Comments (3)
Here is what deviceQuery
[1] from CUDA sample says:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GP10B"
CUDA Driver Version / Runtime Version 8.5 / 8.0
CUDA Capability Major/Minor version number: 6.2
Total amount of global memory: 7854 MBytes (8235356160 bytes)
( 2) Multiprocessors, (128) CUDA Cores/MP: 256 CUDA Cores
GPU Max Clock rate: 1301 MHz (1.30 GHz)
Memory Clock rate: 13 Mhz
Memory Bus Width: 64-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: 32768
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 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 = 8.5, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GP10B
Result = PASS
[1]
https://gist.github.com/ingenieroariel/c4e8e1299be58a5b852d91d85ba7da24
from heavydb.
The most likely cause is that the GPU detection in startmapd
isn't properly handling the Jetson. This detection is actually not required anymore now that mapd_server
can handle it, so I've removed it.
Could you do a git pull
to pick up the new version of startmapd
to see if that helps? Commit f694c47.
A second potential cause is not having permission to access the GPU devices, which I've seen happen in older versions of L4T if not using the default user. This is probably not it in your case since the samples work and you're using the default nvidia
user.
from heavydb.
I get no warnings now. Thanks!
from heavydb.
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