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author | Derick Huth <derickhuth@gmail.com> | 2015-09-24 11:26:53 -0600 |
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committer | Derick Huth <derickhuth@gmail.com> | 2015-09-24 11:26:53 -0600 |
commit | c285135eb903c31cd221f90f03e288a6b67770cd (patch) | |
tree | 1f6ea3120a09feef7236dac579d5a2d5b774aaa7 /examples/cuda-chill/tmv-shadow.lua | |
parent | f5c39e4c6ff55520948c2ef331c968cd84b817d9 (diff) | |
download | chill-c285135eb903c31cd221f90f03e288a6b67770cd.tar.gz chill-c285135eb903c31cd221f90f03e288a6b67770cd.tar.bz2 chill-c285135eb903c31cd221f90f03e288a6b67770cd.zip |
pre-v0.2.1
Diffstat (limited to 'examples/cuda-chill/tmv-shadow.lua')
-rw-r--r-- | examples/cuda-chill/tmv-shadow.lua | 50 |
1 files changed, 0 insertions, 50 deletions
diff --git a/examples/cuda-chill/tmv-shadow.lua b/examples/cuda-chill/tmv-shadow.lua deleted file mode 100644 index 196b939..0000000 --- a/examples/cuda-chill/tmv-shadow.lua +++ /dev/null @@ -1,50 +0,0 @@ -init("tmv-shadow.c","normalMV",0) -dofile("cudaize.lua") --defines custom tile_by_index, copy_to_registers, - --copy_to_shared methods - -N=1024 ---N= 8209 ---N=129 -TI=64 -N=1024 -TI=32 ---tile, "k" for the control loop for the "j" tile, with the final order ---of {"ii", "k", "i", "j"} -tile_by_index({"i","j"}, {TI,TI}, {l1_control="ii", l2_control="k"}, {"ii", "k", "i", "j"}) ---tile_by_index({"i"}, {TI}, {l1_control="ii"}, {"ii", "i", "j"}) ---print_code() ---tile_by_index({"i"}, {TI/32}, {l1_control="iii"}, {"ii", "k", "iii","i", "j"}) - ---print_code() ---Normalize indx will do a tile size of one over the loop level specified ---by the input index. This is useful to get a zero lower bound and hard ---upper bound on a loop instead of it being relative to previous loop ---levels. ---normalize_index("i") ---print_code() - ---Cudaize now determines the grid dimentions from the loops themselves ---(the upper bounds of the block and thread loops). It also renames the ---given block and thread loops's indexes to the approviate values from ---the set {"bx","by","tx","ty","tz"}. The second parameter specifies the ---size of the arrays to be copied in the CUDA scaffolding. -cudaize("tmv_GPU", {a=N, b=N, c=N*N},{block={"ii"}, thread={"i"}}) - ---print_code() - ---Does a datacopy, tile, and add_sync to get a shared memory copy -copy_to_shared("tx", "b", 1) ---copy_to_texture("b") ---print_code() - -copy_to_shared("tx", "c", -16) ---copy_to_texture("c") ---print_code() - -copy_to_registers("k", "a") -print_code() ---unroll(0,5,0) ---unroll(0,4,0) ---unroll(2,4,16) -unroll_to_depth(1) ---print_code() |