How to decide ThreadPerBlock in customised cuda kernel?

[jahwan.oh]

https://github.com/dusty-nv/jetson-video/blob/8048023043e1edb513db56259c9637ee6bad9d8a/cuda/cudaResize.cu#L42

Hi,
I’m using AGX Xavier, and NX Xavier with customized cuda kernel.
I’m trying to understand how to decide <<<block, thread >>> value?

for example, I’m using 3840 x 2160 image and AGX Xavier (NVIDIA Xavier - Cuda))

in this case, how do you decide the value?

thank you.

[dusty_nv]

Hi @jahwan.oh, the maximum number of threads per block is one of the GPU specifications in CUDA, you can print them with deviceQuery utility:

Device 0: "Xavier"
  CUDA Driver Version / Runtime Version          10.2 / 10.2
  CUDA Capability Major/Minor version number:    7.2
  Total amount of global memory:                 31929 MBytes (33479647232 bytes)
  ( 8) Multiprocessors, ( 64) CUDA Cores/MP:     512 CUDA Cores
  GPU Max Clock rate:                            1377 MHz (1.38 GHz)
  Memory Clock rate:                             1377 Mhz
  Memory Bus Width:                              256-bit
  L2 Cache Size:                                 524288 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
  Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 65536
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  2048
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 1 copy engine(s)
  Run time limit on kernels:                     No
  Integrated GPU sharing Host Memory:            Yes
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Disabled
  Device supports Unified Addressing (UVA):      Yes
  Device supports Compute Preemption:            Yes
  Supports Cooperative Kernel Launch:            Yes
  Supports MultiDevice Co-op Kernel Launch:      Yes
  Device PCI Domain ID / Bus ID / location ID:   0 / 0 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.2, CUDA Runtime Version = 10.2, NumDevs = 1
Result = PASS

So for AGX Xavier, it’s Maximum number of threads per block: 1024 (or 32x32)

The reason that I use a smaller value of 8x8 is this code supports older Tegra devices going back to TX1.