Optimum Number of blocks

[viral]

We have written a matrix addition program. We want to note the time taken to add 2 matrices.

The way we do it is :
matrix A [12816,256128]
matrix B [12816,256128]
matrix C [12816,256128]

here C will contain the final result…
Total Blocks we use is 128*16.
Threads/Block= 128

So effectively each thread/block is reading A[id], b[id] ,adding them and writing c[id]
in a loop 256 times.

Our Observations*
→ As we increase/decrease number of thread blocks, by keeping
the number of elements constant. i mean

matrix A [25616,128128]
matrix B [25616,128128]
matrix C [25616,128128]

here C will contain the final result…
Total Blocks we use is 256*16.
Threads/Block= 128

the times taken by the kernel change. Changes are dramatic in the sense its almost 1.5-1.7 times.

one naive thing could be system works better with more number of thread blocks. But is this mentioned anywhere?.

DOes anyone find/notice something like this?

[chris22]

You get better performance when you avoid pipeline stalls. More blocks can do that in some instances.

[viral]

You get better performance when you avoid pipeline stalls.  More blocks can do that in some instances.

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Can you pls elaborate your point. It will be nice if you can share something which you have observed.

[jlehtone]

one naive thing could be system works better with more number of thread blocks. But is this mentioned anywhere?

See chapter 5.2 (page 62) of CUDA Programming Guide Version 1.1.