OpenCL lets you tap into the parallel computing power of modern GPUs and multicore CPUs to accelerate compute-intensive tasks in your Mac apps.Use OpenCL to incorporate advanced numerical and data analytics features, perform cutting-edge image and media processing, and deliver accurate physics and AI simulationin games.
Reference, Guides, and Sample Code
The OpenCL CPU runtime is removed from the OpenCL driver for Windows starting in the 2020 February release version 'igfxwin10100.7870.exe'. But the installer of the new driver did not remove the old OpenCL CPU runtime when you upgrade the newer driver, so you may have two OpenCL CPU runtimes on your system. The later models with OpenCL 2.0 have been supported since version 5.08. MinerGate opens more possibilities for your hardware. Get the suitable version of our GUI miner for your system on the Downloads page. Ethereum mining for AMD cards with OpenCL 1.1. Mining of all CryptoNote coins for AMD with OpenCL 1.2.
Download - Windows (x86) Download - Windows (x64) Download - Linux/Mac OpenCL Recursive Gaussian Filter 2-dimensional Gaussian Blur Filter of RGBA image using IRF method. In OpenCL 2.0 OpenCL C is not entirely backward compatibility with earlier versions. As a result a flag must be passed to the OpenCL C compiled to request OpenCL 2.0 compilation of kernels with 1.2 as the default in the absence of the flag. In some cases the C bindings automatically compile code for ease. The OpenCL Specification Version: 1.2 Document Revision: 19 Khronos OpenCL Working Group Editor: Aaftab Munshi. Last Revision Date: 11/14/12 Page 2 1.!
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Using the OpenCL Logo
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Transitioning to Metal
If you are using OpenCL for computational tasks in your Mac app, we recommend that you transition to Metal and Metal Performance Shaders.
Learn about Metal
For many large applications C++ is the language of choice and so it seems reasonable to define C++ bindings for OpenCL.
The interface is contained with a single C++ header file cl2.hpp and all definitions are contained within the namespace cl. There is no additional requirement to include cl.h and to use either the C++ or original C bindings; it is enough to simply include cl2.hpp.
The bindings themselves are lightweight and correspond closely to the underlying C API. Using the C++ bindings introduces no additional execution overhead.
There are numerous compatibility, portability and memory management fixes in the new header as well as additional OpenCL 2.0 features. As a result the header is not directly backward compatible and for this reason we release it as cl2.hpp rather than a new version of cl.hpp.
Due to the evolution of the underlying OpenCL API the 2.0 C++ bindings include an updated approach to defining supported feature versions and the range of valid underlying OpenCL runtime versions supported.
The combination of preprocessor macros CL_HPP_TARGET_OPENCL_VERSION and CL_HPP_MINIMUM_OPENCL_VERSION control this range. These are three digit decimal values representing OpenCL runime versions. The default for the target is 200, representing OpenCL 2.0 and the minimum is also defined as 200. These settings would use 2.0 API calls only. If backward compatibility with a 1.2 runtime is required, the minimum version may be set to 120.
Note that this is a compile-time setting, and so affects linking against a particular SDK version rather than the versioning of the loaded runtime.
The earlier versions of the header included basic vector and string classes based loosely on STL versions. These were difficult to maintain and very rarely used. For the 2.0 header we now assume the presence of the standard library unless requested otherwise. We use std::array, std::vector, std::shared_ptr and std::string throughout to safely manage memory and reduce the chance of a recurrance of earlier memory management bugs.
These classes are used through typedefs in the cl namespace: cl::array, cl::vector, cl::pointer and cl::string. In addition cl::allocate_pointer forwards to std::allocate_shared by default. In all cases these standard library classes can be replaced with custom interface-compatible versions using the CL_HPP_NO_STD_ARRAY, CL_HPP_NO_STD_VECTOR, CL_HPP_NO_STD_UNIQUE_PTR and CL_HPP_NO_STD_STRING macros.
The OpenCL 1.x versions of the C++ bindings included a size_t wrapper class to interface with kernel enqueue. This caused unpleasant interactions with the standard size_t declaration and led to namespacing bugs. In the 2.0 version we have replaced this with a std::array-based interface. However, the old behaviour can be regained for backward compatibility using the CL_HPP_ENABLE_SIZE_T_COMPATIBILITY macro.
Finally, the program construction interface used a clumsy vector-of-pairs design in the earlier versions. We have replaced that with a cleaner vector-of-vectors and vector-of-strings design. However, for backward compatibility old behaviour can be regained with the CL_HPP_ENABLE_PROGRAM_CONSTRUCTION_FROM_ARRAY_COMPATIBILITY macro.
In OpenCL 2.0 OpenCL C is not entirely backward compatibility with earlier versions. As a result a flag must be passed to the OpenCL C compiled to request OpenCL 2.0 compilation of kernels with 1.2 as the default in the absence of the flag. In some cases the C++ bindings automatically compile code for ease. For those cases the compilation defaults to OpenCL C 2.0. If this is not wanted, the CL_HPP_CL_1_2_DEFAULT_BUILD macro may be specified to assume 1.2 compilation. If more fine-grained decisions on a per-kernel bases are required then explicit build operations that take the flag should be used.
This header may be parameterized by a set of preprocessor macros. Scarbee rickenbacker bass download mac.
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CL_HPP_TARGET_OPENCL_VERSIONDefines the target OpenCL runtime version to build the header against. Defaults to 200, representing OpenCL 2.0.
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CL_HPP_NO_STD_STRINGDo not use the standard library string class. cl::string is not defined and may be defined by the user before cl2.hpp is included.
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CL_HPP_NO_STD_VECTORDo not use the standard library vector class. cl::vector is not defined and may be defined by the user before cl2.hpp is included.
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CL_HPP_NO_STD_ARRAYDo not use the standard library array class. cl::array is not defined and may be defined by the user before cl2.hpp is included.
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CL_HPP_NO_STD_UNIQUE_PTRDo not use the standard library unique_ptr class. cl::pointer and the cl::allocate_pointer functions are not defined and may be defined by the user before cl2.hpp is included.
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CL_HPP_ENABLE_DEVICE_FISSION Persepolis movie download.Enables device fission for OpenCL 1.2 platforms.
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CL_HPP_ENABLE_EXCEPTIONSEnable exceptions for use in the C++ bindings header. This is the preferred error handling mechanism but is not required.
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CL_HPP_ENABLE_SIZE_T_COMPATIBILITYBackward compatibility option to support cl.hpp-style size_t class. Replaces the updated std::array derived version and removal of size_t from the namespace. Note that in this case the new size_t class is placed in the cl::compatibility namespace and thus requires an additional using declaration for direct backward compatibility.
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Cura 2.7 mac download. CL_HPP_ENABLE_PROGRAM_CONSTRUCTION_FROM_ARRAY_COMPATIBILITYDosis semibold. Enable older vector of pairs interface for construction of programs.
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CL_HPP_CL_1_2_DEFAULT_BUILDDefault to OpenCL C 1.2 compilation rather than OpenCL C 2.0 applies to use of cl::Program construction and other program build variants.
The following example shows a general use case for the C++ bindings, including support for the optional exception feature and also the supplied vector and string classes, see following sections for decriptions of these features.
#define CL_HPP_TARGET_OPENCL_VERSION 200
#include <CL/cl2.hpp>
#include <vector>
#include <algorithm>
constint numElements = 32;
int main(void)
// Filter for a 2.0 platform and set it as the default
cl::Platform::get(&platforms);
for (auto &p : platforms) {
std::string platver = p.getInfo<CL_PLATFORM_VERSION>();
if (platver.find('OpenCL 2.') != std::string::npos) {
}
if (plat() 0) {
return -1;
cl::Platform newP = cl::Platform::setDefault(plat);
std::cout << 'Error setting default platform.';
}
// Use C++11 raw string literals for kernel source code
global int globalA;
{
}
std::string kernel2{R'CLC(
kernel void vectorAdd(global const Foo* aNum, global const int *inputA, global const int *inputB,
global int *output, int val, write_only pipe int outPipe, queue_t childQueue)
output[get_global_id(0)] = inputA[get_global_id(0)] + inputB[get_global_id(0)] + val + *(aNum->bar);
queue_t default_queue = get_default_queue();
ndrange_t ndrange = ndrange_1D(get_global_size(0)/2, get_global_size(0)/2);
// Have a child kernel write into third quarter of output
enqueue_kernel(default_queue, CLK_ENQUEUE_FLAGS_WAIT_KERNEL, ndrange,
output[get_global_size(0)*2 + get_global_id(0)] =
inputA[get_global_size(0)*2 + get_global_id(0)] + inputB[get_global_size(0)*2 + get_global_id(0)] + globalA;
// Have a child kernel write into last quarter of output
enqueue_kernel(childQueue, CLK_ENQUEUE_FLAGS_WAIT_KERNEL, ndrange,
output[get_global_size(0)*3 + get_global_id(0)] =
inputA[get_global_size(0)*3 + get_global_id(0)] + inputB[get_global_size(0)*3 + get_global_id(0)] + globalA + 2;
}
std::vector<std::string> programStrings {kernel1, kernel2};
cl::Program vectorAddProgram(programStrings);
vectorAddProgram.build('-cl-std=CL2.0');
catch (..) {
cl_int buildErr = CL_SUCCESS;
auto buildInfo = vectorAddProgram.getBuildInfo<CL_PROGRAM_BUILD_LOG>(&buildErr);
std::cerr << pair.second << std::endl << std::endl;
}
typedefstruct { int *bar; } Foo;
// Get and run kernel that initializes the program-scope global
auto program2Kernel =
cl::KernelFunctor<>(vectorAddProgram, 'updateGlobal');
cl::EnqueueArgs(
auto anSVMInt = cl::allocate_svm<int, cl::SVMTraitCoarse<>>();
cl::SVMAllocator<Foo, cl::SVMTraitCoarse<cl::SVMTraitReadOnly<>>> svmAllocReadOnly;
auto fooPointer = cl::allocate_pointer<Foo>(svmAllocReadOnly);
cl::SVMAllocator<int, cl::SVMTraitCoarse<>> svmAlloc;
std::vector<int, cl::SVMAllocator<int, cl::SVMTraitCoarse<>>> inputA(numElements, 1, svmAlloc);
cl::coarse_svm_vector<int> inputB(numElements, 2, svmAlloc);
//
// Traditional cl_mem allocations
std::vector<int> output(numElements, 0xdeadbeef);
cl::Buffer outputBuffer(begin(output), end(output), false);
// Default command queue, also passed in as a parameter
cl::DeviceCommandQueue defaultDeviceQueue = cl::DeviceCommandQueue::makeDefault(
cl::Context::getDefault(), cl::Device::getDefault());
auto vectorAddKernel =
decltype(fooPointer)&,
cl::coarse_svm_vector<int>&,
int,
// Ensure that the additional SVM pointer is available to the kernel
vectorAddKernel.setSVMPointers(anSVMInt);
// Hand control of coarse allocations to runtime
cl::enqueueUnmapSVM(fooPointer);
cl::unmapSVM(output2);
cl_int error;
cl::EnqueueArgs(
cl::NDRange(numElements/2)),
inputA.data(),
outputBuffer,
aPipe,
error
cl::copy(outputBuffer, begin(output), end(output));
cl::mapSVM(output2);
cl::Device d = cl::Device::getDefault();
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std::cout << 'Output:n';
std::cout << 't' << output[i] << 'n';
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std::cout << 'nn';
return 0;