diff --git a/CMakeLists.txt b/CMakeLists.txt
index fa5b445..93cdf13 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -49,6 +49,8 @@ target_compile_options(Aurora PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:
     -arch=sm_75 --expt-extended-lambda
 >)
 target_link_libraries(Aurora PRIVATE ${CUDA_RUNTIME_LIBRARY} CUDA::cufft CUDA::cudart)
+target_link_libraries(Aurora PRIVATE ${CUDA_cublas_LIBRARY})
+target_link_libraries(Aurora PRIVATE ${CUDA_cusolver_LIBRARY})
 endif(Aurora_USE_CUDA)
 
 find_package(GTest  REQUIRED)
@@ -75,6 +77,8 @@ target_compile_options(Aurora_Test PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:
     -arch=sm_75 --expt-extended-lambda
 >)
 target_link_libraries(Aurora_Test PRIVATE ${CUDA_RUNTIME_LIBRARY} CUDA::cufft CUDA::cudart)
+target_link_libraries(Aurora_Test PRIVATE ${CUDA_cublas_LIBRARY})
+target_link_libraries(Aurora_Test PRIVATE ${CUDA_cusolver_LIBRARY})
 endif(Aurora_USE_CUDA)
 gtest_discover_tests(Aurora_Test )
 #target_link_libraries(CreateMatchedFilter PRIVATE TBB::tbb)
\ No newline at end of file
diff --git a/src/Function1D.cu b/src/Function1D.cu
index fbfd7e0..d95d289 100644
--- a/src/Function1D.cu
+++ b/src/Function1D.cu
@@ -1,14 +1,18 @@
 #include "CudaMatrix.h"
+#include "AuroraDefs.h"
 #include "Function1D.cuh"
+#include "Function1D.h"
 #include "Matrix.h"
 
 #include <cmath>
+#include <cstdlib>
 #include <thrust/device_vector.h>
 #include <thrust/transform.h>
 #include <thrust/iterator/constant_iterator.h>
 #include <thrust/iterator/counting_iterator.h>
 #include <thrust/complex.h>
 #include <cuda_runtime.h>
+#include <cusolverDn.h>
 
 using namespace Aurora;
 using namespace thrust::placeholders;
@@ -701,3 +705,251 @@ CudaMatrix Aurora::log(const CudaMatrix& aMatrix, int aBaseNum)
     cudaDeviceSynchronize();
     return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
 }
+
+__global__ void expKernel(float* aInputData, float* aOutput, unsigned int aInputSize, bool aIsComplex)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aInputSize)
+    {
+        if(aIsComplex)
+        {
+            unsigned int index = 2 * idx;
+            float expReal = expf(aInputData[index]);
+            aOutput[index] = expReal * cosf(aInputData[index + 1]);
+            aOutput[index + 1] = expReal * sinf(aInputData[index + 1]);
+        }
+        else
+        {
+            aOutput[idx] =  expf(aInputData[idx]); 
+        }
+    }
+}
+
+CudaMatrix Aurora::exp(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size * aMatrix.getValueType());
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    expKernel<<<blocksPerGrid, THREADS_PER_BLOCK>>>(aMatrix.getData(), data, size, aMatrix.isComplex());
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+__global__ void modKernel(float* aInputData, float* aOutput, unsigned int aInputSize, float aModValue)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aInputSize)
+    {
+        aOutput[idx] =  fmodf(aInputData[idx], aModValue); 
+    }
+}
+
+CudaMatrix Aurora::mod(const CudaMatrix& aMatrix, float aValue)
+{
+    if(aMatrix.isComplex())
+    {
+        std::cerr<<"mod not support complex"<<std::endl;
+        return CudaMatrix();
+    }
+
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    modKernel<<<blocksPerGrid, THREADS_PER_BLOCK>>>(aMatrix.getData(), data, size, aValue);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2));
+}
+
+__global__ void acosKernel(float* aInputData, float* aOutput, unsigned int aInputSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aInputSize)
+    {
+        aOutput[idx] =  acosf(aInputData[idx]); 
+    }
+}
+
+CudaMatrix Aurora::acos(const CudaMatrix& aMatrix)
+{
+    if(aMatrix.isComplex())
+    {
+        std::cerr<<"acos not support complex"<<std::endl;
+        return CudaMatrix();
+    }
+
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    acosKernel<<<blocksPerGrid, THREADS_PER_BLOCK>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2));
+}
+
+__global__ void acosdKernel(float* aInputData, float* aOutput, unsigned int aInputSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aInputSize)
+    {
+        aOutput[idx] =  acosf(aInputData[idx]) * 180 / PI; 
+    }
+}
+
+CudaMatrix Aurora::acosd(const CudaMatrix& aMatrix)
+{
+    if(aMatrix.isComplex())
+    {
+        std::cerr<<"acos not support complex"<<std::endl;
+        return CudaMatrix();
+    }
+
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    acosdKernel<<<blocksPerGrid, THREADS_PER_BLOCK>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2));
+}
+
+__global__ void conjKernel(float* aInputData, float* aOutput, unsigned int aInputSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aInputSize)
+    {
+        unsigned int index = idx * 2;
+        aOutput[index] =  aInputData[index]; 
+        aOutput[index + 1] = -aInputData[index + 1];
+    }
+}
+
+CudaMatrix Aurora::conj(const CudaMatrix& aMatrix)
+{
+    if(!aMatrix.isComplex())
+    {
+        return CudaMatrix::copyFromRawData(aMatrix.getData(),aMatrix.getDimSize(0),aMatrix.getDimSize(1),aMatrix.getDimSize(2));
+    }
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size * aMatrix.getValueType());
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    conjKernel<<<blocksPerGrid, THREADS_PER_BLOCK>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+
+float Aurora::norm(const CudaMatrix& aMatrix, NormMethod aNormMethod)
+{
+    float resultValue = 0;
+    if(aMatrix.getDims() > 2)
+    {
+        std::cerr<<"norm not support 3d matrix"<<std::endl;
+        return 0;
+    }
+    //for 1 dims
+    if(aMatrix.getDimSize(0) == 1 || aMatrix.getDimSize(1) == 1 )
+    {
+        if(aNormMethod == Aurora::Norm1)
+        {
+            CudaMatrix result = abs(aMatrix);
+            resultValue = thrust::reduce(thrust::device, result.getData(), result.getData() + result.getDataSize(),  0.0, thrust::plus<float>());
+            return resultValue;
+        }
+        else
+        {
+            CudaMatrix result = aMatrix.deepCopy();
+            thrust::transform(thrust::device, result.getData(), result.getData() + result.getDataSize() * result.getValueType(),  result.getData(), thrust::square<float>());
+            resultValue = thrust::reduce(thrust::device, result.getData(), result.getData() + result.getDataSize() * result.getValueType(),  0.0, thrust::plus<float>());
+            return std::sqrt(resultValue);
+        }
+    }
+    //for 2 dims
+    if(aNormMethod == Aurora::NormF)
+    {
+        CudaMatrix result = aMatrix.deepCopy();
+        thrust::transform(thrust::device, result.getData(), result.getData() + result.getDataSize() * result.getValueType(),  result.getData(), thrust::square<float>());
+        resultValue = thrust::reduce(thrust::device, result.getData(), result.getData() + result.getDataSize() * result.getValueType(),  0.0, thrust::plus<float>());
+        return std::sqrt(resultValue);
+    }
+    else if(aNormMethod == Aurora::Norm1)
+    {
+        for(int i=0; i<aMatrix.getDimSize(1); ++i)
+        {
+            CudaMatrix result = abs(aMatrix.block(1, i, i));
+            float tempValue = thrust::reduce(thrust::device, result.getData(), result.getData() + result.getDataSize(),  0.0, thrust::plus<float>());
+            if(resultValue < tempValue)
+            {
+                resultValue = tempValue;
+            }
+        }
+        return resultValue;
+    }
+    else
+    {
+        if(aMatrix.isComplex())
+        {
+            std::cerr<<"norm2 not support 2d complex matrix"<<std::endl;
+            return 0;
+        }
+        cusolverDnHandle_t cusolverH = NULL;
+        cudaStream_t stream = NULL;
+        float* d_S = NULL;
+        float* d_U = NULL;
+        float* d_VT = NULL;
+        int* devInfo = NULL;
+        float* d_work = NULL;
+        int lwork = 0;
+        const int m = aMatrix.getDimSize(0);
+        const int n = aMatrix.getDimSize(1);
+        const int lda = m;
+        const int ldu = m;
+        const int ldvt = n;
+
+        cusolverDnCreate(&cusolverH);
+        cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking);
+        cusolverDnSetStream(cusolverH, stream);
+        cudaMalloc((void**)&d_S, sizeof(float)*n);
+        cudaMalloc((void**)&d_U, sizeof(float)*ldu*m);
+        cudaMalloc((void**)&d_VT, sizeof(float)*ldvt*n);
+        cudaMalloc((void**)&devInfo, sizeof(int));
+
+        cusolverDnSgesvd_bufferSize(cusolverH, m, n, &lwork);
+
+        cudaMalloc((void**)&d_work, sizeof(float)*lwork);
+        auto matrix = aMatrix.deepCopy();
+        cusolverDnSgesvd(cusolverH, 'A', 'A', m, n, matrix.getData(), lda, d_S,d_U, ldu, d_VT, ldvt, d_work, lwork, NULL, devInfo);
+
+        int devInfo_h = 0;
+        cudaMemcpy(&devInfo_h, devInfo, sizeof(int), cudaMemcpyDeviceToHost);
+
+        if (devInfo_h != 0) 
+        {
+            printf("Unsuccessful SVD execution\n");
+            printf("Error code: %d\n", devInfo_h);
+        }
+
+        float S[n] = {0};  
+        cudaMemcpy(S, d_S, sizeof(float)*n, cudaMemcpyDeviceToHost);
+
+        float resultValue = S[0];
+        for (int i = 1; i < n; i++)
+        { 
+            if (S[i] > resultValue)
+            {
+                resultValue = S[i];
+            }
+        }
+
+        if (d_S ) cudaFree(d_S);
+        if (d_U ) cudaFree(d_U);
+        if (d_VT) cudaFree(d_VT);
+        if (devInfo) cudaFree(devInfo);
+        if (d_work) cudaFree(d_work);
+        if (cusolverH) cusolverDnDestroy(cusolverH);
+        if (stream) cudaStreamDestroy(stream);
+        return resultValue;
+    }
+}
diff --git a/src/Function1D.cuh b/src/Function1D.cuh
index fbe6387..8d5c8f4 100644
--- a/src/Function1D.cuh
+++ b/src/Function1D.cuh
@@ -51,7 +51,17 @@ namespace Aurora
 
     CudaMatrix log(const CudaMatrix& aMatrix, int aBaseNum = -1);
 
+    CudaMatrix exp(const CudaMatrix& aMatrix);
 
+    CudaMatrix mod(const CudaMatrix& aMatrix, float aValue);
+
+    CudaMatrix acos(const CudaMatrix& aMatrix);
+
+    CudaMatrix acosd(const CudaMatrix& aMatrix);
+
+    CudaMatrix conj(const CudaMatrix& aMatrix);
+
+    float norm(const CudaMatrix& aMatrix, NormMethod aNormMethod);
 
     // ------compareSet----------------------------------------------------
 
diff --git a/test/Function1D_Cuda_Test.cpp b/test/Function1D_Cuda_Test.cpp
index c1784e8..03c8c90 100644
--- a/test/Function1D_Cuda_Test.cpp
+++ b/test/Function1D_Cuda_Test.cpp
@@ -647,3 +647,156 @@ TEST_F(Function1D_Cuda_Test, compareSet)
         }
     }
 }
+
+TEST_F(Function1D_Cuda_Test, exp)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::exp(hostMatrix);
+    auto result2 = Aurora::exp(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9.9,10,11,12}, 3, 2, 1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::exp(hostMatrix);
+    result2 = Aurora::exp(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, mod)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::mod(hostMatrix, 2);
+    auto result2 = Aurora::mod(deviceMatrix, 2).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+
+    result1 = Aurora::mod(hostMatrix, 3);
+    result2 = Aurora::mod(deviceMatrix, 3).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, acos)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8}, 2,4);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::acos(hostMatrix);
+    auto result2 = Aurora::acos(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, acosd)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8}, 2,4);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::acosd(hostMatrix);
+    auto result2 = Aurora::acosd(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, conj)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8}, 2,4);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::conj(hostMatrix);
+    auto result2 = Aurora::conj(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9.9,10,11,12}, 3, 2, 1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::conj(hostMatrix);
+    result2 = Aurora::conj(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
+    EXPECT_EQ(result2.getValueType(), result1.getValueType());
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_FLOAT_AE(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, norm) {
+    //1Dim
+    float *data = new float[3]{1,2,-3};
+    auto matrix = Aurora::Matrix::fromRawData(data, 3);
+    auto deviceMatrix = matrix.toDeviceMatrix();
+    auto result = Aurora::norm(matrix.toDeviceMatrix(), Aurora::NormMethod::Norm1);
+    EXPECT_FLOAT_AE(result,6);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm2);
+    EXPECT_FLOAT_AE(result,3.74166);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
+    EXPECT_FLOAT_AE(result,3.74166);
+
+    //2Dims
+    data = new float[8]{1,2,-3,6,7,9,22.3,-8.6};
+    matrix = Aurora::Matrix::fromRawData(data, 4,2);
+    deviceMatrix = matrix.toDeviceMatrix();
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm1);
+    EXPECT_FLOAT_AE(result,46.9);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm2);
+    EXPECT_FLOAT_AE(result,26.7284);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
+    EXPECT_FLOAT_AE(result,27.4089);
+
+    //1Dim Complex
+    data = new float[6]{1,2,-3,4,5,-6};
+    matrix = Aurora::Matrix::fromRawData(data, 3,1,1,Aurora::Complex);
+    deviceMatrix = matrix.toDeviceMatrix();
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm1);
+    EXPECT_FLOAT_AE(result,15.0463);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm2);
+    EXPECT_FLOAT_AE(result,9.5394);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
+    EXPECT_FLOAT_AE(result,9.5394);
+
+    //2Dims Complex
+    data = new float[12]{1,2,-3,4,5,-6,7,8,9,22,24,25};
+    matrix = Aurora::Matrix::fromRawData(data, 3,2,1,Aurora::Complex);
+    deviceMatrix = matrix.toDeviceMatrix();
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm1);
+    EXPECT_FLOAT_AE(result,69.0553);
+    //not support
+    //result = Aurora::norm(matrix,Aurora::NormMethod::Norm2);
+    //EXPECT_FLOAT_AE(result,43.5314);
+    result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
+    EXPECT_FLOAT_AE(result,44.3847);
+}