![]() ![]() If you set this parameter to Yes, the compiler may flush single-precision denormalized numbers to zero it may also flush double-precision denormalized numbers to zero if the optional extension for double-precision is supported. This Boolean controls how single- and double-precision denormalized numbers are handled. If you set this parameter to Yes, the compiler treats double-precision floating-point expressions as single-precision floating-point expressions. This setting takes effect only for the CPU.ĭouble as single. Choose Yes to turn the autovectorizer on or No to turn the autovectorizer off. The default is OpenCL C 1.1.Īuto-vectorizer. The dropdown allows you to choose up to three of -triple i386-applecl-darwin, -triple x86_64-applecl-darwin, and -triple gpu_32-applecl-darwin. The default is that the product is built for all three architectures. You can set the following build settings for your OpenCL apps: Figure 1-1 A simple OpenCL kernel in Xcode Figure 1-1 shows a very simple OpenCL project in Xcode. ![]() (You can change which bitcodes are generated using the OpenCL Architectures build setting.)Īt runtime your host application discovers the available devices and determines which of the compiled kernels to enqueue and execute. cl file is compiled by default into three files containing bitcode for i386, x86_64, and gpu_32 architectures. You can also include non-kernel code that will run on the same OpenCL device as the kernel in each. cl file, or you can separate them as you choose. You can place all your kernels into a single. To create a project that uses OpenCL in OS X v10.7 or later:Ĭreate your OpenCL project in Xcode as a new OS X project (empty is fine). (You don’t have to regenerate OpenCL projects that are already working.) Creating An Application That Uses OpenCL In Xcode This chapter describes how to create an OpenCL project in Xcode. Support built into Xcode in OS X v10.7 and later makes developing OpenCL applications much easier than it used to be. To create high-performance code on GPUs, use the Metal framework instead.
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