}
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@ -10,9 +10,7 @@
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#include "common.comp"
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#define nth 256
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layout(local_size_x = nth) in;
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layout(local_size_x = 256) in;
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layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
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layout(binding = 1) buffer restrict tensorOut { float out_[]; };
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@ -25,21 +23,21 @@ layout(push_constant) uniform PushConstants {
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float eps;
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} pcs;
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shared float sum[nth];
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shared float sum[gl_WorkGroupSize.x];
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void main() {
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const uint x = (gl_WorkGroupID.x*pcs.nb01/4) + pcs.inOff; // Based from in_
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// MEAN
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// parallel sum
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sum[gl_LocalInvocationID.x] = 0.0;
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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sum[gl_LocalInvocationID.x] += in_[x+i00];
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}
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// reduce
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barrier();
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memoryBarrierShared();
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[[unroll]] for (uint i = nth/2; i > 0; i /= 2) {
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[[unroll]] for (uint i = gl_WorkGroupSize.x/2; i > 0; i /= 2) {
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if (gl_LocalInvocationID.x < i) {
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sum[gl_LocalInvocationID.x] += sum[gl_LocalInvocationID.x + i];
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}
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@ -57,21 +55,21 @@ void main() {
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// recenter
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const uint y = (gl_WorkGroupID.x*pcs.ne00) + pcs.outOff; // Based from out_
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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out_[y+i00] = in_[x+i00] - mean;
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}
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// VARIANCE
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// parallel sum
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sum[gl_LocalInvocationID.x] = 0.0;
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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sum[gl_LocalInvocationID.x] += out_[y+i00] * out_[y+i00];
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}
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// reduce
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barrier();
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memoryBarrierShared();
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[[unroll]] for (uint i = nth/2; i > 0; i /= 2) {
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[[unroll]] for (uint i = gl_WorkGroupSize.x/2; i > 0; i /= 2) {
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if (gl_LocalInvocationID.x < i) {
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sum[gl_LocalInvocationID.x] += sum[gl_LocalInvocationID.x + i];
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}
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@ -88,7 +86,7 @@ void main() {
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const float variance = sum[0];
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const float scale = 1.0f/sqrt(variance + pcs.eps);
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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out_[y+i00] *= scale;
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}
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}
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@ -10,9 +10,7 @@
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#include "common.comp"
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#define nth 512
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layout(local_size_x = nth) in;
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layout(local_size_x = 512) in;
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layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
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layout(binding = 1) buffer restrict tensorOut { float out_[]; };
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@ -25,21 +23,21 @@ layout(push_constant) uniform PushConstants {
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float eps;
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} pcs;
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shared float sum[nth];
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shared float sum[gl_WorkGroupSize.x];
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void main() {
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const uint x = (gl_WorkGroupID.x*pcs.nb01/4) + pcs.inOff; // Based from in_
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// parallel sum
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sum[gl_LocalInvocationID.x] = 0.0;
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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sum[gl_LocalInvocationID.x] += in_[x+i00] * in_[x+i00];
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}
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// reduce
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barrier();
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memoryBarrierShared();
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[[unroll]] for (uint i = nth/2; i > 0; i /= 2) {
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[[unroll]] for (uint i = gl_WorkGroupSize.x/2; i > 0; i /= 2) {
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if (gl_LocalInvocationID.x < i) {
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sum[gl_LocalInvocationID.x] += sum[gl_LocalInvocationID.x + i];
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}
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@ -57,7 +55,7 @@ void main() {
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const float scale = 1.0f/sqrt(sum[0] + pcs.eps);
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const uint y = (gl_WorkGroupID.x*pcs.ne00) + pcs.outOff; // Based from out_
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += nth) {
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for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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out_[y+i00] = in_[x+i00] * scale;
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}
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}
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@ -10,6 +10,7 @@
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#include "common.comp"
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// TODO: use a local size of 32 or more (Metal uses 1024)
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layout(local_size_x = 1) in;
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layout(binding = 0) buffer restrict readonly tensorInA { float inA[]; };
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