func (this *kernel) EnqueueNDRange(queue CommandQueue,
work_dim cl.CL_uint,
global_work_offset []cl.CL_size_t,
global_work_size []cl.CL_size_t,
local_work_size []cl.CL_size_t,
event_wait_list []Event) (Event, error) {
var errCode cl.CL_int
var event_id cl.CL_event
numEvents := cl.CL_uint(len(event_wait_list))
var events []cl.CL_event
if numEvents > 0 {
events = make([]cl.CL_event, numEvents)
for i := cl.CL_uint(0); i < numEvents; i++ {
events[i] = event_wait_list[i].GetID()
}
}
if errCode = cl.CLEnqueueNDRangeKernel(queue.GetID(),
this.kernel_id,
work_dim,
global_work_offset,
global_work_size,
local_work_size,
numEvents,
events,
&event_id); errCode != cl.CL_SUCCESS {
return nil, fmt.Errorf("EnqueueNDRange failure with errcode_ret %d: %s", errCode, cl.ERROR_CODES_STRINGS[-errCode])
} else {
return &event{event_id}, nil
}
}
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!")
}
}
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!")
}
func TestMatvec(t *testing.T) {
/* Host/device data structures */
var platform [1]cl.CL_platform_id
var device [1]cl.CL_device_id
var context cl.CL_context
var queue cl.CL_command_queue
var i, err cl.CL_int
/* Program/kernel data structures */
var program cl.CL_program
var program_buffer [1][]byte
var program_log interface{}
var program_size [1]cl.CL_size_t
var log_size cl.CL_size_t
var kernel cl.CL_kernel
/* Data and buffers */
var mat [16]float32
var vec, result [4]float32
var correct = [4]float32{0.0, 0.0, 0.0, 0.0}
var mat_buff, vec_buff, res_buff cl.CL_mem
/* Initialize data to be processed by the kernel */
for i = 0; i < 16; i++ {
mat[i] = float32(i) * 2.0
}
for i = 0; i < 4; i++ {
vec[i] = float32(i) * 3.0
correct[0] += mat[i] * vec[i]
correct[1] += mat[i+4] * vec[i]
correct[2] += mat[i+8] * vec[i]
correct[3] += mat[i+12] * vec[i]
}
/* Identify a platform */
err = cl.CLGetPlatformIDs(1, platform[:], nil)
if err < 0 {
t.Errorf("Couldn't find any platforms")
}
/* Access a device */
err = cl.CLGetDeviceIDs(platform[0], cl.CL_DEVICE_TYPE_GPU, 1, device[:], nil)
if err < 0 {
err = cl.CLGetDeviceIDs(platform[0], cl.CL_DEVICE_TYPE_CPU, 1, device[:], nil)
if err < 0 {
t.Errorf("Couldn't find any devices")
}
}
/* Create the context */
context = cl.CLCreateContext(nil, 1, device[:], nil, nil, &err)
if err < 0 {
t.Errorf("Couldn't create a context")
}
/* Read program file and place content into buffer */
program_handle, err1 := os.Open("matvec.cl")
if err1 != nil {
t.Errorf("Couldn't find the program file")
}
defer program_handle.Close()
fi, err2 := program_handle.Stat()
if err2 != nil {
t.Errorf("Couldn't find the program stat")
}
program_size[0] = cl.CL_size_t(fi.Size())
program_buffer[0] = make([]byte, program_size[0])
read_size, err3 := program_handle.Read(program_buffer[0])
if err3 != nil || cl.CL_size_t(read_size) != program_size[0] {
t.Errorf("read file error or file size wrong")
}
/* Create a program containing all program content */
program = cl.CLCreateProgramWithSource(context, 1,
program_buffer[:], program_size[:], &err)
if err < 0 {
t.Errorf("Couldn't create the program")
}
/* Build program */
err = cl.CLBuildProgram(program, 1, device[:], nil, nil, nil)
if err < 0 {
/* Find size of log and print to std output */
cl.CLGetProgramBuildInfo(program, device[0], cl.CL_PROGRAM_BUILD_LOG,
0, nil, &log_size)
//program_log = (char*) malloc(log_size+1);
//program_log[log_size] = '\0';
cl.CLGetProgramBuildInfo(program, device[0], cl.CL_PROGRAM_BUILD_LOG,
log_size, &program_log, nil)
t.Errorf("%s\n", program_log)
//free(program_log);
}
/* Create kernel for the mat_vec_mult function */
kernel = cl.CLCreateKernel(program, []byte("matvec_mult"), &err)
if err < 0 {
t.Errorf("Couldn't create the kernel")
return
}
/* Create CL buffers to hold input and output data */
mat_buff = cl.CLCreateBuffer(context, cl.CL_MEM_READ_ONLY|
cl.CL_MEM_COPY_HOST_PTR, cl.CL_size_t(unsafe.Sizeof(mat)), unsafe.Pointer(&mat[0]), &err)
if err < 0 {
t.Errorf("Couldn't create a buffer object")
return
}
vec_buff = cl.CLCreateBuffer(context, cl.CL_MEM_READ_ONLY|
cl.CL_MEM_COPY_HOST_PTR, cl.CL_size_t(unsafe.Sizeof(vec)), unsafe.Pointer(&vec[0]), nil)
res_buff = cl.CLCreateBuffer(context, cl.CL_MEM_WRITE_ONLY,
cl.CL_size_t(unsafe.Sizeof(result)), nil, nil)
/* Create kernel arguments from the CL buffers */
err = cl.CLSetKernelArg(kernel, 0, cl.CL_size_t(unsafe.Sizeof(mat_buff)), unsafe.Pointer(&mat_buff))
if err < 0 {
t.Errorf("Couldn't set the kernel argument")
return
}
cl.CLSetKernelArg(kernel, 1, cl.CL_size_t(unsafe.Sizeof(vec_buff)), unsafe.Pointer(&vec_buff))
cl.CLSetKernelArg(kernel, 2, cl.CL_size_t(unsafe.Sizeof(res_buff)), unsafe.Pointer(&res_buff))
/* Create a CL command queue for the device*/
queue = cl.CLCreateCommandQueue(context, device[0], 0, &err)
if err < 0 {
t.Errorf("Couldn't create the command queue, errcode=%d\n", err)
return
}
/* Enqueue the command queue to the device */
var work_units_per_kernel = [1]cl.CL_size_t{4} /* 4 work-units per kernel */
err = cl.CLEnqueueNDRangeKernel(queue, kernel, 1, nil, work_units_per_kernel[:],
nil, 0, nil, nil)
if err < 0 {
t.Errorf("Couldn't enqueue the kernel execution command, errcode=%d\n", err)
return
}
/* Read the result */
err = cl.CLEnqueueReadBuffer(queue, res_buff, cl.CL_TRUE, 0, cl.CL_size_t(unsafe.Sizeof(result)),
unsafe.Pointer(&result[0]), 0, nil, nil)
if err < 0 {
t.Errorf("Couldn't enqueue the read buffer command")
return
}
/* Test the result */
if (result[0] == correct[0]) && (result[1] == correct[1]) &&
(result[2] == correct[2]) && (result[3] == correct[3]) {
t.Logf("Matrix-vector multiplication successful.")
} else {
t.Errorf("Matrix-vector multiplication unsuccessful.")
}
/* Deallocate resources */
cl.CLReleaseMemObject(mat_buff)
cl.CLReleaseMemObject(vec_buff)
cl.CLReleaseMemObject(res_buff)
cl.CLReleaseKernel(kernel)
cl.CLReleaseCommandQueue(queue)
cl.CLReleaseProgram(program)
cl.CLReleaseContext(context)
}
func svmbasic(size cl.CL_size_t,
context cl.CL_context,
queue cl.CL_command_queue,
kernel cl.CL_kernel) {
// Prepare input data as follows.
// Build two arrays:
// - an array that consists of the Element structures
// (refer to svmbasic.h for the structure definition)
// - an array that consists of the float values
//
// Each structure of the first array has the following pointers:
// - 'internal', which points to a 'value' field of another entry
// of the same array.
// - 'external', which points to a float value from the the
// second array.
//
// Pointers are set randomly. The structures do not reflect any real usage
// scenario, but are illustrative for a simple device-side traversal.
//
// Array of Element Array of floats
// structures
//
// ||====================||
// || ............. || ||============||
// || ............. ||<-----+ || .......... ||
// ||====================|| | || float ||
// || float* internal--||------+ || float ||
// || float* external--||------------------>|| float ||
// || float value <----||------+ || .......... ||
// ||====================|| | || .......... ||
// || ............. || | || float ||
// || ............. || | || float ||
// ||====================|| | || float ||
// ||====================|| | || float ||
// || float* internal--||------+ || float ||
// || float* external--||------------------>|| float ||
// || float value || || float ||
// ||====================|| || float ||
// || ............. || || .......... ||
// || ............. || ||============||
// ||====================||
//
// The two arrays are created independently and are used to illustrate
// two new OpenCL 2.0 API functions:
// - the array of Element structures is passed to the kernel as a
// kernel argument with the clSetKernelArgSVMPointer function
// - the array of floats is used by the kernel indirectly, and this
// dependency should be also specified with the clSetKernelExecInfo
// function prior to the kernel execution
var err cl.CL_int
// To enable host & device code to share pointer to the same address space
// the arrays should be allocated as SVM memory. Use the clSVMAlloc function
// to allocate SVM memory.
//
// Optionally, this function allows specifying alignment in bytes as its
// last argument. As this basic example doesn't require any _special_ alignment,
// the following code illustrates requesting default alignment via passing
// zero value.
inputElements := cl.CLSVMAlloc(context, // the context where this memory is supposed to be used
cl.CL_MEM_READ_ONLY|cl.CL_MEM_SVM_FINE_GRAIN_BUFFER,
size*cl.CL_size_t(unsafe.Sizeof(sampleElement)), // amount of memory to allocate (in bytes)
0) // alignment in bytes (0 means default)
if nil == inputElements {
println("Cannot allocate SVM memory with clSVMAlloc: it returns null pointer. You might be out of memory.")
return
}
defer cl.CLSVMFree(context, inputElements)
inputFloats := cl.CLSVMAlloc(context, // the context where this memory is supposed to be used
cl.CL_MEM_READ_ONLY|cl.CL_MEM_SVM_FINE_GRAIN_BUFFER,
size*cl.CL_size_t(unsafe.Sizeof(sampleFloat)), // amount of memory to allocate (in bytes)
0) // alignment in bytes (0 means default)
if nil == inputFloats {
println("Cannot allocate SVM memory with clSVMAlloc: it returns null pointer. You might be out of memory.")
return
}
defer cl.CLSVMFree(context, inputFloats)
// The OpenCL kernel uses the aforementioned input arrays to compute
// values for the output array.
output := cl.CLSVMAlloc(context, // the context where this memory is supposed to be used
cl.CL_MEM_WRITE_ONLY|cl.CL_MEM_SVM_FINE_GRAIN_BUFFER,
size*cl.CL_size_t(unsafe.Sizeof(sampleFloat)), // amount of memory to allocate (in bytes)
0) // alignment in bytes (0 means default)
defer cl.CLSVMFree(context, output)
if nil == output {
println("Cannot allocate SVM memory with clSVMAlloc: it returns null pointer. You might be out of memory.")
return
}
// Note: in the coarse-grained SVM, mapping of inputElement and inputFloats is
// needed to do the following initialization. While here, in the fine-grained SVM,
// it is not necessary.
// Populate data-structures with initial data.
r := rand.New(rand.NewSource(99))
for i := cl.CL_size_t(0); i < size; i++ {
inputElement := (*Element)(unsafe.Pointer(uintptr(inputElements) + uintptr(i)*unsafe.Sizeof(sampleElement)))
inputFloat := (*cl.CL_float)(unsafe.Pointer(uintptr(inputFloats) + uintptr(i)*unsafe.Sizeof(sampleFloat)))
randElement := (*Element)(unsafe.Pointer(uintptr(inputElements) + uintptr(r.Intn(int(size)))*unsafe.Sizeof(sampleElement)))
randFloat := (*cl.CL_float)(unsafe.Pointer(uintptr(inputFloats) + uintptr(r.Intn(int(size)))*unsafe.Sizeof(sampleFloat)))
inputElement.internal = &(randElement.value)
inputElement.external = randFloat
inputElement.value = cl.CL_float(i)
*inputFloat = cl.CL_float(i + size)
}
// Note: in the coarse-grained SVM, unmapping of inputElement and inputFloats is
// needed before scheduling the kernel for execution. While here, in the fine-grained SVM,
// it is not necessary.
// Pass arguments to the kernel.
// According to the OpenCL 2.0 specification, you need to use a special
// function to pass a pointer from SVM memory to kernel.
err = cl.CLSetKernelArgSVMPointer(kernel, 0, inputElements)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLSetKernelArgSVMPointer")
err = cl.CLSetKernelArgSVMPointer(kernel, 1, output)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLSetKernelArgSVMPointer")
// For buffer based SVM (both coarse- and fine-grain) if one SVM buffer
// points to memory allocated in another SVM buffer, such allocations
// should be passed to the kernel via clSetKernelExecInfo.
err = cl.CLSetKernelExecInfo(kernel,
cl.CL_KERNEL_EXEC_INFO_SVM_PTRS,
cl.CL_size_t(unsafe.Sizeof(inputFloats)),
unsafe.Pointer(&inputFloats))
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLSetKernelExecInfo")
// Run the kernel.
println("Running kernel...")
var globalWorkSize [1]cl.CL_size_t
globalWorkSize[0] = size
err = cl.CLEnqueueNDRangeKernel(queue,
kernel,
1,
nil,
globalWorkSize[:],
nil,
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueNDRangeKernel")
// Note: In the fine-grained SVM, after enqueuing the kernel above, the host application is
// not blocked from accessing SVM allocations that were passed to the kernel. The host
// can access the same regions of SVM memory as does the kernel if the kernel and the host
// read/modify different bytes. If one side (host or device) needs to modify the same bytes
// that are simultaniously read/modified by another side, atomics operations are usually
// required to maintain sufficient memory consistency. This sample doesn't use this possibility
// and the host just waits in clFinish below until the kernel is finished.
err = cl.CLFinish(queue)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLFinish")
println(" DONE.")
// Validate output state for correctness.
// Compare: in the coarse-grained SVM case you need to map the output.
// Here it is not needed.
println("Checking correctness of the output buffer...")
for i := cl.CL_size_t(0); i < size; i++ {
inputElement := (*Element)(unsafe.Pointer(uintptr(inputElements) + uintptr(i)*unsafe.Sizeof(sampleElement)))
outputFloat := (*cl.CL_float)(unsafe.Pointer(uintptr(output) + uintptr(i)*unsafe.Sizeof(sampleFloat)))
expectedValue := *(inputElement.internal) + *(inputElement.external)
if *outputFloat != expectedValue {
println(" FAILED.")
fmt.Printf("Mismatch at position %d, read %f, expected %f\n", i, *outputFloat, expectedValue)
return
}
}
println(" PASSED.")
}
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)
}
func main() {
var i, j cl.CL_size_t
// Rows and columns in the input image
inputFile := "test.png"
outputFile := "output.png"
refFile := "ref.png"
// Homegrown function to read a BMP from file
inputpixels, imageWidth, imageHeight, err1 := utils.Read_image_data(inputFile)
if err1 != nil {
log.Fatal(err1)
return
} else {
fmt.Printf("width=%d, height=%d (%d)\n", imageWidth, imageHeight, inputpixels[0])
}
// Output image on the host
outputpixels := make([]uint16, imageHeight*imageWidth)
inputImage := make([]float32, imageHeight*imageWidth)
outputImage := make([]float32, imageHeight*imageWidth)
refImage := make([]float32, imageHeight*imageWidth)
for i = 0; i < imageHeight*imageWidth; i++ {
inputImage[i] = float32(inputpixels[i])
}
// 45 degree motion blur
var filter = [49]float32{0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0,
0, 0, -1, 0, 1, 0, 0,
0, 0, -2, 0, 2, 0, 0,
0, 0, -1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0}
// The convolution filter is 7x7
filterWidth := cl.CL_size_t(7)
filterSize := cl.CL_size_t(filterWidth * filterWidth) // Assume a square kernel
// Set up the OpenCL environment
var status cl.CL_int
// Discovery platform
var platform [1]cl.CL_platform_id
status = cl.CLGetPlatformIDs(1, platform[:], nil)
chk(status, "clGetPlatformIDs")
// Discover device
var device [1]cl.CL_device_id
cl.CLGetDeviceIDs(platform[0], cl.CL_DEVICE_TYPE_ALL, 1, device[:], nil)
chk(status, "clGetDeviceIDs")
// Create context
//var props =[3]cl.CL_context_properties{cl.CL_CONTEXT_PLATFORM,
// (cl.CL_context_properties)(unsafe.Pointer(&platform[0])), 0};
var context cl.CL_context
context = cl.CLCreateContext(nil, 1, device[:], nil, nil, &status)
chk(status, "clCreateContext")
// Create command queue
var queue cl.CL_command_queue
queue = cl.CLCreateCommandQueue(context, device[0], 0, &status)
chk(status, "clCreateCommandQueue")
// The image format describes how the data will be stored in memory
var format cl.CL_image_format
format.Image_channel_order = cl.CL_R // single channel
format.Image_channel_data_type = cl.CL_FLOAT // float data type
var desc cl.CL_image_desc
desc.Image_type = cl.CL_MEM_OBJECT_IMAGE2D
desc.Image_width = imageWidth
desc.Image_height = imageHeight
desc.Image_depth = 0
desc.Image_array_size = 0
desc.Image_row_pitch = 0
desc.Image_slice_pitch = 0
desc.Num_mip_levels = 0
desc.Num_samples = 0
desc.Buffer = cl.CL_mem{}
// Create space for the source image on the device
d_inputImage := cl.CLCreateImage(context, cl.CL_MEM_READ_ONLY, &format, &desc,
nil, &status)
chk(status, "clCreateImage")
// Create space for the output image on the device
d_outputImage := cl.CLCreateImage(context, cl.CL_MEM_WRITE_ONLY, &format, &desc,
nil, &status)
chk(status, "clCreateImage")
// Create space for the 7x7 filter on the device
d_filter := cl.CLCreateBuffer(context, 0, filterSize*cl.CL_size_t(unsafe.Sizeof(filter[0])),
nil, &status)
chk(status, "clCreateBuffer")
// Copy the source image to the device
var origin = [3]cl.CL_size_t{0, 0, 0} // Offset within the image to copy from
var region = [3]cl.CL_size_t{cl.CL_size_t(imageWidth), cl.CL_size_t(imageHeight), 1} // Elements to per dimension
status = cl.CLEnqueueWriteImage(queue, d_inputImage, cl.CL_FALSE, origin, region,
0, 0, unsafe.Pointer(&inputImage[0]), 0, nil, nil)
chk(status, "clEnqueueWriteImage")
// Copy the 7x7 filter to the device
status = cl.CLEnqueueWriteBuffer(queue, d_filter, cl.CL_FALSE, 0,
filterSize*cl.CL_size_t(unsafe.Sizeof(filter[0])), unsafe.Pointer(&filter[0]), 0, nil, nil)
chk(status, "clEnqueueWriteBuffer")
// Create the image sampler
sampler := cl.CLCreateSampler(context, cl.CL_FALSE,
cl.CL_ADDRESS_CLAMP_TO_EDGE, cl.CL_FILTER_NEAREST, &status)
chk(status, "clCreateSampler")
// Create a program object with source and build it
program := utils.Build_program(context, device[:], "convolution.cl", nil)
kernel := cl.CLCreateKernel(*program, []byte("convolution"), &status)
chk(status, "clCreateKernel")
// Set the kernel arguments
var w, h, f cl.CL_int
w = cl.CL_int(imageWidth)
h = cl.CL_int(imageHeight)
f = cl.CL_int(filterWidth)
status = cl.CLSetKernelArg(kernel, 0, cl.CL_size_t(unsafe.Sizeof(d_inputImage)), unsafe.Pointer(&d_inputImage))
status |= cl.CLSetKernelArg(kernel, 1, cl.CL_size_t(unsafe.Sizeof(d_outputImage)), unsafe.Pointer(&d_outputImage))
status |= cl.CLSetKernelArg(kernel, 2, cl.CL_size_t(unsafe.Sizeof(h)), unsafe.Pointer(&h))
status |= cl.CLSetKernelArg(kernel, 3, cl.CL_size_t(unsafe.Sizeof(w)), unsafe.Pointer(&w))
status |= cl.CLSetKernelArg(kernel, 4, cl.CL_size_t(unsafe.Sizeof(d_filter)), unsafe.Pointer(&d_filter))
status |= cl.CLSetKernelArg(kernel, 5, cl.CL_size_t(unsafe.Sizeof(f)), unsafe.Pointer(&f))
status |= cl.CLSetKernelArg(kernel, 6, cl.CL_size_t(unsafe.Sizeof(sampler)), unsafe.Pointer(&sampler))
chk(status, "clSetKernelArg")
// Set the work item dimensions
var globalSize = [2]cl.CL_size_t{imageWidth, imageHeight}
status = cl.CLEnqueueNDRangeKernel(queue, kernel, 2, nil, globalSize[:], nil, 0,
nil, nil)
chk(status, "clEnqueueNDRange")
// Read the image back to the host
status = cl.CLEnqueueReadImage(queue, d_outputImage, cl.CL_TRUE, origin,
region, 0, 0, unsafe.Pointer(&outputImage[0]), 0, nil, nil)
chk(status, "clEnqueueReadImage")
// Write the output image to file
for i = 0; i < imageHeight*imageWidth; i++ {
outputpixels[i] = uint16(outputImage[i])
}
utils.Write_image_data(outputFile, outputpixels, imageWidth, imageHeight)
// Compute the reference image
for i = 0; i < imageHeight; i++ {
for j = 0; j < imageWidth; j++ {
refImage[i*imageWidth+j] = 0
}
}
// Iterate over the rows of the source image
halfFilterWidth := filterWidth / 2
var sum float32
for i = 0; i < imageHeight; i++ {
// Iterate over the columns of the source image
for j = 0; j < imageWidth; j++ {
sum = 0 // Reset sum for new source pixel
// Apply the filter to the neighborhood
for k := -halfFilterWidth; k <= halfFilterWidth; k++ {
for l := -halfFilterWidth; l <= halfFilterWidth; l++ {
if i+k >= 0 && i+k < imageHeight &&
j+l >= 0 && j+l < imageWidth {
sum += inputImage[(i+k)*imageWidth+j+l] *
filter[(k+halfFilterWidth)*filterWidth+
l+halfFilterWidth]
} else {
i_k := i + k
j_l := j + l
if i+k < 0 {
i_k = 0
} else if i+k >= imageHeight {
i_k = imageHeight - 1
}
if j+l < 0 {
j_l = 0
} else if j+l >= imageWidth {
j_l = imageWidth - 1
}
sum += inputImage[(i_k)*imageWidth+j_l] *
filter[(k+halfFilterWidth)*filterWidth+
l+halfFilterWidth]
}
}
}
refImage[i*imageWidth+j] = sum
}
}
// Write the ref image to file
for i = 0; i < imageHeight*imageWidth; i++ {
outputpixels[i] = uint16(refImage[i])
}
utils.Write_image_data(refFile, outputpixels, imageWidth, imageHeight)
failed := 0
for i = 0; i < imageHeight; i++ {
for j = 0; j < imageWidth; j++ {
if math.Abs(float64(outputImage[i*imageWidth+j]-refImage[i*imageWidth+j])) > 0.01 {
//fmt.Printf("Results are INCORRECT\n");
//fmt.Printf("Pixel mismatch at <%d,%d> (%f vs. %f) %f\n", i, j,
// outputImage[i*imageWidth+j], refImage[i*imageWidth+j], inputImage[i*imageWidth+j]);
failed++
}
}
}
fmt.Printf("Mismatch Pixel number/Total pixel number = %d/%d\n", failed, imageWidth*imageHeight)
// Free OpenCL resources
cl.CLReleaseKernel(kernel)
cl.CLReleaseProgram(*program)
cl.CLReleaseCommandQueue(queue)
cl.CLReleaseMemObject(d_inputImage)
cl.CLReleaseMemObject(d_outputImage)
cl.CLReleaseMemObject(d_filter)
cl.CLReleaseSampler(sampler)
cl.CLReleaseContext(context)
}
func main() {
/* OpenCL data structures */
var device []cl.CL_device_id
var context cl.CL_context
var queue cl.CL_command_queue
var program *cl.CL_program
var kernel cl.CL_kernel
var err cl.CL_int
var err1 error
var global_size [2]cl.CL_size_t
/* Image data */
var pixels []uint16
var png_format cl.CL_image_format
var input_image, output_image cl.CL_mem
var origin, region [3]cl.CL_size_t
var width, height cl.CL_size_t
/* Open input file and read image data */
pixels, width, height, err1 = utils.Read_image_data(INPUT_FILE)
if err1 != nil {
return
} else {
fmt.Printf("width=%d, height=%d", width, height)
}
/* Create a device and context */
device = utils.Create_device()
context = cl.CLCreateContext(nil, 1, device[:], nil, nil, &err)
if err < 0 {
println("Couldn't create a context")
return
}
/* Build the program and create a kernel */
program = utils.Build_program(context, device[:], PROGRAM_FILE, nil)
kernel = cl.CLCreateKernel(*program, KERNEL_FUNC, &err)
if err < 0 {
fmt.Printf("Couldn't create a kernel: %d", err)
return
}
/* Create image object */
png_format.Image_channel_order = cl.CL_LUMINANCE
png_format.Image_channel_data_type = cl.CL_UNORM_INT16
input_image = cl.CLCreateImage2D(context,
cl.CL_MEM_READ_ONLY|cl.CL_MEM_COPY_HOST_PTR,
&png_format, width, height, 0, unsafe.Pointer(&pixels[0]), &err)
output_image = cl.CLCreateImage2D(context,
cl.CL_MEM_WRITE_ONLY, &png_format, width, height, 0, nil, &err)
if err < 0 {
println("Couldn't create the image object")
return
}
/* Create kernel arguments */
err = cl.CLSetKernelArg(kernel, 0, cl.CL_size_t(unsafe.Sizeof(input_image)), unsafe.Pointer(&input_image))
err |= cl.CLSetKernelArg(kernel, 1, cl.CL_size_t(unsafe.Sizeof(output_image)), unsafe.Pointer(&output_image))
if err < 0 {
println("Couldn't set a kernel argument")
return
}
/* Create a command queue */
queue = cl.CLCreateCommandQueue(context, device[0], 0, &err)
if err < 0 {
println("Couldn't create a command queue")
return
}
/* Enqueue kernel */
global_size[0] = width
global_size[1] = height
err = cl.CLEnqueueNDRangeKernel(queue, kernel, 2, nil, global_size[:],
nil, 0, nil, nil)
if err < 0 {
println("Couldn't enqueue the kernel")
return
}
/* Read the image object */
origin[0] = 0
origin[1] = 0
origin[2] = 0
region[0] = width
region[1] = height
region[2] = 1
err = cl.CLEnqueueReadImage(queue, output_image, cl.CL_TRUE, origin,
region, 0, 0, unsafe.Pointer(&pixels[0]), 0, nil, nil)
if err < 0 {
println("Couldn't read from the image object")
return
}
/* Create output PNG file and write data */
utils.Write_image_data(OUTPUT_FILE, pixels, width, height)
/* Deallocate resources */
cl.CLReleaseMemObject(input_image)
cl.CLReleaseMemObject(output_image)
cl.CLReleaseKernel(kernel)
cl.CLReleaseCommandQueue(queue)
cl.CLReleaseProgram(*program)
cl.CLReleaseContext(context)
}
func main() {
/* OpenCL data structures */
var device []cl.CL_device_id
var context cl.CL_context
var queue cl.CL_command_queue
var program *cl.CL_program
var kernel cl.CL_kernel
var err cl.CL_int
/* Data and buffers */
dim := cl.CL_uint(2)
var global_offset = [2]cl.CL_size_t{3, 5}
var global_size = [2]cl.CL_size_t{6, 4}
var local_size = [2]cl.CL_size_t{3, 2}
var test [24]float32
var test_buffer cl.CL_mem
/* Create a device and context */
device = utils.Create_device()
context = cl.CLCreateContext(nil, 1, device[:], nil, nil, &err)
if err < 0 {
println("Couldn't create a context")
return
}
/* Build the program and create a kernel */
program = utils.Build_program(context, device[:], PROGRAM_FILE, nil)
kernel = cl.CLCreateKernel(*program, KERNEL_FUNC, &err)
if err < 0 {
println("Couldn't create a kernel")
return
}
/* Create a write-only buffer to hold the output data */
test_buffer = cl.CLCreateBuffer(context, cl.CL_MEM_WRITE_ONLY,
cl.CL_size_t(unsafe.Sizeof(test)), nil, &err)
if err < 0 {
println("Couldn't create a buffer")
return
}
/* Create kernel argument */
err = cl.CLSetKernelArg(kernel, 0, cl.CL_size_t(unsafe.Sizeof(test_buffer)), unsafe.Pointer(&test_buffer))
if err < 0 {
println("Couldn't set a kernel argument")
return
}
/* Create a command queue */
queue = cl.CLCreateCommandQueue(context, device[0], 0, &err)
if err < 0 {
println("Couldn't create a command queue")
return
}
/* Enqueue kernel */
err = cl.CLEnqueueNDRangeKernel(queue, kernel, dim, global_offset[:],
global_size[:], local_size[:], 0, nil, nil)
if err < 0 {
println("Couldn't enqueue the kernel")
return
}
/* Read and print the result */
err = cl.CLEnqueueReadBuffer(queue, test_buffer, cl.CL_TRUE, 0,
cl.CL_size_t(unsafe.Sizeof(test)), unsafe.Pointer(&test), 0, nil, nil)
if err < 0 {
println("Couldn't read the buffer")
return
}
for i := 0; i < 24; i += 6 {
fmt.Printf("%.2f %.2f %.2f %.2f %.2f %.2f\n",
test[i], test[i+1], test[i+2], test[i+3], test[i+4], test[i+5])
}
/* Deallocate resources */
cl.CLReleaseMemObject(test_buffer)
cl.CLReleaseKernel(kernel)
cl.CLReleaseCommandQueue(queue)
cl.CLReleaseProgram(*program)
cl.CLReleaseContext(context)
}
func main() {
/* OpenCL data structures */
var device []cl.CL_device_id
var context cl.CL_context
var queue cl.CL_command_queue
var program *cl.CL_program
var kernel cl.CL_kernel
var err cl.CL_int
var offset, global_size, local_size [1]cl.CL_size_t
/* Data and events */
var data [2]cl.CL_int
var data_buffer cl.CL_mem
/* Create a device and context */
device = utils.Create_device()
context = cl.CLCreateContext(nil, 1, device[:], nil, nil, &err)
if err < 0 {
println("Couldn't create a context")
return
}
/* Build the program and create a kernel */
program = utils.Build_program(context, device[:], PROGRAM_FILE, nil)
kernel = cl.CLCreateKernel(*program, KERNEL_FUNC, &err)
if err < 0 {
println("Couldn't create a kernel")
return
}
/* Create a buffer to hold data */
data_buffer = cl.CLCreateBuffer(context, cl.CL_MEM_WRITE_ONLY,
cl.CL_size_t(unsafe.Sizeof(data[0]))*2, nil, &err)
if err < 0 {
println("Couldn't create a buffer")
return
}
/* Create kernel argument */
err = cl.CLSetKernelArg(kernel, 0, cl.CL_size_t(unsafe.Sizeof(data_buffer)), unsafe.Pointer(&data_buffer))
if err < 0 {
println("Couldn't set a kernel argument")
return
}
/* Create a command queue */
queue = cl.CLCreateCommandQueue(context, device[0], 0, &err)
if err < 0 {
println("Couldn't create a command queue")
return
}
/* Enqueue kernel */
offset[0] = 0
global_size[0] = 8
local_size[0] = 4
err = cl.CLEnqueueNDRangeKernel(queue, kernel, 1, offset[:], global_size[:], local_size[:], 0, nil, nil)
if err < 0 {
println("Couldn't enqueue the kernel")
return
}
/* Read the buffer */
err = cl.CLEnqueueReadBuffer(queue, data_buffer, cl.CL_TRUE, 0,
cl.CL_size_t(unsafe.Sizeof(data[0]))*2, unsafe.Pointer(&data[0]), 0, nil, nil)
if err < 0 {
println("Couldn't read the buffer")
return
}
fmt.Printf("Increment: %d\n", data[0])
fmt.Printf("Atomic increment: %d\n", data[1])
/* Deallocate resources */
cl.CLReleaseMemObject(data_buffer)
cl.CLReleaseKernel(kernel)
cl.CLReleaseCommandQueue(queue)
cl.CLReleaseProgram(*program)
cl.CLReleaseContext(context)
}
func main() {
/* OpenCL data structures */
var device []cl.CL_device_id
var context cl.CL_context
var queue cl.CL_command_queue
var program *cl.CL_program
var kernel cl.CL_kernel
var err cl.CL_int
/* Data and events */
var num_ints cl.CL_int
var num_items [1]cl.CL_size_t
var data [NUM_INTS]cl.CL_int
var data_buffer cl.CL_mem
var prof_event cl.CL_event
var total_time cl.CL_ulong
var time_start, time_end interface{}
/* Initialize data */
for i := 0; i < NUM_INTS; i++ {
data[i] = cl.CL_int(i)
}
/* Set number of data points and work-items */
num_ints = NUM_INTS
num_items[0] = NUM_ITEMS
/* Create a device and context */
device = utils.Create_device()
context = cl.CLCreateContext(nil, 1, device[:], nil, nil, &err)
if err < 0 {
println("Couldn't create a context")
return
}
/* Build the program and create a kernel */
program = utils.Build_program(context, device[:], PROGRAM_FILE, nil)
kernel = cl.CLCreateKernel(*program, KERNEL_FUNC, &err)
if err < 0 {
println("Couldn't create a kernel")
return
}
/* Create a buffer to hold data */
data_buffer = cl.CLCreateBuffer(context,
cl.CL_MEM_READ_WRITE|cl.CL_MEM_COPY_HOST_PTR,
cl.CL_size_t(unsafe.Sizeof(data[0]))*NUM_INTS, unsafe.Pointer(&data[0]), &err)
if err < 0 {
println("Couldn't create a buffer")
return
}
/* Create kernel argument */
err = cl.CLSetKernelArg(kernel, 0, cl.CL_size_t(unsafe.Sizeof(data_buffer)), unsafe.Pointer(&data_buffer))
if err < 0 {
println("Couldn't set a kernel argument")
return
}
cl.CLSetKernelArg(kernel, 1, cl.CL_size_t(unsafe.Sizeof(num_ints)), unsafe.Pointer(&num_ints))
/* Create a command queue */
queue = cl.CLCreateCommandQueue(context, device[0],
cl.CL_QUEUE_PROFILING_ENABLE, &err)
if err < 0 {
println("Couldn't create a command queue")
return
}
total_time = 0.0
for i := 0; i < NUM_ITERATIONS; i++ {
/* Enqueue kernel */
cl.CLEnqueueNDRangeKernel(queue, kernel, 1, nil, num_items[:],
nil, 0, nil, &prof_event)
if err < 0 {
println("Couldn't enqueue the kernel")
return
}
/* Finish processing the queue and get profiling information */
cl.CLFinish(queue)
cl.CLGetEventProfilingInfo(prof_event, cl.CL_PROFILING_COMMAND_START,
cl.CL_size_t(unsafe.Sizeof(total_time)), &time_start, nil)
cl.CLGetEventProfilingInfo(prof_event, cl.CL_PROFILING_COMMAND_END,
cl.CL_size_t(unsafe.Sizeof(total_time)), &time_end, nil)
total_time += time_end.(cl.CL_ulong) - time_start.(cl.CL_ulong)
}
fmt.Printf("Average time = %v\n", total_time/NUM_ITERATIONS)
/* Deallocate resources */
cl.CLReleaseEvent(prof_event)
cl.CLReleaseKernel(kernel)
cl.CLReleaseMemObject(data_buffer)
cl.CLReleaseCommandQueue(queue)
cl.CLReleaseProgram(*program)
cl.CLReleaseContext(context)
}
func svmbasic(size cl.CL_size_t,
context cl.CL_context,
queue cl.CL_command_queue,
kernel cl.CL_kernel) {
// Prepare input data as follows.
// Build two arrays:
// - an array that consists of the Element structures
// (refer to svmbasic.h for the structure definition)
// - an array that consists of the float values
//
// Each structure of the first array has the following pointers:
// - 'internal', which points to a 'value' field of another entry
// of the same array.
// - 'external', which points to a float value from the the
// second array.
//
// Pointers are set randomly. The structures do not reflect any real usage
// scenario, but are illustrative for a simple device-side traversal.
//
// Array of Element Array of floats
// structures
//
// ||====================||
// || ............. || ||============||
// || ............. ||<-----+ || .......... ||
// ||====================|| | || float ||
// || float* internal--||------+ || float ||
// || float* external--||------------------>|| float ||
// || float value <----||------+ || .......... ||
// ||====================|| | || .......... ||
// || ............. || | || float ||
// || ............. || | || float ||
// ||====================|| | || float ||
// ||====================|| | || float ||
// || float* internal--||------+ || float ||
// || float* external--||------------------>|| float ||
// || float value || || float ||
// ||====================|| || float ||
// || ............. || || .......... ||
// || ............. || ||============||
// ||====================||
//
// The two arrays are created independently and are used to illustrate
// two new OpenCL 2.0 API functions:
// - the array of Element structures is passed to the kernel as a
// kernel argument with the clSetKernelArgSVMPointer function
// - the array of floats is used by the kernel indirectly, and this
// dependency should be also specified with the clSetKernelExecInfo
// function prior to the kernel execution
var err cl.CL_int
// To enable host & device code to share pointer to the same address space
// the arrays should be allocated as SVM memory. Use the clSVMAlloc function
// to allocate SVM memory.
//
// Optionally, this function allows specifying alignment in bytes as its
// last argument. As this basic example doesn't require any _special_ alignment,
// the following code illustrates requesting default alignment via passing
// zero value.
inputElements := cl.CLSVMAlloc(context, // the context where this memory is supposed to be used
cl.CL_MEM_READ_ONLY,
size*cl.CL_size_t(unsafe.Sizeof(sampleElement)), // amount of memory to allocate (in bytes)
0) // alignment in bytes (0 means default)
if nil == inputElements {
println("Cannot allocate SVM memory with clSVMAlloc: it returns null pointer. You might be out of memory.")
return
}
defer cl.CLSVMFree(context, inputElements)
inputFloats := cl.CLSVMAlloc(context, // the context where this memory is supposed to be used
cl.CL_MEM_READ_ONLY,
size*cl.CL_size_t(unsafe.Sizeof(sampleFloat)), // amount of memory to allocate (in bytes)
0) // alignment in bytes (0 means default)
if nil == inputFloats {
println("Cannot allocate SVM memory with clSVMAlloc: it returns null pointer. You might be out of memory.")
return
}
defer cl.CLSVMFree(context, inputFloats)
// The OpenCL kernel uses the aforementioned input arrays to compute
// values for the output array.
output := cl.CLSVMAlloc(context, // the context where this memory is supposed to be used
cl.CL_MEM_WRITE_ONLY,
size*cl.CL_size_t(unsafe.Sizeof(sampleFloat)), // amount of memory to allocate (in bytes)
0) // alignment in bytes (0 means default)
defer cl.CLSVMFree(context, output)
if nil == output {
println("Cannot allocate SVM memory with clSVMAlloc: it returns null pointer. You might be out of memory.")
return
}
// In the coarse-grained buffer SVM model, only one OpenCL device (or
// host) can have ownership for writing to the buffer. Specifically, host
// explicitly requests the ownership by mapping/unmapping the SVM buffer.
//
// So to fill the input SVM buffers on the host, you need to map them to have
// access from the host program.
//
// The following two map calls are required in case of coarse-grained SVM only.
err = cl.CLEnqueueSVMMap(queue,
cl.CL_TRUE, // blocking map
cl.CL_MAP_WRITE,
inputElements,
size*cl.CL_size_t(unsafe.Sizeof(sampleElement)),
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueSVMMap")
err = cl.CLEnqueueSVMMap(queue,
cl.CL_TRUE, // blocking map
cl.CL_MAP_WRITE,
inputFloats,
size*cl.CL_size_t(unsafe.Sizeof(sampleFloat)),
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueSVMMap")
// Populate data-structures with initial data.
r := rand.New(rand.NewSource(99))
for i := cl.CL_size_t(0); i < size; i++ {
inputElement := (*Element)(unsafe.Pointer(uintptr(inputElements) + uintptr(i)*unsafe.Sizeof(sampleElement)))
inputFloat := (*cl.CL_float)(unsafe.Pointer(uintptr(inputFloats) + uintptr(i)*unsafe.Sizeof(sampleFloat)))
randElement := (*Element)(unsafe.Pointer(uintptr(inputElements) + uintptr(r.Intn(int(size)))*unsafe.Sizeof(sampleElement)))
randFloat := (*cl.CL_float)(unsafe.Pointer(uintptr(inputFloats) + uintptr(r.Intn(int(size)))*unsafe.Sizeof(sampleFloat)))
inputElement.internal = &(randElement.value)
inputElement.external = randFloat
inputElement.value = cl.CL_float(i)
*inputFloat = cl.CL_float(i + size)
}
// The following two unmap calls are required in case of coarse-grained SVM only
err = cl.CLEnqueueSVMUnmap(queue,
inputElements,
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueSVMUnmap")
err = cl.CLEnqueueSVMUnmap(queue,
inputFloats,
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueSVMUnmap")
// Pass arguments to the kernel.
// According to the OpenCL 2.0 specification, you need to use a special
// function to pass a pointer from SVM memory to kernel.
err = cl.CLSetKernelArgSVMPointer(kernel, 0, inputElements)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLSetKernelArgSVMPointer")
err = cl.CLSetKernelArgSVMPointer(kernel, 1, output)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLSetKernelArgSVMPointer")
// For buffer based SVM (both coarse- and fine-grain) if one SVM buffer
// points to memory allocated in another SVM buffer, such allocations
// should be passed to the kernel via clSetKernelExecInfo.
err = cl.CLSetKernelExecInfo(kernel,
cl.CL_KERNEL_EXEC_INFO_SVM_PTRS,
cl.CL_size_t(unsafe.Sizeof(inputFloats)),
unsafe.Pointer(&inputFloats))
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLSetKernelExecInfo")
// Run the kernel.
println("Running kernel...")
var globalWorkSize [1]cl.CL_size_t
globalWorkSize[0] = size
err = cl.CLEnqueueNDRangeKernel(queue,
kernel,
1,
nil,
globalWorkSize[:],
nil,
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueNDRangeKernel")
// Map the output SVM buffer to read the results.
// Mapping is required for coarse-grained SVM only.
err = cl.CLEnqueueSVMMap(queue,
cl.CL_TRUE, // blocking map
cl.CL_MAP_READ,
output,
size*cl.CL_size_t(unsafe.Sizeof(sampleFloat)),
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueSVMMap")
println(" DONE.")
// Validate output state for correctness.
println("Checking correctness of the output buffer...")
for i := cl.CL_size_t(0); i < size; i++ {
inputElement := (*Element)(unsafe.Pointer(uintptr(inputElements) + uintptr(i)*unsafe.Sizeof(sampleElement)))
outputFloat := (*cl.CL_float)(unsafe.Pointer(uintptr(output) + uintptr(i)*unsafe.Sizeof(sampleFloat)))
expectedValue := *(inputElement.internal) + *(inputElement.external)
if *outputFloat != expectedValue {
println(" FAILED.")
fmt.Printf("Mismatch at position %d, read %f, expected %f\n", i, *outputFloat, expectedValue)
return
}
}
println(" PASSED.")
err = cl.CLEnqueueSVMUnmap(queue,
output,
0,
nil,
nil)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLEnqueueSVMUnmap")
err = cl.CLFinish(queue)
utils.CHECK_STATUS(err, cl.CL_SUCCESS, "CLFinish")
}
