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RasterProcessTool
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修改默认参数，提交代码用于检查

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陈增辉 2025-04-02 10:28:51 +08:00
parent bdaa4f22f7
commit 934a39cbff
4 changed files with 65 additions and 40 deletions
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69
Toolbox/SimulationSARTool/SimulationSAR/GPURFPC.cu
View File

@ -490,7 +490,10 @@ __global__ void Kernel_Computer_R_amp_NoAntPattern(
double maxGain, double GainWeight,
float* d_temp_R, float* d_temp_amps// 计算输出
) {
long long idx = blockIdx.x * blockDim.x + threadIdx.x; // »ñÈ¡µ±Ç°µÄÏ̱߳àÂë
long long tid = threadIdx.x;
long long bid = blockIdx.x;
long long dmx = blockDim.x;
long long idx = bid*dmx+tid; // »ñÈ¡µ±Ç°µÄÏ̱߳àÂë
long long prfId = idx / SHAREMEMORY_FLOAT_HALF;
long long posId = idx % SHAREMEMORY_FLOAT_HALF + startPosId; // 当前线程对应的影像点
@ -506,26 +509,13 @@ __global__ void Kernel_Computer_R_amp_NoAntPattern(
double RstZ = antp.Pz - gp.Tz;
double RstR = sqrt(RstX * RstX + RstY * RstY + RstZ * RstZ); // 矢量距离
if (RstR<NearR || RstR>FarR) {
if (prfId > 200) {
printf("error prfId:%d ,idx:%d RstR:%e antP=[%e,%e,%e] ,gp=[%e,%e,%e]\n", prfId, idx, RstR,
antp.Px, antp.Py, antp.Pz, gp.Tx, gp.Ty, gp.Tz
);
}
d_temp_R[idx] = 0;
d_temp_R[idx] = RstR;
d_temp_amps[idx] = 0;
return;
}
else {
if (prfId > 200) {
printf(" prfId:%d ,idx:%d RstR:%e antP=[%e,%e,%e] ,gp=[%e,%e,%e]\n", prfId, idx, RstR,
antp.Px, antp.Py, antp.Pz, gp.Tx, gp.Ty, gp.Tz
);
}
RstX = RstX / RstR;
RstY = RstY / RstR;
RstZ = RstZ / RstR;
@ -540,8 +530,8 @@ __global__ void Kernel_Computer_R_amp_NoAntPattern(
float localangle = acosf(dotAB / (slopR));
if (localangle < 0 || localangle >= LAMP_CUDA_PI / 2 || isnan(localangle)) {
d_temp_R[idx] = 0;
d_temp_amps[idx] = 0;
d_temp_R[idx] = RstR;
d_temp_amps[idx] = localangle;
return;
}
else {}
@ -572,21 +562,35 @@ __global__ void Kernel_Computer_R_amp_NoAntPattern(
sigma = powf(10.0, sigma / 10.0);
float temp_amp = float(ampGain * Pt * sigma);
float temp_R = float(double(RstR - refPhaseRange));
float temp_R = float(RstR - refPhaseRange);
if (isnan(temp_amp) || isnan(temp_R) || isinf(temp_amp) || isinf(temp_R)) {
printf("amp is nan or R is nan,amp=%f;R=%f; \n", temp_amp, temp_R);
d_temp_R[idx] = 0;
d_temp_amps[idx] = 0;
return;
}
else {
d_temp_amps[idx] = temp_amp ;
d_temp_R[idx] = temp_R ;
return;
//if (prfId > 200) {
// printf("idx:%lld , prfid:%lld , d_temp_amp=%e,d_temp_R=%e\n", idx, prfId,d_temp_amps[idx], d_temp_R[idx]);
//}
//return;
}
//if (isnan(temp_amp) || isnan(temp_R) || isinf(temp_amp) || isinf(temp_R)) {
// printf("amp is nan or R is nan,amp=%f;R=%f; \n", temp_amp, temp_R);
// d_temp_R[idx] = 0;
// d_temp_amps[idx] = 0;
// return;
//}
//else {
// if (prfId > 200) {
// printf("error prfId:%ld RstR:%e antP=[%e,%e,%e] ,gp=[%e,%e,%e],temp_amp=%e,temp_R=%e\n", prfId, RstR,
// antp.Px, antp.Py, antp.Pz, gp.Tx, gp.Ty, gp.Tz,
// temp_amp, temp_R);
// }
// d_temp_amps[idx] = temp_amp;
// d_temp_R[idx] = temp_R;
// return;
//}
}
}
}
@ -622,7 +626,9 @@ __global__ void CUDA_Kernel_Computer_echo_NoAntPattern(
s_R[psid] = d_temp_R[pixelId];
s_amp[psid] = d_temp_amps[pixelId];
if (prfId > 200) {
printf("prfId:%d ,idx:%d s_R:%f S_amp:%f \n", prfId, idx, s_R[psid], s_amp[psid]);
printf(" s_R=%e S_amp=%e d_temp_R=%e d_temp_amps=%e idx=%lld prfid=%lld\n", s_R[psid], s_amp[psid],
d_temp_R[pixelId], d_temp_amps[pixelId], idx, prfId
);
}
}
@ -667,7 +673,7 @@ __global__ void CUDA_Kernel_Computer_echo_NoAntPattern(
/** 分块处理 ****************************************************************************************************************/
extern "C" void ProcessRFPCTask(RFPCTask& task, long devid)
extern "C" void ProcessRFPCTask(RFPCTask& task, long devid, float* h_R, float* h_amp)
{
size_t pixelcount = task.prfNum * task.freqNum;
size_t grid_size = (pixelcount + BLOCK_SIZE - 1) / BLOCK_SIZE;
@ -686,6 +692,7 @@ extern "C" void ProcessRFPCTask(RFPCTask& task, long devid)
long prfcount = task.prfNum;
long process = 0;
for (long sTi = 0; sTi < task.targetnum; sTi = sTi + SHAREMEMORY_FLOAT_HALF) {
cudaBlocknum = (task.prfNum * SHAREMEMORY_FLOAT_HALF + BLOCK_SIZE - 1) / BLOCK_SIZE;
Kernel_Computer_R_amp_NoAntPattern << <cudaBlocknum, BLOCK_SIZE >> > (
task.antlist,
@ -703,6 +710,9 @@ extern "C" void ProcessRFPCTask(RFPCTask& task, long devid)
PrintLasterError("CUDA_Kernel_Computer_R_amp");
cudaDeviceSynchronize();
DeviceToHost(h_R, d_R, task.prfNum * SHAREMEMORY_FLOAT_HALF * sizeof(float));
DeviceToHost(h_amp, d_amps, task.prfNum * SHAREMEMORY_FLOAT_HALF * sizeof(float));
break;
cudaBlocknum = (task.prfNum * BLOCK_FREQNUM + BLOCK_SIZE- 1) / BLOCK_SIZE;
CUDA_Kernel_Computer_echo_NoAntPattern << <cudaBlocknum, BLOCK_SIZE >> > (
@ -718,6 +728,11 @@ extern "C" void ProcessRFPCTask(RFPCTask& task, long devid)
process = sTi * 100.0 / task.targetnum;
PRINT("device ID : %d , TargetID [%f]: %d / %d finished %d\n", devid, sTi * 100.0 / task.targetnum, sTi, task.targetnum, devid);
}
}

8
Toolbox/SimulationSARTool/SimulationSAR/GPURFPC.cuh
View File

@ -16,11 +16,7 @@
extern "C" struct SateState {
double Px, Py, Pz, Vx, Vy, Vz;
//double antXaxisX, antXaxisY, antXaxisZ;
//double antYaxisX, antYaxisY, antYaxisZ;
//double antZaxisX, antZaxisY, antZaxisZ;
double antDirectX, antDirectY, antDirectZ;
double Px, Py, Pz, Vx, Vy, Vz,antDirectX, antDirectY, antDirectZ;
};
@ -152,7 +148,7 @@ extern "C" void CUDA_RFPC_MainProcess(
extern "C" double* hostSigmaData_toDevice(int devid);
extern "C" void ProcessRFPCTask(RFPCTask& task,long devid);
extern "C" void ProcessRFPCTask(RFPCTask& task,long devid,float* h_R,float* h_amp);

6
Toolbox/SimulationSARTool/SimulationSAR/QImageSARRFPC.ui
View File

@ -103,7 +103,7 @@
</size>
</property>
<property name="text">
<string>D:/FZSimulation/LTDQ/Input/LandCover.dat</string>
<string>D:/FZSimulation/LTDQ/Input/testEcho/LandCover.dat</string>
</property>
</widget>
</item>
@ -233,7 +233,7 @@
</size>
</property>
<property name="text">
<string>D:/FZSimulation/LTDQ/Input/DEM_XYZ.dat</string>
<string>D:/FZSimulation/LTDQ/Input/testEcho/DEMXYZ.dat</string>
</property>
</widget>
</item>
@ -350,7 +350,7 @@
</size>
</property>
<property name="text">
<string>D:/FZSimulation/LTDQ/Input/DEM_Sloper.dat</string>
<string>D:/FZSimulation/LTDQ/Input/testEcho/DEMSloper.dat</string>
</property>
</widget>
</item>

18
Toolbox/SimulationSARTool/SimulationSAR/RFPCProcessCls.cpp
View File

@ -1114,9 +1114,18 @@ ErrorCode RFPCProcessCls::RFPCMainProcess_GPU_NoAntPattern(size_t startprfid, si
task.antlist = (SateState*)mallocCUDADevice(prfcount * sizeof(SateState), devId);
HostToDevice(h_antlist.get(), task.antlist, sizeof(SateState) * prfcount);
printf("h_antlist: %e,%e,%e,%e,%e,%e,%e,%e,%e \n",
h_antlist.get()[0].Px, h_antlist.get()[0].Py, h_antlist.get()[0].Pz,
h_antlist.get()[0].Vx, h_antlist.get()[0].Vy, h_antlist.get()[0].Vz,
h_antlist.get()[0].antDirectX, h_antlist.get()[0].antDirectY, h_antlist.get()[0].antDirectZ
);
testOutAmpArr(QString("antlist_%1.dat").arg(devId), (double*)(h_antlist.get()), prfcount, 9);
}
float* h_R = (float*)mallocCUDAHost(sizeof(float) * prfcount * SHAREMEMORY_FLOAT_HALF); //2GB 距离
float* h_amp = (float*)mallocCUDAHost(sizeof(float) * prfcount * SHAREMEMORY_FLOAT_HALF);//2GB 强度
// 分块计算
for (const auto& pair : clsGoalStateDict) {
long clsid = pair.first;
@ -1128,7 +1137,12 @@ ErrorCode RFPCProcessCls::RFPCMainProcess_GPU_NoAntPattern(size_t startprfid, si
task.goallist = (GoalState*)mallocCUDADevice(clscount * sizeof(GoalState), devId);
HostToDevice(clsGoalStateDict[clsid].get(), task.goallist, sizeof(GoalState) * clscount);
ProcessRFPCTask(task, devId);
ProcessRFPCTask(task, devId, h_R, h_amp);
testOutDataArr(QString("h_R_%1.bin").arg(devId), h_R, prfcount, SHAREMEMORY_FLOAT_HALF);
exit(-1);
FreeCUDADevice(task.goallist);
}