Beispiel #1
0
func main() {
	// Use this to check the output of each API call
	var status cl.CL_int

	//-----------------------------------------------------
	// STEP 1: Discover and initialize the platforms
	//-----------------------------------------------------
	var numPlatforms cl.CL_uint
	var platforms []cl.CL_platform_id

	// Use clGetPlatformIDs() to retrieve the number of
	// platforms
	status = cl.CLGetPlatformIDs(0, nil, &numPlatforms)

	// Allocate enough space for each platform
	platforms = make([]cl.CL_platform_id, numPlatforms)

	// Fill in platforms with clGetPlatformIDs()
	status = cl.CLGetPlatformIDs(numPlatforms, platforms, nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetPlatformIDs")

	//-----------------------------------------------------
	// STEP 2: Discover and initialize the GPU devices
	//-----------------------------------------------------
	var numDevices cl.CL_uint
	var devices []cl.CL_device_id

	// Use clGetDeviceIDs() to retrieve the number of
	// devices present
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_GPU,
		0,
		nil,
		&numDevices)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetDeviceIDs")

	// Allocate enough space for each device
	devices = make([]cl.CL_device_id, numDevices)

	// Fill in devices with clGetDeviceIDs()
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_GPU,
		numDevices,
		devices,
		nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetDeviceIDs")

	//-----------------------------------------------------
	// STEP 3: Create a context
	//-----------------------------------------------------
	var context cl.CL_context

	// Create a context using clCreateContext() and
	// associate it with the devices
	context = cl.CLCreateContext(nil,
		numDevices,
		devices,
		nil,
		nil,
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateContext")
	defer cl.CLReleaseContext(context)

	//-----------------------------------------------------
	// STEP 4: Create a command queue
	//-----------------------------------------------------
	var commandQueue [MAX_COMMAND_QUEUE]cl.CL_command_queue

	// Create a command queue using clCreateCommandQueueWithProperties(),
	// and associate it with the device you want to execute
	for i := 0; i < MAX_COMMAND_QUEUE; i++ {
		commandQueue[i] = cl.CLCreateCommandQueueWithProperties(context,
			devices[0],
			nil,
			&status)
		utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateCommandQueueWithProperties")
		defer cl.CLReleaseCommandQueue(commandQueue[i])
	}

	//-----------------------------------------------------
	// STEP 5: Create device buffers
	//-----------------------------------------------------
	producerGroupSize := cl.CL_size_t(PRODUCER_GROUP_SIZE)
	producerGlobalSize := cl.CL_size_t(PRODUCER_GLOBAL_SIZE)

	consumerGroupSize := cl.CL_size_t(CONSUMER_GROUP_SIZE)
	consumerGlobalSize := cl.CL_size_t(CONSUMER_GLOBAL_SIZE)

	var samplePipePkt [2]cl.CL_float
	szPipe := cl.CL_uint(PIPE_SIZE)
	szPipePkt := cl.CL_uint(unsafe.Sizeof(samplePipePkt))
	if szPipe%PRNG_CHANNELS != 0 {
		szPipe = (szPipe/PRNG_CHANNELS)*PRNG_CHANNELS + PRNG_CHANNELS
	}
	consumerGlobalSize = cl.CL_size_t(szPipe)
	pipePktPerThread := cl.CL_int(szPipe) / PRNG_CHANNELS
	seed := cl.CL_int(SEED)
	rngType := cl.CL_int(RV_GAUSSIAN)
	var histMin cl.CL_float
	var histMax cl.CL_float
	if rngType == cl.CL_int(RV_UNIFORM) {
		histMin = 0.0
		histMax = 1.0
	} else {
		histMin = -10.0
		histMax = 10.0
	}

	localDevHist := make([]cl.CL_int, MAX_HIST_BINS)
	cpuHist := make([]cl.CL_int, MAX_HIST_BINS)

	//Create and initialize memory objects
	rngPipe := cl.CLCreatePipe(context,
		cl.CL_MEM_READ_WRITE,
		szPipePkt,
		szPipe,
		nil,
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clCreatePipe")

	devHist := cl.CLCreateBuffer(context,
		cl.CL_MEM_READ_WRITE|cl.CL_MEM_COPY_HOST_PTR,
		MAX_HIST_BINS*cl.CL_size_t(unsafe.Sizeof(localDevHist[0])),
		unsafe.Pointer(&localDevHist[0]),
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clCreateBuffer")

	//-----------------------------------------------------
	// STEP 6: Create and compile the program
	//-----------------------------------------------------
	programSource, programeSize := utils.Load_programsource("pipe.cl")

	// Create a program using clCreateProgramWithSource()
	program := cl.CLCreateProgramWithSource(context,
		1,
		programSource[:],
		programeSize[:],
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateProgramWithSource")
	defer cl.CLReleaseProgram(program)

	// Build (compile) the program for the devices with
	// clBuildProgram()
	options := "-cl-std=CL2.0"
	status = cl.CLBuildProgram(program,
		numDevices,
		devices,
		[]byte(options),
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		var program_log interface{}
		var log_size cl.CL_size_t

		/* Find size of log and print to std output */
		cl.CLGetProgramBuildInfo(program, devices[0], cl.CL_PROGRAM_BUILD_LOG,
			0, nil, &log_size)
		cl.CLGetProgramBuildInfo(program, devices[0], cl.CL_PROGRAM_BUILD_LOG,
			log_size, &program_log, nil)
		fmt.Printf("%s\n", program_log)
		return
	}
	//utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLBuildProgram")

	//-----------------------------------------------------
	// STEP 7: Create the kernel
	//-----------------------------------------------------
	// Use clCreateKernel() to create a kernel
	produceKernel := cl.CLCreateKernel(program, []byte("pipe_producer"), &status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateKernel")
	defer cl.CLReleaseKernel(produceKernel)

	consumeKernel := cl.CLCreateKernel(program, []byte("pipe_consumer"), &status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateKernel")
	defer cl.CLReleaseKernel(consumeKernel)

	//-----------------------------------------------------
	// STEP 8: Set the kernel arguments
	//-----------------------------------------------------
	// Associate the input and output buffers with the
	// kernel
	// using clSetKernelArg()
	// Set appropriate arguments to the kernel
	status = cl.CLSetKernelArg(produceKernel,
		0,
		cl.CL_size_t(unsafe.Sizeof(rngPipe)),
		unsafe.Pointer(&rngPipe))

	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(rngPipe)")

	status = cl.CLSetKernelArg(produceKernel,
		1,
		cl.CL_size_t(unsafe.Sizeof(pipePktPerThread)),
		unsafe.Pointer(&pipePktPerThread))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(pipePktPerThread)")

	status = cl.CLSetKernelArg(produceKernel,
		2,
		cl.CL_size_t(unsafe.Sizeof(seed)),
		unsafe.Pointer(&seed))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(seed)")

	status = cl.CLSetKernelArg(produceKernel,
		3,
		cl.CL_size_t(unsafe.Sizeof(rngType)),
		unsafe.Pointer(&rngType))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(rngType)")

	//-----------------------------------------------------
	// STEP 9: Configure the work-item structure
	//-----------------------------------------------------
	// Define an index space (global work size) of work
	// items for
	// execution. A workgroup size (local work size) is not
	// required,
	// but can be used.
	// Enqueue both the kernels.
	var globalThreads = []cl.CL_size_t{producerGlobalSize}
	var localThreads = []cl.CL_size_t{producerGroupSize}

	//-----------------------------------------------------
	// STEP 10: Enqueue the kernel for execution
	//-----------------------------------------------------
	// Execute the kernel by using
	// clEnqueueNDRangeKernel().
	// 'globalWorkSize' is the 1D dimension of the
	// work-items
	var produceEvt [1]cl.CL_event
	status = cl.CLEnqueueNDRangeKernel(commandQueue[0],
		produceKernel,
		1,
		nil,
		globalThreads,
		localThreads,
		0,
		nil,
		&produceEvt[0])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clEnqueueNDRangeKernel")

	/*
	   launch consumer kernel only after producer has finished.
	   This is done to avoid concurrent kernels execution as the
	   memory consistency of pipe is guaranteed only across
	   synchronization points.
	*/
	status = cl.CLWaitForEvents(1, produceEvt[:])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clWaitForEvents(produceEvt)")

	//-----------------------------------------------------
	// STEP 8: Set the kernel arguments
	//-----------------------------------------------------
	// Associate the input and output buffers with the
	// kernel
	// using clSetKernelArg()
	// Set appropriate arguments to the kernel
	status = cl.CLSetKernelArg(consumeKernel,
		0,
		cl.CL_size_t(unsafe.Sizeof(rngPipe)),
		unsafe.Pointer(&rngPipe))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(rngPipe)")

	status = cl.CLSetKernelArg(consumeKernel,
		1,
		cl.CL_size_t(unsafe.Sizeof(devHist)),
		unsafe.Pointer(&devHist))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(devHist)")

	status = cl.CLSetKernelArg(consumeKernel,
		2,
		cl.CL_size_t(unsafe.Sizeof(histMin)),
		unsafe.Pointer(&histMin))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(histMin)")

	status = cl.CLSetKernelArg(consumeKernel,
		3,
		cl.CL_size_t(unsafe.Sizeof(histMax)),
		unsafe.Pointer(&histMax))
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArg(histMax)")

	//-----------------------------------------------------
	// STEP 9: Configure the work-item structure
	//-----------------------------------------------------
	// Define an index space (global work size) of work
	// items for
	// execution. A workgroup size (local work size) is not
	// required,
	// but can be used.
	globalThreads[0] = consumerGlobalSize
	localThreads[0] = consumerGroupSize

	//-----------------------------------------------------
	// STEP 10: Enqueue the kernel for execution
	//-----------------------------------------------------
	// Execute the kernel by using
	// clEnqueueNDRangeKernel().
	// 'globalWorkSize' is the 1D dimension of the
	// work-items
	var consumeEvt [1]cl.CL_event
	status = cl.CLEnqueueNDRangeKernel(
		commandQueue[1],
		consumeKernel,
		1,
		nil,
		globalThreads,
		localThreads,
		0,
		nil,
		&consumeEvt[0])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clEnqueueNDRangeKernel")

	status = cl.CLFlush(commandQueue[0])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clFlush(0)")

	status = cl.CLFlush(commandQueue[1])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clFlush(1)")

	//wait for kernels to finish
	status = cl.CLFinish(commandQueue[0])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clFinish(0)")

	status = cl.CLFinish(commandQueue[1])
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clFinish(1)")

	//-----------------------------------------------------
	// STEP 11: Read the output buffer back to the host
	//-----------------------------------------------------
	// Use clEnqueueReadBuffer() to read the OpenCL output
	// buffer (bufferC)
	// to the host output array (C)
	//copy the data back to host buffer
	var readEvt cl.CL_event
	status = cl.CLEnqueueReadBuffer(commandQueue[1],
		devHist,
		cl.CL_TRUE,
		0,
		(MAX_HIST_BINS)*cl.CL_size_t(unsafe.Sizeof(localDevHist[0])),
		unsafe.Pointer(&localDevHist[0]),
		0,
		nil,
		&readEvt)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clEnqueueReadBuffer")

	//-----------------------------------------------------
	// STEP 12: Verify the results
	//-----------------------------------------------------
	//Find the tolerance limit
	fTol := (float32)(CONSUMER_GLOBAL_SIZE) * (float32)(COMP_TOL) / (float32)(100.0)
	iTol := (int)(fTol)
	if iTol == 0 {
		iTol = 1
	}

	//CPU side histogram computation
	CPUReference(seed, pipePktPerThread, rngType, cpuHist, histMax, histMin)

	//Compare
	for bin := 0; bin < MAX_HIST_BINS; bin++ {
		diff := int(localDevHist[bin] - cpuHist[bin])

		if diff < 0 {
			diff = -diff
		}
		if diff > iTol {
			println("Failed!")
			return
		}
	}

	println("Passed!")
}
Beispiel #2
0
func main() {
	// Use this to check the output of each API call
	var status cl.CL_int

	//-----------------------------------------------------
	// STEP 1: Discover and initialize the platforms
	//-----------------------------------------------------
	var numPlatforms cl.CL_uint

	// Use clGetPlatformIDs() to retrieve the number of
	// platforms
	status = cl.CLGetPlatformIDs(0, nil, &numPlatforms)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetPlatformIDs")

	// Allocate enough space for each platform
	platforms := make([]cl.CL_platform_id, numPlatforms)

	// Fill in platforms with clGetPlatformIDs()
	status = cl.CLGetPlatformIDs(numPlatforms, platforms, nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetPlatformIDs")

	//-----------------------------------------------------
	// STEP 2: Discover and initialize the GPU devices
	//-----------------------------------------------------
	var numDevices cl.CL_uint

	// Use clGetDeviceIDs() to retrieve the number of
	// devices present
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_GPU,
		0,
		nil,
		&numDevices)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetDeviceIDs")

	// Allocate enough space for each device
	devices := make([]cl.CL_device_id, numDevices)

	// Fill in devices with clGetDeviceIDs()
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_GPU,
		numDevices,
		devices,
		nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetDeviceIDs")

	var caps cl.CL_device_svm_capabilities
	var caps_value interface{}

	status = cl.CLGetDeviceInfo(
		devices[0],
		cl.CL_DEVICE_SVM_CAPABILITIES,
		cl.CL_size_t(unsafe.Sizeof(caps)),
		&caps_value,
		nil)
	caps = caps_value.(cl.CL_device_svm_capabilities)

	// Coarse-grained buffer SVM should be available on any OpenCL 2.0 device.
	// So it is either not an OpenCL 2.0 device or it must support coarse-grained buffer SVM:
	if !(status == cl.CL_SUCCESS && (caps&cl.CL_DEVICE_SVM_FINE_GRAIN_BUFFER) != 0) {
		fmt.Printf("Cannot detect fine-grained buffer SVM capabilities on the device. The device seemingly doesn't support fine-grained buffer SVM. caps=%x\n", caps)
		println("")
		return
	}

	//-----------------------------------------------------
	// STEP 3: Create a context
	//-----------------------------------------------------
	// Create a context using clCreateContext() and
	// associate it with the devices
	context := cl.CLCreateContext(nil,
		numDevices,
		devices,
		nil,
		nil,
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateContext")
	defer cl.CLReleaseContext(context)

	//-----------------------------------------------------
	// STEP 4: Create a command queue
	//-----------------------------------------------------
	// Create a command queue using clCreateCommandQueueWithProperties(),
	// and associate it with the device you want to execute
	queue := cl.CLCreateCommandQueueWithProperties(context,
		devices[0],
		nil,
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateCommandQueueWithProperties")
	defer cl.CLReleaseCommandQueue(queue)

	//-----------------------------------------------------
	// STEP 5: Create and compile the program
	//-----------------------------------------------------
	programSource, programeSize := utils.Load_programsource("svmfg.cl")

	// Create a program using clCreateProgramWithSource()
	program := cl.CLCreateProgramWithSource(context,
		1,
		programSource[:],
		programeSize[:],
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateProgramWithSource")
	defer cl.CLReleaseProgram(program)

	// Build (compile) the program for the devices with
	// clBuildProgram()
	options := "-cl-std=CL2.0"

	status = cl.CLBuildProgram(program,
		numDevices,
		devices,
		[]byte(options),
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		var log interface{}
		var log_size cl.CL_size_t
		/* Find size of log and print to std output */
		cl.CLGetProgramBuildInfo(program, devices[0], cl.CL_PROGRAM_BUILD_LOG, 0, nil, &log_size)
		cl.CLGetProgramBuildInfo(program, devices[0], cl.CL_PROGRAM_BUILD_LOG, log_size, &log, nil)
		fmt.Printf("%s\n", log)
		return
	}
	//utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLBuildProgram")

	//-----------------------------------------------------
	// STEP 7: Create the kernel
	//-----------------------------------------------------
	// Use clCreateKernel() to create a kernel
	kernel := cl.CLCreateKernel(program,
		[]byte("svmbasic"),
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateKernel")
	defer cl.CLReleaseKernel(kernel)

	// Then call the main sample routine - resource allocations, OpenCL kernel
	// execution, and so on.
	svmbasic(1024*1024, context, queue, kernel)

	// All resource deallocations happen in defer.
}
Beispiel #3
0
Datei: bst.go Projekt: xfong/gocl
func main() {
	// Use this to check the output of each API call
	var status cl.CL_int

	//-----------------------------------------------------
	// STEP 1: Discover and initialize the platforms
	//-----------------------------------------------------
	var numPlatforms cl.CL_uint
	var platforms []cl.CL_platform_id

	// Use clGetPlatformIDs() to retrieve the number of
	// platforms
	status = cl.CLGetPlatformIDs(0, nil, &numPlatforms)

	// Allocate enough space for each platform
	platforms = make([]cl.CL_platform_id, numPlatforms)

	// Fill in platforms with clGetPlatformIDs()
	status = cl.CLGetPlatformIDs(numPlatforms, platforms, nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetPlatformIDs")

	//-----------------------------------------------------
	// STEP 2: Discover and initialize the GPU devices
	//-----------------------------------------------------
	var numDevices cl.CL_uint
	var devices []cl.CL_device_id

	// Use clGetDeviceIDs() to retrieve the number of
	// devices present
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_GPU,
		0,
		nil,
		&numDevices)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetDeviceIDs")

	// Allocate enough space for each device
	devices = make([]cl.CL_device_id, numDevices)

	// Fill in devices with clGetDeviceIDs()
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_GPU,
		numDevices,
		devices,
		nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetDeviceIDs")

	//-----------------------------------------------------
	// STEP 3: Create a context
	//-----------------------------------------------------
	var context cl.CL_context

	// Create a context using clCreateContext() and
	// associate it with the devices
	context = cl.CLCreateContext(nil,
		numDevices,
		devices,
		nil,
		nil,
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateContext")
	defer cl.CLReleaseContext(context)

	//-----------------------------------------------------
	// STEP 4: Create a command queue
	//-----------------------------------------------------
	var cmdQueue cl.CL_command_queue

	// Create a command queue using clCreateCommandQueueWithProperties(),
	// and associate it with the device you want to execute
	cmdQueue = cl.CLCreateCommandQueueWithProperties(context,
		devices[0],
		nil,
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateCommandQueueWithProperties")
	defer cl.CLReleaseCommandQueue(cmdQueue)

	//-----------------------------------------------------
	// STEP 5: Create device buffers
	//-----------------------------------------------------
	// initialize any device/SVM memory here.

	/* svm buffer for binary tree */
	svmTreeBuf := cl.CLSVMAlloc(context,
		cl.CL_MEM_READ_WRITE,
		cl.CL_size_t(NUMBER_OF_NODES*unsafe.Sizeof(sampleNode)),
		0)
	if nil == svmTreeBuf {
		println("clSVMAlloc(svmTreeBuf) failed.")
		return
	}
	defer cl.CLSVMFree(context, svmTreeBuf)

	/* svm buffer for search keys */
	svmSearchBuf := cl.CLSVMAlloc(context,
		cl.CL_MEM_READ_WRITE,
		cl.CL_size_t(NUMBER_OF_SEARCH_KEY*unsafe.Sizeof(sampleKey)),
		0)
	if nil == svmSearchBuf {
		println("clSVMAlloc(svmSearchBuf) failed.")
		return
	}
	defer cl.CLSVMFree(context, svmSearchBuf)

	//create the binary tree and set the root
	/* root node of the binary tree */
	svmRoot := cpuCreateBinaryTree(cmdQueue, svmTreeBuf)

	//initialize search keys
	cpuInitSearchKeys(cmdQueue, svmSearchBuf)

	/* if voice is not deliberately muzzled, shout parameters */
	fmt.Printf("-------------------------------------------------------------------------\n")
	fmt.Printf("Searching %d keys in a BST having %d Nodes...\n", NUMBER_OF_SEARCH_KEY, NUMBER_OF_NODES)
	fmt.Printf("-------------------------------------------------------------------------\n")

	//-----------------------------------------------------
	// STEP 6: Create and compile the program
	//-----------------------------------------------------
	programSource, programeSize := utils.Load_programsource("bst.cl")

	// Create a program using clCreateProgramWithSource()
	program := cl.CLCreateProgramWithSource(context,
		1,
		programSource[:],
		programeSize[:],
		&status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateProgramWithSource")
	defer cl.CLReleaseProgram(program)

	// Build (compile) the program for the devices with
	// clBuildProgram()
	options := "-cl-std=CL2.0"
	status = cl.CLBuildProgram(program,
		numDevices,
		devices,
		[]byte(options),
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		var program_log interface{}
		var log_size cl.CL_size_t

		/* Find size of log and print to std output */
		cl.CLGetProgramBuildInfo(program, devices[0], cl.CL_PROGRAM_BUILD_LOG,
			0, nil, &log_size)
		cl.CLGetProgramBuildInfo(program, devices[0], cl.CL_PROGRAM_BUILD_LOG,
			log_size, &program_log, nil)
		fmt.Printf("%s\n", program_log)
		return
	}
	//utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLBuildProgram")

	//-----------------------------------------------------
	// STEP 7: Create the kernel
	//-----------------------------------------------------
	var kernel cl.CL_kernel

	// Use clCreateKernel() to create a kernel
	kernel = cl.CLCreateKernel(program, []byte("bst_kernel"), &status)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLCreateKernel")
	defer cl.CLReleaseKernel(kernel)

	//-----------------------------------------------------
	// STEP 8: Set the kernel arguments
	//-----------------------------------------------------
	// Associate the input and output buffers with the
	// kernel
	// using clSetKernelArg()
	// Set appropriate arguments to the kernel
	status = cl.CLSetKernelArgSVMPointer(kernel,
		0,
		svmTreeBuf)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArgSVMPointer(svmTreeBuf)")

	status = cl.CLSetKernelArgSVMPointer(kernel,
		1,
		svmSearchBuf)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clSetKernelArgSVMPointer(svmSearchBuf)")

	//-----------------------------------------------------
	// STEP 9: Configure the work-item structure
	//-----------------------------------------------------
	// Define an index space (global work size) of work
	// items for
	// execution. A workgroup size (local work size) is not
	// required,
	// but can be used.
	var localWorkSize [1]cl.CL_size_t
	var kernelWorkGroupSize interface{}
	status = cl.CLGetKernelWorkGroupInfo(kernel,
		devices[0],
		cl.CL_KERNEL_WORK_GROUP_SIZE,
		cl.CL_size_t(unsafe.Sizeof(localWorkSize[0])),
		&kernelWorkGroupSize,
		nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLGetKernelWorkGroupInfo")
	localWorkSize[0] = kernelWorkGroupSize.(cl.CL_size_t)

	var globalWorkSize [1]cl.CL_size_t
	globalWorkSize[0] = NUMBER_OF_SEARCH_KEY

	//-----------------------------------------------------
	// STEP 10: Enqueue the kernel for execution
	//-----------------------------------------------------
	// Execute the kernel by using
	// clEnqueueNDRangeKernel().
	// 'globalWorkSize' is the 1D dimension of the
	// work-items
	status = cl.CLEnqueueNDRangeKernel(cmdQueue,
		kernel,
		1,
		nil,
		globalWorkSize[:],
		localWorkSize[:],
		0,
		nil,
		nil)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "CLEnqueueNDRangeKernel")

	status = cl.CLFlush(cmdQueue)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clFlush")

	status = cl.CLFinish(cmdQueue)
	utils.CHECK_STATUS(status, cl.CL_SUCCESS, "clFinish")

	//-----------------------------------------------------
	// STEP 11: Read the output buffer back to the host
	//-----------------------------------------------------
	// Use clEnqueueReadBuffer() to read the OpenCL output
	// buffer (bufferC)
	// to the host output array (C)
	//copy the data back to host buffer

	//this demo doesn't need clEnqueueReadBuffer due to SVM

	//-----------------------------------------------------
	// STEP 12: Verify the results
	//-----------------------------------------------------
	// reference implementation
	svmBinaryTreeCPUReference(cmdQueue,
		svmRoot,
		svmTreeBuf,
		svmSearchBuf)

	// compare the results and see if they match
	pass := svmCompareResults(cmdQueue, svmSearchBuf)
	if pass {
		println("Passed!")
	} else {
		println("Failed!")
	}
}
Beispiel #4
0
func main() {
	// This code executes on the OpenCL host

	// Host data
	var size cl.CL_int
	var A []cl.CL_int //input array
	var B []cl.CL_int //input array
	var C []cl.CL_int //output array

	// Elements in each array
	const elements = cl.CL_size_t(2048)

	// Compute the size of the data
	datasize := cl.CL_size_t(unsafe.Sizeof(size)) * elements

	// Allocate space for input/output data
	A = make([]cl.CL_int, datasize)
	B = make([]cl.CL_int, datasize)
	C = make([]cl.CL_int, datasize)
	// Initialize the input data
	for i := cl.CL_int(0); i < cl.CL_int(elements); i++ {
		A[i] = i
		B[i] = i
	}

	// Use this to check the output of each API call
	var status cl.CL_int

	//-----------------------------------------------------
	// STEP 1: Discover and initialize the platforms
	//-----------------------------------------------------

	var numPlatforms cl.CL_uint
	var platforms []cl.CL_platform_id

	// Use clGetPlatformIDs() to retrieve the number of
	// platforms
	status = cl.CLGetPlatformIDs(0, nil, &numPlatforms)

	// Allocate enough space for each platform
	platforms = make([]cl.CL_platform_id, numPlatforms)

	// Fill in platforms with clGetPlatformIDs()
	status = cl.CLGetPlatformIDs(numPlatforms, platforms, nil)
	if status != cl.CL_SUCCESS {
		println("CLGetPlatformIDs status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 2: Discover and initialize the devices
	//-----------------------------------------------------

	var numDevices cl.CL_uint
	var devices []cl.CL_device_id

	// Use clGetDeviceIDs() to retrieve the number of
	// devices present
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_ALL,
		0,
		nil,
		&numDevices)
	if status != cl.CL_SUCCESS {
		println("CLGetDeviceIDs status!=cl.CL_SUCCESS")
		return
	}

	// Allocate enough space for each device
	devices = make([]cl.CL_device_id, numDevices)

	// Fill in devices with clGetDeviceIDs()
	status = cl.CLGetDeviceIDs(platforms[0],
		cl.CL_DEVICE_TYPE_ALL,
		numDevices,
		devices,
		nil)
	if status != cl.CL_SUCCESS {
		println("CLGetDeviceIDs status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 3: Create a context
	//-----------------------------------------------------

	var context cl.CL_context

	// Create a context using clCreateContext() and
	// associate it with the devices
	context = cl.CLCreateContext(nil,
		numDevices,
		devices,
		nil,
		nil,
		&status)
	if status != cl.CL_SUCCESS {
		println("CLCreateContext status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 4: Create a command queue
	//-----------------------------------------------------

	var cmdQueue cl.CL_command_queue

	// Create a command queue using clCreateCommandQueue(),
	// and associate it with the device you want to execute
	// on
	cmdQueue = cl.CLCreateCommandQueue(context,
		devices[0],
		0,
		&status)
	if status != cl.CL_SUCCESS {
		println("CLCreateCommandQueue status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 5: Create device buffers
	//-----------------------------------------------------

	var bufferA cl.CL_mem // Input array on the device
	var bufferB cl.CL_mem // Input array on the device
	var bufferC cl.CL_mem // Output array on the device

	// Use clCreateBuffer() to create a buffer object (d_A)
	// that will contain the data from the host array A
	bufferA = cl.CLCreateBuffer(context,
		cl.CL_MEM_READ_ONLY,
		datasize,
		nil,
		&status)
	if status != cl.CL_SUCCESS {
		println("CLCreateBuffer status!=cl.CL_SUCCESS")
		return
	}
	// Use clCreateBuffer() to create a buffer object (d_B)
	// that will contain the data from the host array B
	bufferB = cl.CLCreateBuffer(context,
		cl.CL_MEM_READ_ONLY,
		datasize,
		nil,
		&status)
	if status != cl.CL_SUCCESS {
		println("CLCreateBuffer status!=cl.CL_SUCCESS")
		return
	}
	// Use clCreateBuffer() to create a buffer object (d_C)
	// with enough space to hold the output data
	bufferC = cl.CLCreateBuffer(context,
		cl.CL_MEM_WRITE_ONLY,
		datasize,
		nil,
		&status)
	if status != cl.CL_SUCCESS {
		println("CLCreateBuffer status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 6: Write host data to device buffers
	//-----------------------------------------------------

	// Use clEnqueueWriteBuffer() to write input array A to
	// the device buffer bufferA
	status = cl.CLEnqueueWriteBuffer(cmdQueue,
		bufferA,
		cl.CL_FALSE,
		0,
		datasize,
		unsafe.Pointer(&A[0]),
		0,
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		println("CLEnqueueWriteBuffer status!=cl.CL_SUCCESS")
		return
	}
	// Use clEnqueueWriteBuffer() to write input array B to
	// the device buffer bufferB
	status = cl.CLEnqueueWriteBuffer(cmdQueue,
		bufferB,
		cl.CL_FALSE,
		0,
		datasize,
		unsafe.Pointer(&B[0]),
		0,
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		println("CLEnqueueWriteBuffer status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 7: Create and compile the program
	//-----------------------------------------------------
	programSource, programeSize := utils.Load_programsource("chapter2.cl")

	// Create a program using clCreateProgramWithSource()
	program := cl.CLCreateProgramWithSource(context,
		1,
		programSource[:],
		programeSize[:],
		&status)
	if status != cl.CL_SUCCESS {
		println("CLCreateProgramWithSource status!=cl.CL_SUCCESS")
		return
	}
	// Build (compile) the program for the devices with
	// clBuildProgram()
	status = cl.CLBuildProgram(program,
		numDevices,
		devices,
		nil,
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		println("CLBuildProgram status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 8: Create the kernel
	//-----------------------------------------------------

	var kernel cl.CL_kernel

	// Use clCreateKernel() to create a kernel from the
	// vector addition function (named "vecadd")
	kernel = cl.CLCreateKernel(program, []byte("vecadd"), &status)
	if status != cl.CL_SUCCESS {
		println("CLCreateKernel status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 9: Set the kernel arguments
	//-----------------------------------------------------

	// Associate the input and output buffers with the
	// kernel
	// using clSetKernelArg()
	status = cl.CLSetKernelArg(kernel,
		0,
		cl.CL_size_t(unsafe.Sizeof(bufferA)),
		unsafe.Pointer(&bufferA))
	status |= cl.CLSetKernelArg(kernel,
		1,
		cl.CL_size_t(unsafe.Sizeof(bufferB)),
		unsafe.Pointer(&bufferB))
	status |= cl.CLSetKernelArg(kernel,
		2,
		cl.CL_size_t(unsafe.Sizeof(bufferC)),
		unsafe.Pointer(&bufferC))
	if status != cl.CL_SUCCESS {
		println("CLSetKernelArg status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 10: Configure the work-item structure
	//-----------------------------------------------------

	// Define an index space (global work size) of work
	// items for
	// execution. A workgroup size (local work size) is not
	// required,
	// but can be used.
	var globalWorkSize [1]cl.CL_size_t
	// There are 'elements' work-items
	globalWorkSize[0] = elements

	//-----------------------------------------------------
	// STEP 11: Enqueue the kernel for execution
	//-----------------------------------------------------

	// Execute the kernel by using
	// clEnqueueNDRangeKernel().
	// 'globalWorkSize' is the 1D dimension of the
	// work-items
	status = cl.CLEnqueueNDRangeKernel(cmdQueue,
		kernel,
		1,
		nil,
		globalWorkSize[:],
		nil,
		0,
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		println("CLEnqueueNDRangeKernel status!=cl.CL_SUCCESS")
		return
	}
	//-----------------------------------------------------
	// STEP 12: Read the output buffer back to the host
	//-----------------------------------------------------

	// Use clEnqueueReadBuffer() to read the OpenCL output
	// buffer (bufferC)
	// to the host output array (C)
	cl.CLEnqueueReadBuffer(cmdQueue,
		bufferC,
		cl.CL_TRUE,
		0,
		datasize,
		unsafe.Pointer(&C[0]),
		0,
		nil,
		nil)
	if status != cl.CL_SUCCESS {
		println("CLEnqueueReadBuffer status!=cl.CL_SUCCESS")
		return
	}
	// Verify the output
	result := true
	for i := cl.CL_int(0); i < cl.CL_int(elements); i++ {
		if C[i] != i+i {
			result = false
			break
		}
	}
	if result {
		println("Output is correct\n")
	} else {
		println("Output is incorrect\n")
	}

	//-----------------------------------------------------
	// STEP 13: Release OpenCL resources
	//-----------------------------------------------------

	// Free OpenCL resources
	cl.CLReleaseKernel(kernel)
	cl.CLReleaseProgram(program)
	cl.CLReleaseCommandQueue(cmdQueue)
	cl.CLReleaseMemObject(bufferA)
	cl.CLReleaseMemObject(bufferB)
	cl.CLReleaseMemObject(bufferC)
	cl.CLReleaseContext(context)
}