diff --git a/src/Function1D.cu b/src/Function1D.cu
new file mode 100644
index 0000000..776844a
--- /dev/null
+++ b/src/Function1D.cu
@@ -0,0 +1,304 @@
+#include "CudaMatrix.h"
+#include "Function1D.cuh"
+#include "Matrix.h"
+
+#include <cmath>
+#include <thrust/device_vector.h>
+#include <thrust/transform.h>
+#include <thrust/iterator/constant_iterator.h>
+#include <cuda_runtime.h>
+
+using namespace Aurora;
+
+namespace
+{
+    const int THREADS_PER_BLOCK = 256;
+}
+
+__global__ void complexKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[2*idx] = aInputData[idx];
+        aOutput[2*idx + 1] = 0;
+    }
+}
+
+CudaMatrix Aurora::complex(const CudaMatrix& aMatrix)
+{
+    if(aMatrix.isComplex())
+    {
+        return CudaMatrix();
+    }
+
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * aMatrix.getDataSize() * Aurora::Complex);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    complexKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), Aurora::Complex);
+}
+
+__global__ void realKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[idx] = aInputData[idx*2];
+    }
+}
+
+CudaMatrix Aurora::real(const CudaMatrix& aMatrix)
+{
+    if(!aMatrix.isComplex())
+    {
+        return CudaMatrix();
+    }
+
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * aMatrix.getDataSize());
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    realKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), Aurora::Normal);
+}
+
+__global__ void imageKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[idx] = aInputData[idx*2 + 1];
+    }
+}
+
+CudaMatrix Aurora::imag(const CudaMatrix& aMatrix)
+{
+    if(!aMatrix.isComplex())
+    {
+        return CudaMatrix();
+    }
+
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * aMatrix.getDataSize());
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    imageKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), Aurora::Normal);
+}
+
+__global__ void ceilKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[idx] = std::ceil(aInputData[idx]);
+    }
+}
+
+CudaMatrix Aurora::ceil(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    ceilKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+CudaMatrix Aurora::ceil(const CudaMatrix&& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    ceilKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+__global__ void roundKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[idx] = std::round(aInputData[idx]);
+    }
+}
+
+CudaMatrix Aurora::round(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    roundKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+CudaMatrix Aurora::round(const CudaMatrix&& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    roundKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+__global__ void floorKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[idx] = std::floor(aInputData[idx]);
+    }
+}
+
+CudaMatrix Aurora::floor(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    floorKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+CudaMatrix Aurora::floor(const CudaMatrix&& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    floorKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+__global__ void sqrtKernel(float* aInputData, float* aOutput, unsigned int aSize)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        aOutput[idx] = std::sqrt(aInputData[idx]);
+    }
+}
+
+CudaMatrix Aurora::sqrt(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    sqrtKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+CudaMatrix Aurora::sqrt(const CudaMatrix&& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    sqrtKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size);
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+__global__ void absKernel(float* aInputData, float* aOutput, unsigned int aSize, bool aIsComplex)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        if(aIsComplex)
+        {
+            aOutput[idx] = sqrt(aInputData[2*idx] * aInputData[2*idx] +  aInputData[2*idx+1] * aInputData[2*idx+1]);
+        }
+        else
+        {
+            aOutput[idx] = abs(aInputData[idx]);
+        }       
+    }
+}
+
+CudaMatrix Aurora::abs(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    absKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size, aMatrix.isComplex());
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2));
+}
+
+CudaMatrix Aurora::abs(const CudaMatrix&& aMatrix)
+{
+    size_t size = aMatrix.getDataSize();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    absKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, size, aMatrix.isComplex());
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2));
+}
+
+__global__ void signKernel(float* aInputData, float* aOutput, unsigned int aSize, bool aIsComplex)
+{
+    unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    if (idx < aSize)
+    {
+        if(aIsComplex)
+        {
+            float absValue = sqrt(aInputData[2*idx] * aInputData[2*idx] + aInputData[2*idx + 1] * aInputData[2*idx + 1]);
+            aOutput[2*idx] = aInputData[2*idx] / absValue;
+            aOutput[2*idx + 1] = aInputData[2*idx + 1] / absValue;
+            return;
+        }
+
+        if(aInputData[idx] < 0)
+        {
+            aOutput[idx] = -1;
+        }
+        else if(aInputData[idx] > 0)
+        {
+            aOutput[idx] = 1;
+        }
+        else
+        {
+            aOutput[idx] = 0;
+        }
+    }
+}
+
+CudaMatrix Aurora::sign(const CudaMatrix& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    signKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, aMatrix.getDataSize(), aMatrix.isComplex());
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
+
+CudaMatrix Aurora::sign(const CudaMatrix&& aMatrix)
+{
+    size_t size = aMatrix.getDataSize() * aMatrix.getValueType();
+    float* data = nullptr;
+    cudaMalloc((void**)&data, sizeof(float) * size);
+    int blocksPerGrid = (size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
+    signKernel<<<THREADS_PER_BLOCK, blocksPerGrid>>>(aMatrix.getData(), data, aMatrix.getDataSize(), aMatrix.isComplex());
+    cudaDeviceSynchronize();
+    return Aurora::CudaMatrix::fromRawData(data, aMatrix.getDimSize(0), aMatrix.getDimSize(1), aMatrix.getDimSize(2), aMatrix.getValueType());
+}
diff --git a/src/Function1D.cuh b/src/Function1D.cuh
new file mode 100644
index 0000000..d7ba7dd
--- /dev/null
+++ b/src/Function1D.cuh
@@ -0,0 +1,44 @@
+#ifndef AURORA_CUDA_FUNCTION1D_H
+#define AURORA_CUDA_FUNCTION1D_H
+
+#include "CudaMatrix.h"
+
+namespace Aurora
+{
+    CudaMatrix complex(const CudaMatrix& aMatrix);
+
+    CudaMatrix real(const CudaMatrix& aMatrix);
+
+    CudaMatrix imag(const CudaMatrix& aMatrix);
+
+    CudaMatrix ceil(const CudaMatrix& aMatrix);
+
+    CudaMatrix ceil(const CudaMatrix&& aMatrix);
+
+    CudaMatrix round(const CudaMatrix& aMatrix);
+
+    CudaMatrix round(const CudaMatrix&& aMatrix);
+
+    CudaMatrix floor(const CudaMatrix& aMatrix);
+
+    CudaMatrix floor(const CudaMatrix&& aMatrix);
+
+    /**
+     * 开根号，暂时只支持正整数
+     * @param matrix
+     * @return
+     */
+    CudaMatrix sqrt(const CudaMatrix& aMatrix);
+
+    CudaMatrix sqrt(const CudaMatrix&& aMatrix);
+
+    CudaMatrix abs(const CudaMatrix& aMatrix);
+
+    CudaMatrix abs(const CudaMatrix&& aMatrix);
+
+    CudaMatrix sign(const CudaMatrix& aMatrix);
+
+    CudaMatrix sign(const CudaMatrix&& aMatrix);
+}
+
+#endif //AURORA_CUDA_FUNCTION1D_H
\ No newline at end of file
diff --git a/test/Function1D_Cuda_Test.cpp b/test/Function1D_Cuda_Test.cpp
new file mode 100644
index 0000000..bfdaf3f
--- /dev/null
+++ b/test/Function1D_Cuda_Test.cpp
@@ -0,0 +1,224 @@
+#include <gtest/gtest.h>
+
+#include "CudaMatrix.h"
+#include "Matrix.h"
+#include "TestUtility.h"
+
+#include "Function1D.h"
+#include "Function1D.cuh"
+
+class Function1D_Cuda_Test:public ::testing::Test
+{
+protected:
+    static void SetUpFunction1DCudaTester(){
+
+    }
+    static void TearDownTestCase(){
+    }
+    void SetUp(){
+    }
+    void TearDown(){
+    }
+
+};
+
+TEST_F(Function1D_Cuda_Test, complex)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1,2,3,4,5,6,7,8}, 2,2,2);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::complex(hostMatrix);
+    auto result2 = Aurora::complex(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Complex);
+    for(size_t i=0; i<result1.getDataSize() * 2; ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, real)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1,2,3,4,5,6,7,8}, 2,2,1,Aurora::Complex);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::real(hostMatrix);
+    auto result2 = Aurora::real(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, imag)
+{
+    Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1,2,3,4,5,6,7,8}, 2,2,1,Aurora::Complex);
+    Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
+    
+    auto result1 = Aurora::imag(hostMatrix);
+    auto result2 = Aurora::imag(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, ceil)
+{
+    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::ceil(hostMatrix);
+    auto result2 = Aurora::ceil(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::ceil(hostMatrix);
+    result2 = Aurora::ceil(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Complex);
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, round)
+{
+    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::round(hostMatrix);
+    auto result2 = Aurora::round(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::round(hostMatrix);
+    result2 = Aurora::round(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Complex);
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, floor)
+{
+    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::floor(hostMatrix);
+    auto result2 = Aurora::floor(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::floor(hostMatrix);
+    result2 = Aurora::floor(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Complex);
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, sqrt)
+{
+    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::sqrt(hostMatrix);
+    auto result2 = Aurora::sqrt(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::sqrt(hostMatrix);
+    result2 = Aurora::sqrt(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Complex);
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, abs)
+{
+    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::abs(hostMatrix);
+    auto result2 = Aurora::abs(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::abs(hostMatrix);
+    result2 = Aurora::abs(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}
+
+TEST_F(Function1D_Cuda_Test, sign)
+{
+    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::sign(hostMatrix);
+    auto result2 = Aurora::sign(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 8);
+    EXPECT_EQ(result2.getValueType(), Aurora::Normal);
+    for(size_t i=0; i<result1.getDataSize(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+
+    hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
+    deviceMatrix = hostMatrix.toDeviceMatrix();
+    result1 = Aurora::sign(hostMatrix);
+    result2 = Aurora::sign(deviceMatrix).toHostMatrix();
+    EXPECT_EQ(result2.getDataSize(), 4);
+    EXPECT_EQ(result2.getValueType(), Aurora::Complex);
+    for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
+    {
+        EXPECT_EQ(result1[i], result2[i]);
+    }
+}