C++ CLKernel::out方法代码示例

TEST(testlocal, reduceviascratch_multipleworkgroups_ints) {
    EasyCL *cl = EasyCL::createForFirstGpuOtherwiseCpu();
    CLKernel *kernel = cl->buildKernel("testlocal.cl", "reduceViaScratch_multipleworkgroups_ints");
    int workgroupSize = min(512, cl->getMaxWorkgroupSize());
    const int numWorkgroups = workgroupSize;
    const int N = workgroupSize * numWorkgroups;
    cout << "numworkgroups " << numWorkgroups << " workgroupsize " << workgroupSize << " N " << N << endl;
    int *myarray = new int[N];
    int sumViaCpu = 0;
    int localSumViaCpu = 0;
    int localSumViaCpu2 = 0;
    int *localSumsViaCpu = new int[numWorkgroups];
    memset(localSumsViaCpu, 0, sizeof(int)*numWorkgroups);
    for(int i = 0; i < N; i++) {
        myarray[i] = ((i + 7) * 3) % 50;
        sumViaCpu += myarray[i];
        if(i < workgroupSize) {
            localSumViaCpu += myarray[i];
        }
        if(i >= workgroupSize && i < workgroupSize * 2) {
            localSumViaCpu2 += myarray[i];
        }
        int workgroupId = i / workgroupSize;
        localSumsViaCpu[workgroupId] += myarray[i];
    }
    ASSERT_EQ(localSumViaCpu, localSumsViaCpu[0]);
    ASSERT_EQ(localSumViaCpu2, localSumsViaCpu[1]);
    ASSERT_NE(myarray[0], sumViaCpu);

//    Timer timer;

    CLWrapper *a1wrapper = cl->wrap(N, myarray);
    a1wrapper->copyToDevice();
    int *a2 = new int[numWorkgroups];
    CLWrapper *a2wrapper = cl->wrap(numWorkgroups, a2);
    kernel->in(a1wrapper);
    kernel->out(a2wrapper);
    kernel->localInts(workgroupSize);
    kernel->run_1d(N, workgroupSize);

    int finalSum;
    kernel->in(a2wrapper);
    kernel->out(1, &finalSum);
    kernel->localInts(workgroupSize);
    kernel->run_1d(numWorkgroups, workgroupSize);
//    timer.timeCheck("finished 2-way reduce");

    EXPECT_EQ(sumViaCpu, finalSum);

    delete a1wrapper;
    delete a2wrapper;
    delete[] a2;
    delete[]myarray;
    delete kernel;
    delete cl;
}

TEST(test_scenario_te42kyfo, main) {
    EasyCL *cl = EasyCL::createForFirstGpuOtherwiseCpu();
    CLKernel *kernel = cl->buildKernelFromString(getKernel(), "test", "");
    CLArrayFloat *out = cl->arrayFloat(5);
    CLArrayFloat *in = cl->arrayFloat(5);
    for(int i = 0; i < 5; i++) {
       (*out)[i] = 0;
    }
    for(int i = 0; i < 100; i++) {
      for(int n = 0; n < 5; n++) {
        (*in)[n] = i*n;
      }
      kernel->in(in);
      kernel->out(out);
      kernel->run_1d(5, 5);
      assertEquals(i*2 + 5, (*out)[2]);
      assertEquals(i*4 + 5, (*out)[4]);
    }
    cout << "finished" << endl;

    delete in;
    delete out;
    delete kernel;
    delete cl;
}

// this runs an entire kernel to get one value.  Clearly this is going to be pretty slow, but
// at least it's more or less compatible, and comparable, to how cutorch does it
// lgfgs expects a working implementation of this method
float THClStorage_get(THClState *state, const THClStorage *self, long index)
{
////  printf("THClStorage_get\n");
  THArgCheck((index >= 0) && (index < self->size), 2, "index out of bounds");
  THArgCheck(self->wrapper != 0, 1, "storage argument not initialized, is empty");

//  if( self->wrapper->isDeviceDirty() ) {
//    if(state->trace) cout << "wrapper->copyToHost()" << endl;
//    self->wrapper->copyToHost();
//  }
//  return self->data[index];

  const char *uniqueName = __FILE__ ":get";
  EasyCL *cl = self->cl; // cant remember if this is a good idea or not :-P
  CLKernel *kernel = 0;
  if(cl->kernelExists(uniqueName)) {
    kernel = cl->getKernel(uniqueName);
  } else {
    TemplatedKernel kernelBuilder(cl);
    kernel = kernelBuilder.buildKernel( uniqueName, __FILE__, getGetKernelSource(), "THClStorageGet" );
  }

  float res;
  kernel->out(1, &res);
  kernel->in(self->wrapper);
  kernel->in((int64_t)index);
  kernel->run_1d(1, 1);

  if(state->addFinish) cl->finish();
  return res;
}

TEST( testdefines, simple ) {
    EasyCL *cl = EasyCL::createForFirstGpuOtherwiseCpu();
    CLKernel *kernel = cl->buildKernel("testdefines.cl", "testDefines", 
        "-D DOUBLE -D SOME_VALUE=5" );
    float out[32];
    kernel->out( 32, out );
    kernel->run_1d( 32, 32 );
    EXPECT_EQ( 10, out[3] );

    delete kernel;
    delete cl;
}

TEST( testMemset, basic ) {
    EasyCL *cl = DeepCLGtestGlobals_createEasyCL();

    CLKernel *kMemset = 0;
    // [[[cog
    // import stringify
    // stringify.write_kernel2( "kMemset", "cl/memset.cl", "cl_memset", '""' )
    // ]]]
    // generated using cog, from cl/memset.cl:
    const char * kMemsetSource =  
    "// Copyright Hugh Perkins 2015 hughperkins at gmail\n"
    "//\n"
    "// This Source Code Form is subject to the terms of the Mozilla Public License,\n"
    "// v. 2.0. If a copy of the MPL was not distributed with this file, You can\n"
    "// obtain one at http://mozilla.org/MPL/2.0/.\n"
    "\n"
    "kernel void cl_memset(global float *target, const float value, const int N) {\n"
    "    #define globalId get_global_id(0)\n"
    "    if ((int)globalId < N) {\n"
    "        target[globalId] = value;\n"
    "    }\n"
    "}\n"
    "\n"
    "";
    kMemset = cl->buildKernelFromString(kMemsetSource, "cl_memset", "", "cl/memset.cl");
    // [[[end]]]

    int N = 10000;
    float *myArray = new float[N];
    CLWrapper *myArrayWrapper = cl->wrap( N, myArray );
    myArrayWrapper->createOnDevice();
    kMemset->out( myArrayWrapper )->in( 99.0f )->in( N );
    int workgroupSize = 64;
    kMemset->run_1d( ( N + workgroupSize - 1 ) / workgroupSize * workgroupSize, workgroupSize );
    cl->finish();
    myArrayWrapper->copyToHost();
    for( int i = 0; i < 10; i++ ) {
//        cout << "myArray[" << i << "]=" << myArray[i] << endl;
    }
    for( int i = 0; i < N; i++ ) {
        EXPECT_EQ( 99.0f, myArray[i] );
    }

    delete kMemset;

    delete cl;
}

TEST(testfloatarray, main) {
    if(!EasyCL::isOpenCLAvailable()) {
        cout << "opencl library not found" << endl;
        exit(-1);
    }
    cout << "found opencl library" << endl;

    EasyCL *cl = EasyCL::createForFirstGpuOtherwiseCpu();
    CLKernel *kernel = cl->buildKernelFromString(getKernel(), "test", "");
    float in[5];
    float inout[5];
    float out[5];
    for(int i = 0; i < 5; i++) {
        in[i] = i * 3;
        inout[i] = i * 3;
    }
    kernel->in(5, in);
    kernel->out(5, out);
    kernel->inout(5, inout);
    kernel->run_1d(5, 5);

    for(int i = 0; i < 5; i++) {
        cout << out[i] << " ";
    }
    cout << endl;
    for(int i = 0; i < 5; i++) {
        cout << inout[i] << " ";
    }
    cout << endl;

    assertEquals(inout[0], 7);
    assertEquals(inout[1] , 10);
    assertEquals(inout[2] , 34);
    assertEquals(inout[3] , 16);
    assertEquals(inout[4], 19);
    assertEquals(out[0] , 5);
    assertEquals(out[1] , 8);
    assertEquals(out[2] , 26);
    assertEquals(out[3] , 14);
    assertEquals(out[4] , 17);
    cout << "tests completed ok" << endl;

    delete kernel;
    delete cl;
}

int main(int argc, char *argv[]) 
{
	const int test_size = 128;

	std::random_device rd;
	std::seed_seq s{ rd(), rd(), rd(), rd(), rd(), rd(), rd(), rd() };
	std::mt19937 mt(s);

	EasyCL *cl = EasyCL::createForFirstGpuOtherwiseCpu();

	CLKernel *kern = cl->buildKernel("test.cl", "test");

	std::vector<uint32_t> inbuf(test_size*4), outbuf(test_size), compare(test_size);
	std::generate(inbuf.begin(), inbuf.end(), mt);

	std::cout << "Running CL implementation" << std::endl;
	kern->in(inbuf.size(), &inbuf[0]);
	kern->out(outbuf.size(), &outbuf[0]);
	size_t global_size[] = { test_size };
	kern->run(1, global_size, nullptr);
	delete kern;

	std::cout << "Running local implementation" << std::endl;
	for (int i = 0; i < compare.size(); ++i) {
		compare[i] = inbuf[i] ^ inbuf[i + 1] ^ inbuf[i + 2] ^ inbuf[i + 3];
	}

	std::cout << "Comparing CL test with local implementation" << std::endl;
	for (int i = 0; i < compare.size(); ++i) {
		if (outbuf[i] != compare[i]) {
			std::cout << "Error in index " << i << " " << outbuf[i] << " != " << compare[i] << std::endl;
		}
	}

	return 0;
}