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What is the difference between CUDA and OpenCL?
OpenCL is an open standard that can be used to program CPUs, GPUs, and other devices from different vendors, while CUDA is specific to NVIDIA GPUs. Although OpenCL promises a portable language for GPU programming, its generality may entail a performance penalty.
How do you pronounce SYCL?
SYCL (pronounced ‘sickle’) is a royalty-free, cross-platform abstraction layer that builds on the underlying concepts, portability and efficiency of OpenCL that enables code for heterogeneous processors to be written in a “single-source” style using completely standard C++.
How are shaders split up in the GPU?
If both how do you split that up so the GPU isn’t trying to parallel compute both the shader and another process at the same time It’s not quite correct, today, to think of compute shaders as being “in the shader pipeline” in the same sense that your vertex and fragment shaders are literally hooked up into a pipeline.
What does OpenCL allow you to do with memory?
What it allows you to do, though, is consume and produce memory resources also used by draw calls in a relatively efficient way. OpenCL makes this rather difficult (see for example https://software.intel.com/en-us/articles/opencl-and-opengl-interoperability-tutorial ).
How are compute shaders hooked up to the pipeline?
It’s not quite correct, today, to think of compute shaders as being “in the shader pipeline” in the same sense that your vertex and fragment shaders are literally hooked up into a pipeline. Compute shaders are not “hooked up” to anything currently, cannot drive rasterization, or directly consume the outputs of rasterization.
Is the compute shader hooked up to rasterization?
Compute shaders are not “hooked up” to anything currently, cannot drive rasterization, or directly consume the outputs of rasterization. What it allows you to do, though, is consume and produce memory resources also used by draw calls in a relatively efficient way.