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miaobyte merged 7 commits into from
Apr 2, 2025
Merged

excuter(cpu/cuda):comparescalar,max,min,compare; sin,cos,tan; #14

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excuter(cpu/cuda):max,min,compare; sin,cos,tan;
miaobyte Apr 1, 2025
701ee0f
excuter(cpu/cuda):comparescalar
miaobyte Apr 2, 2025
489c164
half,bfloat16
miaobyte Apr 2, 2025
5d07d3b
half,bfloat16
miaobyte Apr 2, 2025
60b61a8
half,bfloat16:fix
miaobyte Apr 2, 2025
e3993e6
half,bfloat16:fix
miaobyte Apr 2, 2025
fbd68e0
half,bfloat16:fix
miaobyte Apr 2, 2025
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4 changes: 2 additions & 2 deletions .github/workflows/excuter-cuda-linux.yml
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Expand Up @@ -2,7 +2,7 @@ name: Excuter/cuda-linux Build
on: [push, pull_request]

env:
CUDA_VERSION: "12.1.0"
CUDA_VERSION: "12.6.0"
CUDA_MAJOR_VERSION: "12"
CUDNN_VERSION: "8.9.7.29"
CUTLASS_VERSION: "3.4.1"
Expand All @@ -29,7 +29,7 @@ jobs:
run: |
docker run --rm -v ${{ github.workspace }}:/workspace \
-w /workspace \
nvidia/cuda:12.1.0-devel-ubuntu22.04 \
nvidia/cuda:12.6.0-devel-ubuntu22.04 \
/bin/bash -c "
# 安装系统依赖
apt-get update && \
Expand Down
48 changes: 28 additions & 20 deletions doc/excuter/op-mem-cuda/list.md
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Expand Up @@ -5,27 +5,35 @@
| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| matmul | cublas | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1 @ T2 | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| exp | miaobyte | exp(tensor<any> A)->(tensor<any> C) | T3=exp(T1) | exp(tensor<any> A)->(tensor<any> C) |
| pow | miaobyte | pow(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=pow(T1, T2) | pow(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| powscalar | miaobyte | powscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=pow(T1, scalar) | powscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| rdivscalar | miaobyte | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) | T3=scalar/T1 | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) |
| div | miaobyte | div(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1/T2 | div(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| sub | miaobyte | sub(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1-T2 | sub(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| argset | none | argset(var<any> value)->(var<any> name) | var argname = argvalue | argset(var<any> value)->(var<any> name) |
| mulscalar | miaobyte | mulscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1*scalar | mulscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| sqrt | miaobyte | sqrt(tensor<any> A)->(tensor<any> C) | T3=sqrt(T1) | sqrt(tensor<any> A)->(tensor<any> C) |
| vecset | none | vecset(vector<any> value)->(vector<any> name) | shape = [3 4 5] | vecset(vector<any> value)->(vector<any> name) |
| newtensor | none | newtensor(vector<int32> shape)->(tensor<any> tensor1) | T1 = zeros(shape) | newtensor(vector<int32> shape)->(tensor<any> tensor1) |
| newtensor | none | newtensor(var<string> shape)->(tensor<any> tensor1) | T1 = zeros(shape) | newtensor(var<string> shape)->(tensor<any> tensor1) |
| print | miaobyte | print(tensor<any> )->() | print(T1) | print(tensor<any> )->() |
| print | miaobyte | print(tensor<any> , var<string> )->() | print(T1) | print(tensor<any> , var<string> )->() |
| divscalar | miaobyte | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=scalar/T1 | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| constant | miaobyte | constant(tensor<any> t, var<any> value)->() | constant(T1) | constant(tensor<any> t, var<any> value)->() |
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
| subscalar | miaobyte | subscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1-scalar | subscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| log | miaobyte | log(tensor<any> A)->(tensor<any> C) | T3=log(T1) | log(tensor<any> A)->(tensor<any> C) |
| uniform | miaobyte | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() | uniform(T1,low,high,seed) | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() |
| add | cublas | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| add | miaobyte | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| uniform | miaobyte | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() | uniform(T1,low,high,seed) | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() |
| addscalar | miaobyte | addscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1+scalar | addscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| log | miaobyte | log(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=log(T1) | log(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
| divscalar | miaobyte | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=scalar/T1 | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| sin | miaobyte | sin(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=sin(T1) | sin(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| tan | miaobyte | tan(tensor<float64|float32> A)->(tensor<float64|float32> C) | T3=tan(T1) | tan(tensor<float64|float32> A)->(tensor<float64|float32> C) |
| print | miaobyte | print(tensor<any> )->() | print(T1) | print(tensor<any> )->() |
| print | miaobyte | print(tensor<any> , var<string> )->() | print(T1) | print(tensor<any> , var<string> )->() |
| newtensor | none | newtensor(vector<int32> shape)->(tensor<any> tensor1) | T1 = zeros(shape) | newtensor(vector<int32> shape)->(tensor<any> tensor1) |
| newtensor | none | newtensor(var<string> shape)->(tensor<any> tensor1) | T1 = zeros(shape) | newtensor(var<string> shape)->(tensor<any> tensor1) |
| vecset | none | vecset(vector<any> value)->(vector<any> name) | shape = [3 4 5] | vecset(vector<any> value)->(vector<any> name) |
| subscalar | miaobyte | subscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1-scalar | subscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| sqrt | miaobyte | sqrt(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=sqrt(T1) | sqrt(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| argset | none | argset(var<any> value)->(var<any> name) | var argname = argvalue | argset(var<any> value)->(var<any> name) |
| sub | miaobyte | sub(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1-T2 | sub(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| mulscalar | miaobyte | mulscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1*scalar | mulscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| div | miaobyte | div(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1/T2 | div(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| constant | miaobyte | constant(tensor<any> t, var<any> value)->() | constant(T1) | constant(tensor<any> t, var<any> value)->() |
| powscalar | miaobyte | powscalar(tensor<float64|float32> A, var<float64|float32> scalar)->(tensor<float64|float32> C) | T3=pow(T1, scalar) | powscalar(tensor<float64|float32> A, var<float64|float32> scalar)->(tensor<float64|float32> C) |
| max | miaobyte | max(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=max(T1, T2) | max(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| pow | miaobyte | pow(tensor<float64|float32> A, tensor<float64|float32> B)->(tensor<float64|float32> C) | T3=pow(T1, T2) | pow(tensor<float64|float32> A, tensor<float64|float32> B)->(tensor<float64|float32> C) |
| maxscalar | miaobyte | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=max(T1, scalar) | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| mul | miaobyte | mul(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1*T2 | mul(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| exp | miaobyte | exp(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=exp(T1) | exp(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| rdivscalar | miaobyte | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) | T3=scalar/T1 | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) |
| minscalar | miaobyte | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=min(T1, scalar) | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| cos | miaobyte | cos(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=cos(T1) | cos(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| min | miaobyte | min(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=min(T1, T2) | min(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| compare | miaobyte | compare(tensor<any> A, tensor<any> B)->(tensor<int8> mask) | mask=compare(T1, T2) | compare(tensor<any> A, tensor<any> B)->(tensor<int8> mask) |
5 changes: 5 additions & 0 deletions doc/excuter/op-mem-ompsimd/list.md
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Expand Up @@ -7,7 +7,11 @@
| concat | none | concat()->() | Tresult = concat([T1, T2...], axis=3) | concat()->() |
| matmul | cblas | matmul(tensor<float64|float32> A, tensor<float64|float32> B)->(tensor<float64|float32> C) | T3=T1 @ T2 | matmul(tensor<float64|float32> A, tensor<float64|float32> B)->(tensor<float64|float32> C) |
| matmul | miaobyte | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1 @ T2 | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| compare | miaobyte | compare(tensor<any> A, tensor<any> B)->(tensor<int8> mask) | mask=compare(T1,T2) | compare(tensor<any> A, tensor<any> B)->(tensor<int8> mask) |
| min | miaobyte | min(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=min(T1,T2) | min(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| minscalar | miaobyte | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=min(T1,scalar) | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| exp | miaobyte | exp(tensor<any> A)->(tensor<any> C) | T3=exp(T1) | exp(tensor<any> A)->(tensor<any> C) |
| maxscalar | miaobyte | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=max(T1,scalar) | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| pow | miaobyte | pow(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1^T2 | pow(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| powscalar | miaobyte | powscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=T1^scalar | powscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| rdivscalar | miaobyte | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) | T3=scalar/T1 | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) |
Expand All @@ -21,6 +25,7 @@
| newtensor | none | newtensor(var<string> shape)->(tensor<any> tensor1) | T1 =Tensor(shape=[...]) | newtensor(var<string> shape)->(tensor<any> tensor1) |
| print | miaobyte | print(tensor<any> )->() | print(T1) | print(tensor<any> )->() |
| print | miaobyte | print(tensor<any> , var<string> )->() | print(T1) | print(tensor<any> , var<string> )->() |
| max | miaobyte | max(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=max(T1,T2) | max(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| divscalar | miaobyte | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=T1/scalar | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| constant | miaobyte | constant(tensor<any> t, var<any> value)->() | constant(T1,value) | constant(tensor<any> t, var<any> value)->() |
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
Expand Down
125 changes: 18 additions & 107 deletions excuter/cpp-common/src/deepx/tensorfunc/elementwise.hpp
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Expand Up @@ -87,42 +87,8 @@ namespace deepx::tensorfunc
mulscalarDispatcher<Author, T>::mulscalar(input, value, output);
}

template <typename Author, typename T>
struct muladdDispatcher
{
static void muladd(const Tensor<T> &A, const Tensor<T> &B, const Tensor<T> &C, Tensor<T> &D) = delete;
};

template <typename Author, typename T>
void muladd(const Tensor<T> &A, const Tensor<T> &B, const Tensor<T> &C, Tensor<T> &D)
{
muladdDispatcher<Author, T>::muladd(A, B, C, D);
}

template <typename Author, typename T>
struct muladdscalarDispatcher
{
static void muladdscalar(const Tensor<T> &A, const Tensor<T> &B, const T alpha, const Tensor<T> &C, const T beta, Tensor<T> &D) = delete;
};

template <typename Author, typename T>
void muladdscalar(const Tensor<T> &A, const Tensor<T> &B, const T alpha, const Tensor<T> &C, const T beta, Tensor<T> &D)
{
muladdscalarDispatcher<Author, T>::muladdscalar(A, B, alpha, C, beta, D);
}

template <typename Author, typename T>
struct mulscalaraddDispatcher
{
static void mulscalaradd(const Tensor<T> &A, const T alpha, const Tensor<T> &B, const T beta, Tensor<T> &C) = delete;
};

template <typename Author, typename T>
void mulscalaradd(const Tensor<T> &A, const T alpha, const Tensor<T> &B, const T beta, Tensor<T> &C)
{
mulscalaraddDispatcher<Author, T>::mulscalaradd(A, alpha, B, beta, C);
}



template <typename Author, typename T>
struct divDispatcher
{
Expand Down Expand Up @@ -159,42 +125,7 @@ namespace deepx::tensorfunc
rdivscalarDispatcher<Author, T>::rdivscalar(value, input, output);
}

template <typename Author, typename T>
struct divaddDispatcher
{
static void divadd(const Tensor<T> &A, const Tensor<T> &B, const Tensor<T> &C, Tensor<T> &D) = delete;
};

template <typename Author, typename T>
void divadd(const Tensor<T> &A, const Tensor<T> &B, const Tensor<T> &C, Tensor<T> &D)
{
divaddDispatcher<Author, T>::divadd(A, B, C, D);
}

template <typename Author, typename T>
struct divscalaraddDispatcher
{
static void divscalaradd(const Tensor<T> &A, const T alpha, const Tensor<T> &B, const T beta, Tensor<T> &C) = delete;
};

template <typename Author, typename T>
void divscalaradd(const Tensor<T> &A, const T alpha, const Tensor<T> &B, const T beta, Tensor<T> &C)
{
divscalaraddDispatcher<Author, T>::divscalaradd(A, alpha, B, beta, C);
}

template <typename Author, typename T>
struct divaddbetaDispatcher
{
static void divaddbeta(const Tensor<T> &A, const Tensor<T> &B, const T alpha, const Tensor<T> &C, const T beta, Tensor<T> &D) = delete;
};

template <typename Author, typename T>
void divaddbeta(const Tensor<T> &A, const Tensor<T> &B, const T alpha, const Tensor<T> &C, const T beta, Tensor<T> &D)
{
divaddbetaDispatcher<Author, T>::divaddbeta(A, B, alpha, C, beta, D);
}


template <typename Author, typename T,typename = void>
struct sqrtDispatcher
{
Expand Down Expand Up @@ -303,17 +234,7 @@ namespace deepx::tensorfunc
maxDispatcher<Author, T>::max(A, B, C);
}

template <typename Author, typename T>
struct maxgradDispatcher
{
static void maxgrad(const Tensor<T> &A, const Tensor<T> &B, Tensor<T> &A_grad, Tensor<T> &B_grad, const Tensor<T> &output_grad) = delete;
};

template <typename Author, typename T>
void maxgrad(const Tensor<T> &A, const Tensor<T> &B, Tensor<T> &A_grad, Tensor<T> &B_grad, const Tensor<T> &output_grad)
{
maxgradDispatcher<Author, T>::maxgrad(A, B, A_grad, B_grad, output_grad);
}


template <typename Author, typename T>
struct maxscalarDispatcher
Expand All @@ -327,17 +248,7 @@ namespace deepx::tensorfunc
maxscalarDispatcher<Author, T>::maxscalar(A, b, C);
}

template <typename Author, typename T>
struct maxscalargradDispatcher
{
static void maxscalargrad(const Tensor<T> &A, const T b, Tensor<T> &A_grad, const Tensor<T> &output_grad) = delete;
};

template <typename Author, typename T>
void maxscalargrad(const Tensor<T> &A, const T b, Tensor<T> &A_grad, const Tensor<T> &output_grad)
{
maxscalargradDispatcher<Author, T>::maxscalargrad(A, b, A_grad, output_grad);
}


template <typename Author, typename T>
struct minDispatcher
Expand All @@ -352,39 +263,39 @@ namespace deepx::tensorfunc
}

template <typename Author, typename T>
struct mingradDispatcher
struct minscalarDispatcher
{
static void mingrad(const Tensor<T> &A, const Tensor<T> &B, Tensor<T> &A_grad, Tensor<T> &B_grad, const Tensor<T> &output_grad) = delete;
static void minscalar(const Tensor<T> &A, T b, Tensor<T> &C) = delete;
};

template <typename Author, typename T>
void mingrad(const Tensor<T> &A, const Tensor<T> &B, Tensor<T> &A_grad, Tensor<T> &B_grad, const Tensor<T> &output_grad)
void minscalar(const Tensor<T> &A, T b, Tensor<T> &C)
{
mingradDispatcher<Author, T>::mingrad(A, B, A_grad, B_grad, output_grad);
minscalarDispatcher<Author, T>::minscalar(A, b, C);
}

template <typename Author, typename T>
struct minscalarDispatcher
struct compareDispatcher
{
static void minscalar(const Tensor<T> &A, T b, Tensor<T> &C) = delete;
static void compare(const Tensor<T> &A, const Tensor<T> &B, Tensor<float> &mask) = delete;
};

template <typename Author, typename T>
void minscalar(const Tensor<T> &A, T b, Tensor<T> &C)
void compare(const Tensor<T> &A, const Tensor<T> &B,Tensor<float> &mask)
{
minscalarDispatcher<Author, T>::minscalar(A, b, C);
compareDispatcher<Author, T>::compare(A, B, mask);
}

template <typename Author, typename T>
struct minscalargradDispatcher
struct comparescalarDispatcher
{
static void minscalargrad(const Tensor<T> &A, const T b, Tensor<T> &A_grad, const Tensor<T> &output_grad) = delete;
static void comparescalar(const Tensor<T> &A, const T scalar, Tensor<float> &mask) = delete;
};

template <typename Author, typename T>
void minscalargrad(const Tensor<T> &A, const T b, Tensor<T> &A_grad, const Tensor<T> &output_grad)
void comparescalar(const Tensor<T> &A, const T scalar, Tensor<float> &mask)
{
minscalargradDispatcher<Author, T>::minscalargrad(A, b, A_grad, output_grad);
comparescalarDispatcher<Author, T>::comparescalar(A, scalar, mask);
}
} // namespace deepx::tensorfunc

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