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In Figure11, we evaluate the new algorithm for computing the wavelet transform using the shared memory.
Theoretically, the approach of using the shared memory should be faster.
Those corrections can be done by using the shared memory of the host with the function thrust::for_each.
Threads can communicate with the other threads in the same block by using the shared memory efficiently.
MNS3 has the same parameters as MNS2, but MNS3 was implemented using the shared memory approach (see subsection 3.2).
The Parallella's implementation uses the shared memory space to store the packets.
Use the shared bank.
Moreover, threads within a block can communicate with each other by using the fast shared memory.
We used the GPU shared memory that is faster than the global memory.
Figure 5 shows threads and buffers used for communication in the shared memory pipeline.
The architecture of the OMAP3530 can interface the ARM and DSP processors using a shared memory.
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