CUDA內核只啓動並運行在某些網格大小

我實際上正在使用CUDA，並且正在嘗試使用此技術來優化程序。所以我有一個大的內核，我必須在100k +時間和100M +時間或者數十億之間啓動？CUDA內核只啓動並運行在某些網格大小

所以我讀使用爲dim3變量允許線程推出的量（參見：https://devtalk.nvidia.com/default/topic/621867/size-limitation-for-1d-arrays-in-cuda-/?offset=7）

我得到了一個示例代碼（在我的gtx970）運行一段時間並且有時沒有。

#ifndef PROPAGATORSAT_CUH_ 
# define PROPAGATORSAT_CUH 
# define M_PI (3.14159265358979323846) 
# define TWO_PI (2 * M_PI) 
# define TOTAL_TIME (615359.772) 
# define STEP (0.771) 
# define NB_IT (TOTAL_TIME/(double)STEP) 
# define NB_THREADS (1024) 
# define NB_BLOCKS (int)((NB_IT + NB_THREADS - 1)/NB_THREADS) 

# include <cmath> 
# include <cfloat> 
# include <stdio.h> 
# include "../common/book.h" 
# include "cuda_runtime.h" 
# include "device_launch_parameters.h" 
# define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); } 
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true) 
{ 
    if (code != cudaSuccess) 
    { 
     fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line); 
     if (abort) exit(code); 
    } 
} 

class       Global 
{ 
public: 
    const double    _ITURadEarth = 6378145.0; 
    const double    _ITUGravCst = 3.986012E5; 
    const double    _ITUJ2 = 0.001082636; 
    const double    _J2000AngleDeg = 0;//-79.8058; 
    const double    _J2000AngleRad = 0;//TO_RAD(_J2000AngleDeg); 
    const double    _ITUAngleRateEarthRot = 4.1780745823E-3; 
    const double    _ITUAngleRateEarthRotRad = degToRad(_ITUAngleRateEarthRot); 

public: 
      __device__ double myAsin(double angle); 
    __host__ __device__ double myAcos(double angle); 
    __host__ __device__ double negPiToPi(double angle); 
    __host__ __device__ double degToRad(double angle); 
      __device__ double radToDeg(double angle); 
}; 

class        Cartesian 
{ 
public: 
    double       _X; 
    double       _Y; 
    double       _Z; 

private: 
    double       _m; 

public: 
    __host__ __device__    Cartesian(double x, double y, double z) : _X(x), _Y(y), _Z(z), _m(-1) {} 
}; 

class      Propagator 
{ 
public: 
    double     _iDeg; 
    double     _a; 
    double     _omega_0; 
    double     _OMEGA_0; 
    double     _omega_r; 
    double     _OMEGA_r; 
    double     _rho; 
    double     _SinI; 
    double     _CosI; 
    double     _p; 
    double     _e; 
    double     _ReKm; 
    double     _n0; 
    double     _n_bar; 
    double     _M0; 
    double     _sqrt_e; 
    int      _orbitCase = -1; 
    double     _WdeltaRad; 
    double     _precessionRateRad; 
    double     _artificialPrecessionRad = DBL_MIN; 
    double     _simulationDuration = DBL_MIN; 
    double     _incrementWdeltaRad; 

    void     propagator(double    smaKm, 
             double    incDeg, 
             double    e, 
             double    raanDeg, 
             double    aopDeg, 
             double    trueAnomalyDeg, 
             bool     stationKeeping, 
             double    WdeltaDeg, 
             bool     precessionMechanismSupplied, 
             double    precessionRateDeg); 
    __device__ Cartesian evaluate(double     timeSec, 
            double     simulationDuration, 
            double     artificialPrecessionRad, 
            bool     ECImode); 
    __device__ double  solveKepler(double    M, 
             double    e, 
             double    epsilon); 
    __device__ Cartesian rotateOrbitalElements(Cartesian pq0, 
                double omega, 
                double OMEGA, 
                double CosI, 
                double SinI); 
}; 

#endif /* !PROPAGATORSAT_CUH_ */ 

__host__ __device__ double Global::myAcos(double angle) 
{ 
    return (acos(((angle > 1) ? (1) : (angle < -1) ? (-1) : (angle)))); 
} 

__device__ double Global::myAsin(double angle) 
{ 
    return (asin(((angle > 1) ? (1) : (angle < -1) ? (-1) : (angle)))); 
} 

__host__ __device__ double Global::degToRad(double angle) 
{ 
    return (angle * M_PI/180.0); 
} 

__device__ double Global::radToDeg(double angle) 
{ 
    return (angle * 180.0/M_PI); 
} 

__host__ __device__ double Global::negPiToPi(double angle) 
{ 
    double   output; 

    output = fmod(angle, TWO_PI); 
    output = fmod(angle + TWO_PI, TWO_PI); 
    return ((output > M_PI) ? (output - TWO_PI) : (output)); 
} 

void  Propagator::propagator(double smaKm, double incDeg, double e, double raanDeg, double aopDeg, double trueAnomalyDeg, bool stationKeeping, double WdeltaDeg, bool precessionMechanismSupplied, double precessionRateDeg) 
{ 
    double   iRad, trueAnomalyRad, cosV, E, mu; 
    Global   global; 

    _iDeg = incDeg; 
    iRad = global.degToRad(_iDeg); 
    _CosI = cos(iRad); 
    _SinI = sin(iRad); 
    _e = e; 
    _a = smaKm; 
    trueAnomalyRad = global.degToRad(trueAnomalyDeg); 
    if (e == 0) 
     _M0 = trueAnomalyRad; 
    else 
    { 
     cosV = cos(trueAnomalyRad); 
     E = global.myAcos((e + cosV)/(1 + e * cosV)); 
     if (global.negPiToPi(trueAnomalyRad) < 0) 
      E = M_PI * 2 - E; 
     _M0 = E - e * sin(E); 
    } 
    _OMEGA_0 = global.degToRad(raanDeg); 
    _omega_0 = global.degToRad(aopDeg); 
    _p = _a * (1 - e * e); 
    _ReKm = global._ITURadEarth/1000; 
    mu = global._ITUGravCst; 
    _n0 = sqrt(mu/pow(_a, 3)); 
    _n_bar = _n0 * (1.0 + 1.5 * global._ITUJ2 * pow(_ReKm, 2)/pow(_p, 2) * (1.0 - 1.5 * pow(_SinI, 2)) * pow(1.0 - pow(e, 2), 0.5)); 
    _OMEGA_r = -1.5 * global._ITUJ2 * pow(_ReKm, 2)/pow(_p, 2) * _n_bar * _CosI; 
    _omega_r = 1.5 * global._ITUJ2 * pow(_ReKm, 2)/pow(_p, 2) * _n_bar * (2.0 - 2.5 * pow(_SinI, 2)); 
    _sqrt_e = sqrt((1 + e)/(1 - e)); 
    _WdeltaRad = global.degToRad(WdeltaDeg); 
    _precessionRateRad = global.degToRad(precessionRateDeg); 
    if (stationKeeping == false) 
     _orbitCase = 1; 
    else if (precessionMechanismSupplied == false) 
     _orbitCase = 2; 
    else 
     _orbitCase = 3; 
} 

__device__ Cartesian Propagator::rotateOrbitalElements(Cartesian pq0, double omega, double OMEGA, double CosI, double SinI) 
{ 
    double    CosOMEGA, SinOMEGA, CosOmega, SinOmega, R11, R12, R13, R21, R22, R23, R31, R32, R33, x, y, z; 

    CosOMEGA = cos(OMEGA); 
    SinOMEGA = sin(OMEGA); 
    CosOmega = cos(omega); 
    SinOmega = sin(omega); 
    R11 = CosOMEGA * CosOmega - SinOMEGA * SinOmega * CosI; 
    R12 = -CosOMEGA * SinOmega - SinOMEGA * CosOmega * CosI; 
    R13 = SinOMEGA * SinI; 
    R21 = SinOMEGA * CosOmega + CosOMEGA * SinOmega * CosI; 
    R22 = -SinOMEGA * SinOmega + CosOMEGA * CosOmega * CosI; 
    R23 = -CosOMEGA * SinI; 
    R31 = SinOmega * SinI; 
    R32 = CosOmega * SinI; 
    R33 = CosI; 
    x = R11 * pq0._X + R12 * pq0._Y + R13 * pq0._Z; 
    y = R21 * pq0._X + R22 * pq0._Y + R23 * pq0._Z; 
    z = R31 * pq0._X + R32 * pq0._Y + R33 * pq0._Z; 
    Cartesian   cart = Cartesian(x, y, z); 

    return (cart); 
} 
__device__ Cartesian Propagator::evaluate(double timeSec, double simulationDuration, double artificialPrecessionRad, bool ECImode = true) 
{ 
    double    M, E, v, cosV, sinV, rotationAngleECF, omega, OMEGA; 
    Global    global; 

    if (_simulationDuration != simulationDuration || _artificialPrecessionRad != artificialPrecessionRad) 
    { 
     _simulationDuration = simulationDuration; 
     _artificialPrecessionRad = artificialPrecessionRad; 
     _incrementWdeltaRad = (_WdeltaRad * 2)/_simulationDuration; 
    } 
    M = _M0 + ((_orbitCase == 3) ? _n0 : _n_bar) * timeSec; 
    E = E = (_e == 0) ? M : solveKepler(M, _e, 1e-8); 
    v = 2.0 * atan(_sqrt_e * tan(E/2)); 
    cosV = cos(v); 
    sinV = sin(v); 
    _rho = _p/(1 + _e * cosV); 
    rotationAngleECF = (ECImode) ? 0 : -1 * (global._J2000AngleRad + timeSec * global._ITUAngleRateEarthRotRad); 
    omega = _omega_0 + ((_orbitCase == 3) ? 0 : _omega_r * timeSec); 
    OMEGA = _OMEGA_0 + rotationAngleECF + ((_orbitCase == 3) ? 0 : _OMEGA_r * timeSec); 
    if (_orbitCase == 1) 
     OMEGA += artificialPrecessionRad * timeSec; 
    else if (_orbitCase == 2) 
     OMEGA += _WdeltaRad * ((2.0 * timeSec/_simulationDuration) - 1); 
    else if (_orbitCase == 3) 
     OMEGA += _precessionRateRad * timeSec - _WdeltaRad + _incrementWdeltaRad * timeSec; 
    Cartesian pq0 = Cartesian(1000 * _rho * cosV, 1000 * _rho * sinV, 0); 

    Cartesian positionECI = Propagator::rotateOrbitalElements(pq0, omega, OMEGA, _CosI, _SinI); 

    return (positionECI); 
} 
__device__ double Propagator::solveKepler(double M, double e, double epsilon) 
{ 
    double   En, Ens; 

    En = M; 
    Ens = En - (En - e * sin(En) - M)/(1 - e * cos(En)); 
    while (abs(Ens - En) > epsilon) 
    { 
     En = Ens; 
     Ens = En - (En - e * sin(En) - M)/(1 - e * cos(En)); 
    } 
    return (Ens); 
} 

__global__ void kernel(Propagator *CUDA_prop) 
{ 
    size_t  tid; 

    tid = (blockIdx.x + blockIdx.y * gridDim.x + gridDim.x * gridDim.y * blockIdx.z) * blockDim.x + threadIdx.x; 
    //if (tid < NB_IT) 
    Cartesian positionNGSOsatECI = CUDA_prop[0].evaluate(STEP * tid, 615359.772, 0); 
} 

int  main(void) 
{ 
    cudaEvent_t  start, stop; 
    HANDLE_ERROR(cudaEventCreate(&start)); 
    HANDLE_ERROR(cudaEventCreate(&stop)); 
    HANDLE_ERROR(cudaEventRecord(start, 0)); 
    Propagator prop[1], *CUDA_prop; 
    dim3  block(1000, 1, 1); 
    dim3  thread(1024, 1, 1); 

    prop[0].propagator(7847.3, 53, 0, 18, 0, 67.5, true, 5, true, 3.4000000596279278E-05); 
    HANDLE_ERROR(cudaMalloc((void **)&CUDA_prop, sizeof(Propagator))); 
    HANDLE_ERROR(cudaMemcpy(CUDA_prop, prop, sizeof(Propagator), cudaMemcpyHostToDevice)); 
    kernel <<< block, thread >>> (CUDA_prop); 
    gpuErrchk(cudaPeekAtLastError()); 
    gpuErrchk(cudaDeviceSynchronize()); 
    HANDLE_ERROR(cudaFree(CUDA_prop)); 
    HANDLE_ERROR(cudaEventRecord(stop, 0)); 
    HANDLE_ERROR(cudaEventSynchronize(stop)); 
    float   elapsedTime; 
    HANDLE_ERROR(cudaEventElapsedTime(&elapsedTime, start, stop)); 
    printf("time : %f ms\n", elapsedTime); 
    HANDLE_ERROR(cudaEventDestroy(start)); 
    HANDLE_ERROR(cudaEventDestroy(stop)); 
    return (0); 
}

如果我啓動這個數量的「線程？」它工作到大約300k塊。但有時它的數量不一樣。我得到一個錯誤：「未知錯誤」從線路：

gpuErrchk(cudaDeviceSynchronize());

或cudaFree，或內核調用後一些功能。在這裏輸入代碼

如果我只用1k塊和1k線程啓動並使用cuda-memcheck我得到與以前相同的錯誤但沒有cuda-memcheck它運行得很好。

我不知道是什麼導致這個問題，以及如何解決它

注：了handle_error宏可以通過gpuErrchk maccro改變，這是從做同樣的事情庫中的定義

而且我也想知道如何確定我可以使用硬件或任何其他規格啓動的最大線程數量。

來源

2016-09-26 Nico Wadel

聽起來很像[看門狗定時器]（https://devtalk.nvidia.com/default/topic/459869/cuda-programming-and-performance/-quot-display-driver-stopped-responding-and- has-recovered-quot-wddm-timeout-detection-and-recovery-/）踢進來。內核運行多久才失敗？ – tera

您的GPU是專用計算設備還是您也將其用於顯示？ – talonmies

我也使用我的GPU進行顯示，內核爲300k塊和1024線程運行約2100毫秒，100k塊和1024線程運行約700毫秒。對於看門狗，我看起來更早，它被設置爲6或7秒。當它失敗時，它不會運行超過3秒 –

在使用WDDM驅動程序的Windows上，可以批量啓動多個內核以減少啓動開銷。由於看門狗定時器適用於整個批處理，即使每個內核本身在選定的超時值內完成，也可能會觸發超時。

到目前爲止，強制立即執行所有內核的廉價方法是調用cudaStreamQuery(0)。不同於調用cudaDeviceSynchronize()，這將立即返回，而不是等待內核完成。

內核調用之間的散列cudaStreamQuery(0)因此確保WDDM超時只適用於兩個cudaStreamQuery(0)調用之間的內核。

如果即使單個內核需要很長時間並觸發看門狗，也可以嘗試將其分割爲多個調用，每個調用的塊數較少，然後再次調用cudaStreamQuery(0)。這不僅使監督人員感到高興，而且也使GUI具有一定的反應性。

來源

2016-09-26 12:36:45 tera

我做了你所說的。在多個內核調用之間以及甚至之後使用cudaStreamQuery，我將內核分割爲多個內核來啓動較少的塊。但是我也遇到了同樣的問題。 5分鐘前我可以啓動<<< 400000，1024 >>>現在我甚至不能啓動<<< 200000,1024 >>>，我試過了15秒後我可以啓動<<< 200000,1024 >>> kernel ... –

然後再減少塊數。我個人會在慢速或0.01s的速度上瞄準像0.1s這樣的快速GPU，這樣a）保持GUI模糊響應，b）仍然遠離看門狗超時，c）即使升級到GPU速度提升10倍。 – tera

或者獲得獨立的GPU進行顯示，並將GPU置於TCC模式（如果支持，則切換到Linux :)）。 – tera

CUDA內核只啓動並運行在某些網格大小

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