/* uniform to gaussian */
func boxMuller(u [2]cl.CL_float) [2]cl.CL_float {
var g [2]cl.CL_float
r := cl.CL_float(math.Sqrt(-2 * math.Log(float64(u[0]))))
theta := cl.CL_float(2.0 * PI * u[1])
g[0] = r * cl.CL_float(math.Sin(float64(theta)))
g[1] = r * cl.CL_float(math.Cos(float64(theta)))
return g
}
func CPUReference(seed cl.CL_int,
pipePktPerThread cl.CL_int,
rngType cl.CL_int,
cpuHist []cl.CL_int,
histMax, histMin cl.CL_float) {
var pmPRNG PM_PRNG
var irn [PRNG_CHANNELS][2]cl.CL_int
var frn [PRNG_CHANNELS][2]cl.CL_float
var grn [PRNG_CHANNELS][2]cl.CL_float
var binWidth cl.CL_float
// Initialize the prng
pmPRNG.rngInit(seed)
// Put starting values for each channel
for ch := cl.CL_int(0); ch < cl.CL_int(PRNG_CHANNELS); ch++ {
irn[ch][0] = (ch + 1) * (ch + 1)
irn[ch][1] = (ch + 1) * (ch + 1)
}
//compute binWidth
binWidth = (histMax - histMin) / cl.CL_float(MAX_HIST_BINS)
for pkt := cl.CL_int(0); pkt < pipePktPerThread; pkt++ {
// Generate random numbers
for ch := 0; ch < PRNG_CHANNELS; ch++ {
irn[ch][0] = pmPRNG.rngPM(irn[ch][1], cl.CL_int(ch))
irn[ch][1] = pmPRNG.rngPM(irn[ch][0], cl.CL_int(ch))
frn[ch][0] = cl.CL_float(irn[ch][0]) * AM
if frn[ch][0] > RMAX {
frn[ch][0] = cl.CL_float(RMAX)
}
frn[ch][1] = cl.CL_float(irn[ch][1]) * AM
if frn[ch][1] > RMAX {
frn[ch][1] = cl.CL_float(RMAX)
}
if rngType == RV_GAUSSIAN {
grn[ch] = boxMuller(frn[ch])
} else {
grn[ch] = frn[ch]
}
}
// host side histogram
for ch := 0; ch < PRNG_CHANNELS; ch++ {
rmin := histMin
rmax := rmin + binWidth
found := 0
for bindex := 0; (bindex < MAX_HIST_BINS) && (found != 2); bindex++ {
if (grn[ch][0] >= rmin) && (grn[ch][0] < rmax) {
found += 1
cpuHist[bindex] += 1
}
if (grn[ch][1] >= rmin) && (grn[ch][1] < rmax) {
found += 1
cpuHist[bindex] += 1
}
rmin = rmax
rmax = rmin + binWidth
}
}
}
}
// This program demo OpenCL 2.0 Pipe feature package main import ( "fmt" "gocl/cl" "gocl/cl_demo/utils" "unsafe" ) const ( //constants for urng IA = 16807 // a IM = 2147483647 // m AM = 1.0 / cl.CL_float(IM) // 1/m - To calculate floating point result IQ = 127773 IR = 2836 NTAB = 16 NDIV = (1 + (IM-1)/NTAB) EPS = 1.2e-7 RMAX = (1.0 - EPS) PRNG_CHANNELS = 256 MAX_NTAB = (PRNG_CHANNELS * NTAB) //mathematical constants PI = 3.14159265359 //arbitrary mask to xor with seed. required to avoid seed to rng being zero. MASK = 0x2F24EA81 )
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 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")
}
