I have implemented few normal looping applications in OpenMP, TBB and OpenCL. In all these applications, OpeCL gives far better performance than others too when I am only running it on CPU with no spe
I have some general parameters declared as a global (__constant) struct, like so: typedef struct { int a;
In CUDA, there is a concept of a warp, which is defined as 开发者_JAVA技巧the maximum number of threads that can execute the same instruction simultaneously within a single processing element.For NVID
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I\'m working on an algorithm that does prettymuch the same operation a bunch of times. Since the operation consists of some linear algebra(BLAS), I thourght I would try using the GPU for this.
Can I have two mixed chipset/generation AMD gpus in my desktop; a 6950 and 4870, and dedicate one gpu (4870) for opencl/gpgpu purposes only, eliminating the device from video output or display driving
I\'ve got one program which creates 3 worker programs. The preferable method of communication in my situation would be through a memory buffer which all four programs may access.
I\'m currently implementing an algorithm that does allot of linear algebra on small matrices and vectors. the code is fast but I\'m wondering if it would make sense to implement it on a gpgpu instead
In OpenCL, my understanding is that you can use the barrier() function to synchronize threads in a work group.I do (generally) understand what they are for and when to use them.I\'m also aware that al
I\'ve been wondering, is there a way to estimate the mount of shared mem on the different GPGPU\'s without going out and buying the cards?
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