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Fix various problems with use of shared memory.
If the entire subdomain is read into the shared memory on the GPU, the performance is limited by the high use of shared memory.
One of the solutions proposed exploiting CUDA is quite close to ours at least in terms of thread organization and in the use of shared memory.
Among these resources are the use of texture memory, which is faster for handling read-only data, to store the lookup-tables employed by the marching cubes algorithm and the volume data itself, and the use of shared memory, which permits the data sharing among threads contained in a same block, besides being faster than the standard video memory.
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Although Fermi features an L1 cache, the performance when using this implicit (true) caching method is found to be significantly inferior to the explicit caching scheme which configures the GPU to use 48 kB of shared memory.
Under industry legend Seymour Cray, the company pioneered the "vector" supercomputer, a machine of breathtaking raw power that uses massive amounts of shared memory to solve complex mathematical problems.
The Intel X3100 setting uses up to 358MB of shared memory and the NVIDIA GeForce 8400M GS uses up to 831MB.
GPU occupancy is defined by the combination of the number of threads, the number of registers used by each thread and the amount of shared memory used by each thread.
Maximizing occupancy entails writing kernel code and executing the kernel in a configuration that maximizes the number of threads while minimizing the number of registers and amount of shared memory used by each thread.
To perform the reduction, two arrays of shared memory are used.
Similarly, unless explicitly specified, the maximum amount of shared memory available was used for caching of the high-fluence region of the A[ r][ z] array.
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