Java JCuda类代码示例

import jcuda.runtime.JCuda; //导入依赖的package包/类
public void fill(Volume3D vol, float number){
	initCUDA();
	CUdeviceptr sizePointer = CUDAUtil.copyToDeviceMemory(vol.size);
	CUfunction function = new CUfunction();
	JCudaDriver.cuModuleGetFunction(function, module,
	"_Z4fillPfPifi");

	ArrayList<Object> arguments = new ArrayList<Object>();
	arguments.add(((CUDAVolume3D) vol).getDevicePointer());
	arguments.add(sizePointer);
	arguments.add(new Float(number));
	arguments.add(new Integer(vol.getInternalDimension()));

	// Calculate new grid size
	gridSize = getGrid(vol.size);

	if (debug) System.out.println("Calling.");
	callCUDAFunction(function, arguments);
	if (debug) System.out.println("Freeing.");

	JCuda.cudaFree(sizePointer);
	//((CUDAVolume3D) vol).fetch();
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public static void main(String[] args)
{
    JCuda.setExceptionsEnabled(true);;
    JCusparse.setExceptionsEnabled(true);
    JCusolver.setExceptionsEnabled(true);

    String path = "src/main/resources/data/jcusolver/";
    String fileName = path + "lap2D_5pt_n100.mtx";
    String testFunc = "chol"; // "chol", "lu", "qr"
    String reorder = "symrcm"; // "symrcm", "symamd", null

    runTest(
        "-F="+fileName,
        "-R="+testFunc,
        "-P="+reorder);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public void cuda_init()
   {
              JCudaDriver.setExceptionsEnabled(true);
               JCuda.setExceptionsEnabled(true);
               JCurand.setExceptionsEnabled(true);
			cudaDeviceReset();
			cuInit(0);
			
			context = new HeatBugsGPUContext(0,0);
			context.InitHeatBugsConstant(gridWidth,gridHeight, MAX_HEAT, randomMovementProbability, evaporationRate,diffusionRate, bugCount);
			context.InitModule(1234,bugCount,0);
			context.InitMemory(locationPointer, idealTemp, heatOutput);
			context.InitKernelParameters();
			
	
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public void cuda_init() 
      {

		JCudaDriver.setExceptionsEnabled(true);
              JCuda.setExceptionsEnabled(true);
              JCurand.setExceptionsEnabled(true);
		cudaDeviceReset();
		cuInit(0);
//		int numElements = numStudents;
		Devices = new StudentsGPUContext[numDevices];  //array of GPU contexts, can be applied to multiple GPUs
		int numElements = numStudents/numDevices;
//		int lastNumElements = 0;
		
		for(int i =0; i<numDevices ;i++)
		{
			Devices[i] = new StudentsGPUContext(i,i);
			Devices[i].InitStudentsConstant(forceToSchoolMultiplier ,randomMultiplier, yard.getWidth(),yard.getHeight());
			Devices[i].InitModule(1234, numElements, numStudents, numDevices); 
			Devices[i].InitMemory(locationPointer, buddies);
			Devices[i].InitKernelParameters();	
		}
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public void cuda_init()
   {
              JCudaDriver.setExceptionsEnabled(true);
               JCuda.setExceptionsEnabled(true);
               JCurand.setExceptionsEnabled(true);
			cudaDeviceReset();
			cuInit(0);
			
			int numCells = (gridHeight*gridWidth)/numDevices;
	//		int numBugs = bugCount/numDevices;
			for(int i = 0;i <numDevices ;i++)
			{
				contexts[i] = new HeatBugsGPUContext(i,i);
				contexts[i].InitHeatBugsConstant(gridWidth,gridHeight,i*gridHeight/numDevices,(i+1)*gridHeight/numDevices -1, MAX_HEAT, randomMovementProbability, evaporationRate,diffusionRate, bugCount,numDevices);
				contexts[i].InitModule(1234,numCells,i*(gridWidth*gridHeight)/numDevices);
				contexts[i].InitMemory(locationPointer, idealTemp, heatOutput);
				contexts[i].InitKernelParameters();
				System.out.println("device " + contexts[i].index + " begin " + contexts[i].begin_row + " endrow " + contexts[i].end_row  + " gridoffset "+ contexts[i].gridOffset + " numCells " +contexts[i].numCells); 
				
			}

}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
private TransScale() {
	JCudaDriver.setExceptionsEnabled(true);
	JCuda.setExceptionsEnabled(true);
	cuInit(0);
	// Get the number of devices 
	int[] numDevicesArray = { 0 };
	cuDeviceGetCount(numDevicesArray);
	this.numDevices = numDevicesArray[0];
	
	this.availableDevs = new ArrayBlockingQueue<>(numDevices);
	this.daemonThreads = new DeviceThread[numDevices];
	
	// Fill arrays and start the daemon thread
	for (int i = 0 ; i < numDevices ; i++) {
		this.daemonThreads[i] = new DeviceThread(this, i);
		this.daemonThreads[i].setName("DeviceThread#" + i);
		availableDevs.add(this.daemonThreads[i]);		// Add to available queue
		this.daemonThreads[i].start();
	}
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
/**
 * Lazy initialization of brownianIncrement. Synchronized to ensure thread safety of lazy init.
 */
private void doGenerateBrownianMotion() {
	if(brownianIncrements != null) return;	// Nothing to do

	// Enable exceptions and omit all subsequent error checks
	JCuda.setExceptionsEnabled(true);
	JCurand.setExceptionsEnabled(true);
	JCuda.setLogLevel(LogLevel.LOG_DEBUG);

	// Hack: It is important to init the context first. - Clean up.
	RandomVariableInterface rv = new RandomVariableCuda(0.0);
	
	curandGenerator generator = new curandGenerator();

	// Create pseudo-random number generator 
	curandCreateGenerator(generator, CURAND_RNG_PSEUDO_DEFAULT);

	// Set seed 
	curandSetPseudoRandomGeneratorSeed(generator, 1234);

	// Allocate memory for RandomVariable wrapper objects.
	brownianIncrements = new RandomVariableInterface[timeDiscretization.getNumberOfTimeSteps()][numberOfFactors];

	// Pre-calculate square roots of deltaT
	for(int timeIndex=0; timeIndex<timeDiscretization.getNumberOfTimeSteps(); timeIndex++) {
		double time = timeDiscretization.getTime(timeIndex+1);
		float sqrtOfTimeStep = (float)Math.sqrt(timeDiscretization.getTimeStep(timeIndex));

		for(int factor=0; factor<numberOfFactors; factor++) {
			// Generate n floats on device			
			CUdeviceptr realizations = RandomVariableCuda.getCUdeviceptr((long)numberOfPaths);
			jcuda.jcurand.JCurand.curandGenerateNormal(generator, realizations, numberOfPaths, 0.0f /* mean */, sqrtOfTimeStep /* stddev */);

			brownianIncrements[timeIndex][factor] = new RandomVariableCuda(time, realizations, numberOfPaths);
		}				
	}

	// Cleanup 
	curandDestroyGenerator(generator);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
/**
 * @param size in bytes
 */
public static cudnn.Pointer malloc(long size) throws CudaException
{
	Pointer deviceData=new Pointer();
	checkError(JCuda.cudaMalloc(deviceData, size));
	return cudnn.Pointer.fromJcuda(deviceData);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
/**
 * @param args
 */
public static void main2(String[] args) {
	Pointer devPtr = new Pointer();
	JCuda.cudaMalloc(devPtr, 1024 * 1024 * 1024);
	logger.info("Pointer: "+devPtr);
	JCuda.cudaFree(devPtr);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public static void main(String args[])
{
    JCuda.setExceptionsEnabled(true);;
    JCusparse.setExceptionsEnabled(true);
    JCusolver.setExceptionsEnabled(true);

    String path = "src/main/resources/data/jcusolver/";
    String fileName = path + "gr_900_900_crg.mtx";
    String testFunc = "chol"; // "chol", "lu", "qr"

    runTest(
        "-F="+fileName,
        "-R="+testFunc);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public static void main(String args[])
{
    // Enable exceptions and omit all subsequent error checks
    JCuda.setExceptionsEnabled(true);
    JCurand.setExceptionsEnabled(true);

    int n = 100;
    curandGenerator generator = new curandGenerator();

    // Allocate n floats on host 
    float hostData[] = new float[n];

    // Allocate n floats on device 
    Pointer deviceData = new Pointer();
    cudaMalloc(deviceData, n * Sizeof.FLOAT);

    // Create pseudo-random number generator 
    curandCreateGenerator(generator, CURAND_RNG_PSEUDO_DEFAULT);

    // Set seed 
    curandSetPseudoRandomGeneratorSeed(generator, 1234);

    // Generate n floats on device 
    curandGenerateUniform(generator, deviceData, n);

    // Copy device memory to host 
    cudaMemcpy(Pointer.to(hostData), deviceData, 
        n * Sizeof.FLOAT, cudaMemcpyDeviceToHost);

    // Show result
    System.out.println(Arrays.toString(hostData));

    // Cleanup 
    curandDestroyGenerator(generator);
    cudaFree(deviceData);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public static void main(String args[])
{
    JCuda.setExceptionsEnabled(true);
    JCudnn.setExceptionsEnabled(true);
    JCublas2.setExceptionsEnabled(true);

    int version = (int) cudnnGetVersion();
    System.out.printf("cudnnGetVersion() : %d , " + 
        "CUDNN_VERSION from cudnn.h : %d\n",
        version, CUDNN_VERSION);

    System.out.println("Creating network and layers...");
    Network mnist = new Network();
    
    System.out.println("Classifying...");
    int i1 = mnist.classifyExample(dataDirectory + first_image);
    int i2 = mnist.classifyExample(dataDirectory + second_image);

    mnist.setConvolutionAlgorithm(CUDNN_CONVOLUTION_FWD_ALGO_FFT);
    int i3 = mnist.classifyExample(dataDirectory + third_image);
    
    System.out.println(
        "\nResult of classification: " + i1 + " " + i2 + " " + i3);
    if (i1 != 1 || i2 != 3 || i3 != 5)
    {
        System.out.println("\nTest failed!\n");
    }
    else
    {
        System.out.println("\nTest passed!\n");
    }
    mnist.destroy();
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
public Matrix(int rows, int cols) {
	this.dontFree = false;
	this.rows = rows;
	this.cols = cols;
	this.data_d = new Pointer();
	JCuda.cudaMalloc(data_d, rows*cols * Sizeof.FLOAT);
	CublasUtil.allocated.add(this);
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
private static void getrfGetriBatched(List<Matrix> A, List<Matrix> B) {
	Pointer[] Apointers = new Pointer[A.size()];
	Pointer[] Bpointers = new Pointer[B.size()];
	for (int i=0; i<A.size(); ++i) {
		Apointers[i] = A.get(i).data_d;
		Bpointers[i] = B.get(i).data_d;
	}
	Pointer Apointers_d = new Pointer();
	JCuda.cudaMalloc(Apointers_d, A.size() * Sizeof.POINTER);
	JCuda.cudaMemcpy(Apointers_d, Pointer.to(Apointers), A.size() * Sizeof.POINTER, cudaMemcpyKind.cudaMemcpyHostToDevice);
	Pointer Bpointers_d = new Pointer();
	JCuda.cudaMalloc(Bpointers_d, B.size() * Sizeof.POINTER);
	JCuda.cudaMemcpy(Bpointers_d, Pointer.to(Bpointers), B.size() * Sizeof.POINTER, cudaMemcpyKind.cudaMemcpyHostToDevice);
	Pointer info_d = new Pointer();
	JCuda.cudaMalloc(info_d, A.size() * Sizeof.INT);
	Pointer pivots_d = new Pointer();
	JCuda.cudaMalloc(pivots_d, A.get(0).rows * A.size() * Sizeof.INT);
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
	
	JCublas2.cublasSgetrfBatched(cublasHandle, A.get(0).rows, Apointers_d, A.get(0).rows, pivots_d, info_d, A.size());
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
	
	JCublas2.cublasSgetriBatched(cublasHandle, A.get(0).rows, Apointers_d, A.get(0).rows, pivots_d, Bpointers_d, B.get(0).rows, info_d, A.size());
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
	
	JCuda.cudaFree(Apointers_d);
	JCuda.cudaFree(Bpointers_d);
	JCuda.cudaFree(info_d);
	JCuda.cudaFree(pivots_d);
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
}
 

import jcuda.runtime.JCuda; //导入依赖的package包/类
private static void gemmBatched(float alpha, List<Matrix> A, List<Matrix> B, float beta, List<Matrix> C) {
	Pointer[] Apointers = new Pointer[A.size()];
	Pointer[] Bpointers = new Pointer[B.size()];
	Pointer[] Cpointers = new Pointer[C.size()];
	for (int i=0; i<A.size(); ++i) {
		Apointers[i] = A.get(i).data_d;
		Bpointers[i] = B.get(i).data_d;
		Cpointers[i] = C.get(i).data_d;
	}
	Pointer Apointers_d = new Pointer();
	JCuda.cudaMalloc(Apointers_d, A.size() * Sizeof.POINTER);
	JCuda.cudaMemcpy(Apointers_d, Pointer.to(Apointers), A.size() * Sizeof.POINTER, cudaMemcpyKind.cudaMemcpyHostToDevice);
	Pointer Bpointers_d = new Pointer();
	JCuda.cudaMalloc(Bpointers_d, B.size() * Sizeof.POINTER);
	JCuda.cudaMemcpy(Bpointers_d, Pointer.to(Bpointers), B.size() * Sizeof.POINTER, cudaMemcpyKind.cudaMemcpyHostToDevice);
	Pointer Cpointers_d = new Pointer();
	JCuda.cudaMalloc(Cpointers_d, C.size() * Sizeof.POINTER);
	JCuda.cudaMemcpy(Cpointers_d, Pointer.to(Cpointers), C.size() * Sizeof.POINTER, cudaMemcpyKind.cudaMemcpyHostToDevice);
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
	
	JCublas2.cublasSgemmBatched(cublasHandle, cublasOperation.CUBLAS_OP_N, cublasOperation.CUBLAS_OP_N, C.get(0).rows, C.get(0).cols, B.get(0).rows, Pointer.to(new float[] {alpha}), Apointers_d, A.get(0).rows, Bpointers_d, B.get(0).rows, Pointer.to(new float[] {beta}), Cpointers_d, C.get(0).rows, A.size());
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
	
	JCuda.cudaFree(Apointers_d);
	JCuda.cudaFree(Bpointers_d);
	JCuda.cudaFree(Cpointers_d);
	if (DEBUG_SYNC) JCudaDriver.cuCtxSynchronize();
}