use two parallel reduction, still have bugs
confusing bug
maybe bank conflict
fix the parallel reduction bug: missing elements
Merge branch 'master' into testing

Conflicts:
	knn.cu
tile input to compute dist, 32*32 tile, two 32*128 vectors, but slower...
smaller blockDim to get better occupancy, but slower...
modify paralle reduction to allow smaller blockSize
support large-scale data, findMin pr algorithm is modified
use mem coalescing in computeDist
use mem coalescing in computeDist
final coalescing method
use larger blockDim(1024) and smaller sharedMem(8196), occupancy is poor
but performance is better
smaller sharedMem of 16384, not better than 8192
smaller sharedMem of 4096, not better than 8192
set sharedMem size to 8192, best until now
change timing
fail complete unroll
unroll last warp
only unroll last warp